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driving</title> <meta name="description" content="Search results for: cognitive driving"> <meta name="keywords" content="cognitive driving"> <meta name="viewport" content="width=device-width, initial-scale=1, minimum-scale=1, maximum-scale=1, user-scalable=no"> <meta charset="utf-8"> <link href="https://cdn.waset.org/favicon.ico" type="image/x-icon" rel="shortcut icon"> <link href="https://cdn.waset.org/static/plugins/bootstrap-4.2.1/css/bootstrap.min.css" rel="stylesheet"> <link href="https://cdn.waset.org/static/plugins/fontawesome/css/all.min.css" rel="stylesheet"> <link href="https://cdn.waset.org/static/css/site.css?v=150220211555" rel="stylesheet"> </head> <body> <header> <div class="container"> <nav class="navbar navbar-expand-lg navbar-light"> <a class="navbar-brand" href="https://waset.org"> <img src="https://cdn.waset.org/static/images/wasetc.png" alt="Open Science Research Excellence" title="Open Science Research Excellence" /> </a> <button class="d-block d-lg-none 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action="https://publications.waset.org/abstracts/search"> <div id="custom-search-input"> <div class="input-group"> <i class="fas fa-search"></i> <input type="text" class="search-query" name="q" placeholder="Author, Title, Abstract, Keywords" value="cognitive driving"> <input type="submit" class="btn_search" value="Search"> </div> </div> </form> </div> </div> <div class="row mt-3"> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Commenced</strong> in January 2007</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Frequency:</strong> Monthly</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Edition:</strong> International</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Paper Count:</strong> 2817</div> </div> </div> </div> <h1 class="mt-3 mb-3 text-center" style="font-size:1.6rem;">Search results for: cognitive driving</h1> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2817</span> Cognition of Driving Context for Driving Assistance</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Manolo%20Dulva%20Hina">Manolo Dulva Hina</a>, <a href="https://publications.waset.org/abstracts/search?q=Clement%20Thierry"> Clement Thierry</a>, <a href="https://publications.waset.org/abstracts/search?q=Assia%20Soukane"> Assia Soukane</a>, <a href="https://publications.waset.org/abstracts/search?q=Amar%20Ramdane-Cherif"> Amar Ramdane-Cherif</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper, we presented our innovative way of determining the driving context for a driving assistance system. We invoke the fusion of all parameters that describe the context of the environment, the vehicle and the driver to obtain the driving context. We created a training set that stores driving situation patterns and from which the system consults to determine the driving situation. A machine-learning algorithm predicts the driving situation. The driving situation is an input to the fission process that yields the action that must be implemented when the driver needs to be informed or assisted from the given the driving situation. The action may be directed towards the driver, the vehicle or both. This is an ongoing work whose goal is to offer an alternative driving assistance system for safe driving, green driving and comfortable driving. Here, ontologies are used for knowledge representation. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=cognitive%20driving" title="cognitive driving">cognitive driving</a>, <a href="https://publications.waset.org/abstracts/search?q=intelligent%20transportation%20system" title=" intelligent transportation system"> intelligent transportation system</a>, <a href="https://publications.waset.org/abstracts/search?q=multimodal%20system" title=" multimodal system"> multimodal system</a>, <a href="https://publications.waset.org/abstracts/search?q=ontology" title=" ontology"> ontology</a>, <a href="https://publications.waset.org/abstracts/search?q=machine%20learning" title=" machine learning"> machine learning</a> </p> <a href="https://publications.waset.org/abstracts/79015/cognition-of-driving-context-for-driving-assistance" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/79015.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">368</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2816</span> Head-Mounted Displays for HCI Validations While Driving</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=D.%20Reich">D. Reich</a>, <a href="https://publications.waset.org/abstracts/search?q=R.%20Stark"> R. Stark</a> </p> <p class="card-text"><strong>Abstract:</strong></p> To provide reliable and valid findings when evaluating innovative in-car devices in the automotive context highly realistic driving environments are recommended. Nowadays, in-car devices are mostly evaluated due to driving simulator studies followed by real car driving experiments. Driving simulators are characterized by high internal validity, but weak regarding ecological validity. Real car driving experiments are ecologically valid, but difficult to standardize, more time-robbing and costly. One economizing suggestion is to implement more immersive driving environments when applying driving simulator studies. This paper presents research comparing non-immersive standard PC conditions with mobile and highly immersive Oculus Rift conditions while performing the Lane Change Task (LCT). Subjective data with twenty participants show advantages regarding presence and immersion experience when performing the LCT with the Oculus Rift, but affect adversely cognitive workload and simulator sickness, compared to non-immersive PC condition. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=immersion" title="immersion">immersion</a>, <a href="https://publications.waset.org/abstracts/search?q=oculus%20rift" title=" oculus rift"> oculus rift</a>, <a href="https://publications.waset.org/abstracts/search?q=presence" title=" presence"> presence</a>, <a href="https://publications.waset.org/abstracts/search?q=situation%20awareness" title=" situation awareness"> situation awareness</a> </p> <a href="https://publications.waset.org/abstracts/54834/head-mounted-displays-for-hci-validations-while-driving" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/54834.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">190</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2815</span> The Correlation between Eye Movements, Attentional Shifting, and Driving Simulator Performance among Adolescents with Attention Deficit Hyperactivity Disorder</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Navah%20Z.%20Ratzon">Navah Z. Ratzon</a>, <a href="https://publications.waset.org/abstracts/search?q=Anat%20Keren"> Anat Keren</a>, <a href="https://publications.waset.org/abstracts/search?q=Shlomit%20Y.%20Greenberg"> Shlomit Y. Greenberg</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Car accidents are a problem worldwide. Adolescents’ involvement in car accidents is higher in comparison to the overall driving population. Researchers estimate the risk of accidents among adolescents with symptoms of attention-deficit/hyperactivity disorder (ADHD) to be 1.2 to 4 times higher than that of their peers. Individuals with ADHD exhibit unique patterns of eye movements and attentional shifts that play an important role in driving. In addition, deficiencies in cognitive and executive functions among adolescents with ADHD is likely to put them at greater risk for car accidents. Fifteen adolescents with ADHD and 17 matched controls participated in the study. Individuals from both groups attended local public schools and did not have a driver’s license. Participants’ mean age was 16.1 (SD=.23). As part of the experiment, they all completed a driving simulation session, while their eye movements were monitored. Data were recorded by an eye tracker: The entire driving session was recorded, registering the tester’s exact gaze position directly on the screen. Eye movements and simulator data were analyzed using Matlab (Mathworks, USA). Participants’ cognitive and metacognitive abilities were evaluated as well. No correlation was found between saccade properties, regions of interest, and simulator performance in either group, although participants with ADHD allocated more visual scan time (25%, SD = .13%) to a smaller segment of dashboard area, whereas controls scanned the monitor more evenly (15%, SD = .05%). The visual scan pattern found among participants with ADHD indicates a distinct pattern of engagement-disengagement of spatial attention compared to that of non-ADHD participants as well as lower attention flexibility, which likely affects driving. Additionally the lower the results on the cognitive tests, the worse driving performance was. None of the participants had prior driving experience, yet participants with ADHD distinctly demonstrated difficulties in scanning their surroundings, which may impair driving. This stresses the need to consider intervention programs, before driving lessons begin, to help adolescents with ADHD acquire proper driving habits, avoid typical driving errors, and achieve safer driving. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=ADHD" title="ADHD">ADHD</a>, <a href="https://publications.waset.org/abstracts/search?q=attentional%20shifting" title=" attentional shifting"> attentional shifting</a>, <a href="https://publications.waset.org/abstracts/search?q=driving%20simulator" title=" driving simulator"> driving simulator</a>, <a href="https://publications.waset.org/abstracts/search?q=eye%20movements" title=" eye movements"> eye movements</a> </p> <a href="https://publications.waset.org/abstracts/65630/the-correlation-between-eye-movements-attentional-shifting-and-driving-simulator-performance-among-adolescents-with-attention-deficit-hyperactivity-disorder" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/65630.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">329</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2814</span> Developing a Driving Simulator with a Navigation System to Measure Driver Distraction, Workload, Driving Safety and Performance</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Tamer%20E.%20Yared">Tamer E. Yared</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The use of driving simulators has made laboratory testing easier. It has been proven to be valid for testing driving ability by many researchers. One benefit of using driving simulators is keeping the human subjects away from traffic hazards, which drivers usually face in a real driving environment while performing a driving experiment. In this study, a driving simulator was developed with a navigation system using a game development software (Unity 3D) and C-sharp codes to measure and evaluate driving performance, safety, and workload for different driving tasks. The driving simulator hardware included a gaming steering wheel and pedals as well as a monitor to view the driving tasks. Moreover, driver distraction was evaluated by utilizing an eye-tracking system working in conjunction with the driving simulator. Twenty subjects were recruited to evaluate driver distraction, workload, driving safety, and performance, as well as provide their feedback about the driving simulator. The subjects’ feedback was obtained by filling a survey after conducting several driving tasks. The main question of that survey was asking the subjects to compare driving on the driving simulator with real driving. Furthermore, other aspects of the driving simulator were evaluated by the subjects in the survey. The survey revealed that the recruited subjects gave an average score of 7.5 out of 10 to the driving simulator when compared to real driving, where the scores ranged between 6 and 8.5. This study is a preliminary effort that opens the door for more improvements to the driving simulator in terms of hardware and software development, which will contribute significantly to driving ability testing. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=driver%20distraction" title="driver distraction">driver distraction</a>, <a href="https://publications.waset.org/abstracts/search?q=driving%20performance" title=" driving performance"> driving performance</a>, <a href="https://publications.waset.org/abstracts/search?q=driving%20safety" title=" driving safety"> driving safety</a>, <a href="https://publications.waset.org/abstracts/search?q=driving%20simulator" title=" driving simulator"> driving simulator</a>, <a href="https://publications.waset.org/abstracts/search?q=driving%20workload" title=" driving workload"> driving workload</a>, <a href="https://publications.waset.org/abstracts/search?q=navigation%20system" title=" navigation system"> navigation system</a> </p> <a href="https://publications.waset.org/abstracts/132536/developing-a-driving-simulator-with-a-navigation-system-to-measure-driver-distraction-workload-driving-safety-and-performance" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/132536.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">178</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2813</span> Estimating the Efficiency of a Meta-Cognitive Intervention Program to Reduce the Risk Factors of Teenage Drivers with Attention Deficit Hyperactivity Disorder While Driving</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Navah%20Z.%20Ratzon">Navah Z. Ratzon</a>, <a href="https://publications.waset.org/abstracts/search?q=Talia%20Glick"> Talia Glick</a>, <a href="https://publications.waset.org/abstracts/search?q=Iris%20Manor"> Iris Manor</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Attention Deficit Hyperactivity Disorder (ADHD) is a chronic disorder that affects the sufferer’s functioning throughout life and in various spheres of activity, including driving. Difficulties in cognitive functioning and executive functions are often part and parcel of the ADHD diagnosis, and thus form a risk factor in driving. Studies examining the effectiveness of intervention programs for improving and rehabilitating driving in typical teenagers have been conducted in relatively small numbers; while studies on similar programs for teenagers with ADHD have been especially scarce. The aim of the present study has been to examine the effectiveness of a metacognitive occupational therapy intervention program for reducing risk factors in driving among teenagers with ADHD. The present study included 37 teenagers aged 17 to 19. They included 23 teenagers with ADHD divided into experimental (11) and control (12) groups; as well as 14 non-ADHD teenagers forming a second control group. All teenagers taking part in the study were examined in the Tel Aviv University driving lab, and underwent cognitive diagnoses and a driving simulator test. Every subject in the intervention group took part in 3 assessment meetings, and two metacognitive treatment meetings. The control groups took part in two assessment meetings with a follow-up meeting 3 months later. In all the study’s groups, the treatment’s effectiveness was tested by comparing monitoring results on the driving simulator at the first and second evaluations. In addition, the driving of 5 subjects from the intervention group was monitored continuously from a month prior to the start of the intervention, a month during the phase of the intervention and another month until the end of the intervention. In the ADHD control group, the driving of 4 subjects was monitored from the end of the first evaluation for a period of 3 months. The study’s findings were affected by the fact that the ADHD control group was different from the two other groups, and exhibited ADHD characteristics manifested by impaired executive functions and lower metacognitive abilities relative to their peers. The study found partial, moderate, non-significant correlations between driving skills and cognitive functions, executive functions, and perceptions and attitudes towards driving. According to the driving simulator test results and the limited sampling results of actual driving, it was found that a metacognitive occupational therapy intervention may be effective in reducing risk factors in driving among teenagers with ADHD relative to their peers with and without ADHD. In summary, the results of the present study indicate a positive direction that speaks to the viability of using a metacognitive occupational therapy intervention program for reducing risk factors in driving. A further study is required that will include a bigger number of subjects, add actual driving monitoring hours, and assign subjects randomly to the various groups. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=ADHD" title="ADHD">ADHD</a>, <a href="https://publications.waset.org/abstracts/search?q=driving" title=" driving"> driving</a>, <a href="https://publications.waset.org/abstracts/search?q=driving%20monitoring" title=" driving monitoring"> driving monitoring</a>, <a href="https://publications.waset.org/abstracts/search?q=metacognitive%20intervention" title=" metacognitive intervention"> metacognitive intervention</a>, <a href="https://publications.waset.org/abstracts/search?q=occupational%20therapy" title=" occupational therapy"> occupational therapy</a>, <a href="https://publications.waset.org/abstracts/search?q=simulator" title=" simulator"> simulator</a>, <a href="https://publications.waset.org/abstracts/search?q=teenagers" title=" teenagers"> teenagers</a> </p> <a href="https://publications.waset.org/abstracts/65440/estimating-the-efficiency-of-a-meta-cognitive-intervention-program-to-reduce-the-risk-factors-of-teenage-drivers-with-attention-deficit-hyperactivity-disorder-while-driving" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/65440.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">306</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2812</span> Effects of Cannabis and Cocaine on Driving Related Tasks of Perception, Cognition, and Action</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Michelle%20V.%20Tomczak">Michelle V. Tomczak</a>, <a href="https://publications.waset.org/abstracts/search?q=Reyhaneh%20Bakhtiari"> Reyhaneh Bakhtiari</a>, <a href="https://publications.waset.org/abstracts/search?q=Aaron%20Granley"> Aaron Granley</a>, <a href="https://publications.waset.org/abstracts/search?q=Anthony%20Singhal"> Anthony Singhal</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Objective: Cannabis and cocaine are associated with a range of mental and physical effects that can impair aspects of human behavior. Driving is a complex cognitive behavior that is an essential part of everyday life and can be broken down into many subcomponents, each of which can uniquely impact road safety. With the growing movement of jurisdictions to legalize cannabis, there is an increased focus on impairment and driving. The purpose of this study was to identify driving-related cognitive-performance deficits that are impacted by recreational drug use. Design and Methods: With the assistance of law enforcement agencies, we recruited over 300 participants under the influence of various drugs including cannabis and cocaine. These individuals performed a battery of computer-based tasks scientifically proven to be re-lated to on-road driving performance and designed to test response-speed, memory processes, perceptual-motor skills, and decision making. Data from a control group with healthy non-drug using adults was collected as well. Results: Compared to controls, the drug group showed def-icits in all tasks. The data also showed clear differences between the cannabis and cocaine groups where cannabis users were faster, and performed better on some aspects of the decision-making and perceptual-motor tasks. Memory performance was better in the cocaine group for simple tasks but not more complex tasks. Finally, the participants who consumed both drugs performed most similarly to the cannabis group. Conclusions: Our results show distinct and combined effects of cannabis and cocaine on human performance relating to driving. These dif-ferential effects are likely related to the unique effects of each drug on the human brain and how they distinctly contribute to mental states. Our results have important implications for road safety associated with driver impairment. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=driving" title="driving">driving</a>, <a href="https://publications.waset.org/abstracts/search?q=cognitive%20impairment" title=" cognitive impairment"> cognitive impairment</a>, <a href="https://publications.waset.org/abstracts/search?q=recreational%20drug%20use" title=" recreational drug use"> recreational drug use</a>, <a href="https://publications.waset.org/abstracts/search?q=cannabis%20and%20cocaine" title=" cannabis and cocaine"> cannabis and cocaine</a> </p> <a href="https://publications.waset.org/abstracts/119099/effects-of-cannabis-and-cocaine-on-driving-related-tasks-of-perception-cognition-and-action" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/119099.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">126</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2811</span> Modeling Driving Distraction Considering Psychological-Physical Constraints</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Yixin%20Zhu">Yixin Zhu</a>, <a href="https://publications.waset.org/abstracts/search?q=Lishengsa%20Yue"> Lishengsa Yue</a>, <a href="https://publications.waset.org/abstracts/search?q=Jian%20Sun"> Jian Sun</a>, <a href="https://publications.waset.org/abstracts/search?q=Lanyue%20Tang"> Lanyue Tang</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Modeling driving distraction in microscopic traffic simulation is crucial for enhancing simulation accuracy. Current driving distraction models are mainly derived from physical motion constraints under distracted states, in which distraction-related error terms are added to existing microscopic driver models. However, the model accuracy is not very satisfying, due to a lack of modeling the cognitive mechanism underlying the distraction. This study models driving distraction based on the Queueing Network Human Processor model (QN-MHP). This study utilizes the queuing structure of the model to perform task invocation and switching for distracted operation and control of the vehicle under driver distraction. Based on the assumption of the QN-MHP model about the cognitive sub-network, server F is a structural bottleneck. The latter information must wait for the previous information to leave server F before it can be processed in server F. Therefore, the waiting time for task switching needs to be calculated. Since the QN-MHP model has different information processing paths for auditory information and visual information, this study divides driving distraction into two types: auditory distraction and visual distraction. For visual distraction, both the visual distraction task and the driving task need to go through the visual perception sub-network, and the stimuli of the two are asynchronous, which is called stimulus on asynchrony (SOA), so when calculating the waiting time for switching tasks, it is necessary to consider it. In the case of auditory distraction, the auditory distraction task and the driving task do not need to compete for the server resources of the perceptual sub-network, and their stimuli can be synchronized without considering the time difference in receiving the stimuli. According to the Theory of Planned Behavior for drivers (TPB), this study uses risk entropy as the decision criterion for driver task switching. A logistic regression model is used with risk entropy as the independent variable to determine whether the driver performs a distraction task, to explain the relationship between perceived risk and distraction. Furthermore, to model a driver’s perception characteristics, a neurophysiological model of visual distraction tasks is incorporated into the QN-MHP, and executes the classical Intelligent Driver Model. The proposed driving distraction model integrates the psychological cognitive process of a driver with the physical motion characteristics, resulting in both high accuracy and interpretability. This paper uses 773 segments of distracted car-following in Shanghai Naturalistic Driving Study data (SH-NDS) to classify the patterns of distracted behavior on different road facilities and obtains three types of distraction patterns: numbness, delay, and aggressiveness. The model was calibrated and verified by simulation. The results indicate that the model can effectively simulate the distracted car-following behavior of different patterns on various roadway facilities, and its performance is better than the traditional IDM model with distraction-related error terms. The proposed model overcomes the limitations of physical-constraints-based models in replicating dangerous driving behaviors, and internal characteristics of an individual. Moreover, the model is demonstrated to effectively generate more dangerous distracted driving scenarios, which can be used to construct high-value automated driving test scenarios. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=computational%20cognitive%20model" title="computational cognitive model">computational cognitive model</a>, <a href="https://publications.waset.org/abstracts/search?q=driving%20distraction" title=" driving distraction"> driving distraction</a>, <a href="https://publications.waset.org/abstracts/search?q=microscopic%20traffic%20simulation" title=" microscopic traffic simulation"> microscopic traffic simulation</a>, <a href="https://publications.waset.org/abstracts/search?q=psychological-physical%20constraints" title=" psychological-physical constraints"> psychological-physical constraints</a> </p> <a href="https://publications.waset.org/abstracts/166497/modeling-driving-distraction-considering-psychological-physical-constraints" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/166497.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">91</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2810</span> Motorist Driving Strategy-Related Factors Affecting Vehicle Fuel Efficiency</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Aydin%20Azizi">Aydin Azizi</a>, <a href="https://publications.waset.org/abstracts/search?q=Abdurrahman%20Tanira"> Abdurrahman Tanira</a> </p> <p class="card-text"><strong>Abstract:</strong></p> With the onset of climate change and limited fuel resources, improving fuel efficiency has become an important part of the motor industry. To maximize fuel efficiency, development of technologies must come hand-in-hand with awareness of efficient driving strategies. This study aims to explore the various driving habits that can impact fuel efficiency by reviewing available literature. Such habits include sudden and unnecessary acceleration or deceleration, improper hardware maintenance, driving above or below optimum speed and idling. By studying such habits and ultimately applying it to driving techniques, in combination with improved mechanics of the car, will optimize the use of fuel. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=fuel%20efficiency" title="fuel efficiency">fuel efficiency</a>, <a href="https://publications.waset.org/abstracts/search?q=driving%20techniques" title=" driving techniques"> driving techniques</a>, <a href="https://publications.waset.org/abstracts/search?q=optimum%20speed" title=" optimum speed"> optimum speed</a>, <a href="https://publications.waset.org/abstracts/search?q=optimizing%20fuel%20consumption" title=" optimizing fuel consumption"> optimizing fuel consumption</a> </p> <a href="https://publications.waset.org/abstracts/44070/motorist-driving-strategy-related-factors-affecting-vehicle-fuel-efficiency" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/44070.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">460</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2809</span> Attitude and Perception of Non-emergency Vehicle Drivers on Roads Towards Medical Emergency Vehicles: The Role of Empathy and Pro-Social Skills</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Purnima%20K%20Bajre">Purnima K Bajre</a>, <a href="https://publications.waset.org/abstracts/search?q=Rujula%20Talloo"> Rujula Talloo</a> </p> <p class="card-text"><strong>Abstract:</strong></p> A variety of vehicles are driven on roads such as private vehicles, commercial vehicles, public vehicles, and emergency service vehicles (EMV). Drivers driving different vehicles can have attitude differences towards emergency service vehicles which in turn affects their likelihood to give way to them. The present review aims to understand the factors that mediate this yielding behavior of drivers towards EMVs. Through extensive review of available literature, factors such as effects of lights and sirens, cognitive load, age of the driver, driving general experience, traffic load, drivers’ experience and training with EMVs and drivers’ attitude towards EMV drivers, have emerged as mediating factors. Whereas cognitive load is the most researched area and is observed to be associated negatively with on road drivers’ attitudes towards EMVs, there is a paucity of research to understand the relationships between empathy, pro-social skills, and on road drivers’ attitude towards EMVs. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=cognitive%20load" title="cognitive load">cognitive load</a>, <a href="https://publications.waset.org/abstracts/search?q=emergency%20service%20vehicle" title=" emergency service vehicle"> emergency service vehicle</a>, <a href="https://publications.waset.org/abstracts/search?q=empathy" title=" empathy"> empathy</a>, <a href="https://publications.waset.org/abstracts/search?q=traffic%20load" title=" traffic load"> traffic load</a> </p> <a href="https://publications.waset.org/abstracts/191314/attitude-and-perception-of-non-emergency-vehicle-drivers-on-roads-towards-medical-emergency-vehicles-the-role-of-empathy-and-pro-social-skills" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/191314.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">31</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2808</span> Expert-Driving-Criteria Based on Fuzzy Logic Approach for Intelligent Driving Diagnosis</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Andr%C3%A9s%20C.%20Cuervo%20Pinilla">Andrés C. Cuervo Pinilla</a>, <a href="https://publications.waset.org/abstracts/search?q=Christian%20G.%20Quintero%20M."> Christian G. Quintero M.</a>, <a href="https://publications.waset.org/abstracts/search?q=Chinthaka%20Premachandra"> Chinthaka Premachandra</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper considers people’s driving skills diagnosis under real driving conditions. In that sense, this research presents an approach that uses GPS signals which have a direct correlation with driving maneuvers. Besides, it is presented a novel expert-driving-criteria approximation using fuzzy logic which seeks to analyze GPS signals in order to issue an intelligent driving diagnosis. Based on above, this works presents in the first section the intelligent driving diagnosis system approach in terms of its own characteristics properties, explaining in detail significant considerations about how an expert-driving-criteria approximation must be developed. In the next section, the implementation of our developed system based on the proposed fuzzy logic approach is explained. Here, a proposed set of rules which corresponds to a quantitative abstraction of some traffics laws and driving secure techniques seeking to approach an expert-driving- criteria approximation is presented. Experimental testing has been performed in real driving conditions. The testing results show that the intelligent driving diagnosis system qualifies driver’s performance quantitatively with a high degree of reliability. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=driver%20support%20systems" title="driver support systems">driver support systems</a>, <a href="https://publications.waset.org/abstracts/search?q=intelligent%20transportation%20systems" title=" intelligent transportation systems"> intelligent transportation systems</a>, <a href="https://publications.waset.org/abstracts/search?q=fuzzy%20logic" title=" fuzzy logic"> fuzzy logic</a>, <a href="https://publications.waset.org/abstracts/search?q=real%20time%20data%20processing" title=" real time data processing"> real time data processing</a> </p> <a href="https://publications.waset.org/abstracts/6508/expert-driving-criteria-based-on-fuzzy-logic-approach-for-intelligent-driving-diagnosis" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/6508.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">518</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2807</span> The Effects of Billboard Content and Visible Distance on Driver Behavior</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Arsalan%20Hassan%20Pour">Arsalan Hassan Pour</a>, <a href="https://publications.waset.org/abstracts/search?q=Mansoureh%20Jeihani"> Mansoureh Jeihani</a>, <a href="https://publications.waset.org/abstracts/search?q=Samira%20%20Ahangari"> Samira Ahangari</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Distracted driving has been one of the most integral concerns surrounding our daily use of vehicles since the invention of the automobile. While much attention has been recently given to cell phones related distraction, commercial billboards along roads are also candidates for drivers' visual and cognitive distractions, as they may take drivers’ eyes from the road and their minds off the driving task to see, perceive and think about the billboard’s content. Using a driving simulator and a head-mounted eye-tracking system, speed change, acceleration, deceleration, throttle response, collision, lane changing, and offset from the center of the lane data along with gaze fixation duration and frequency data were collected in this study. Some 92 participants from a fairly diverse sociodemographic background drove on a simulated freeway in Baltimore, Maryland area and were exposed to three different billboards to investigate the effects of billboards on drivers’ behavior. Participants glanced at the billboards several times with different frequencies, the maximum of which occurred on the billboard with the highest cognitive load. About 74% of the participants didn’t look at billboards for more than two seconds at each glance except for the billboard with a short visible area. Analysis of variance (ANOVA) was performed to find the variations in driving behavior when they are invisible, readable, and post billboards area. The results show a slight difference in speed, throttle, brake, steering velocity, and lane changing, among different areas. Brake force and deviation from the center of the lane increased in the readable area in comparison with the visible area, and speed increased right after each billboard. The results indicated that billboards have a significant effect on driving performance and visual attention based on their content and visibility status. Generalized linear model (GLM) analysis showed no connection between participants’ age and driving experience with gaze duration. However, the visible distance of the billboard, gender, and billboard content had a significant effect on gaze duration. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=ANOVA" title="ANOVA">ANOVA</a>, <a href="https://publications.waset.org/abstracts/search?q=billboards" title=" billboards"> billboards</a>, <a href="https://publications.waset.org/abstracts/search?q=distracted%20driving" title=" distracted driving"> distracted driving</a>, <a href="https://publications.waset.org/abstracts/search?q=drivers%27%20behavior" title=" drivers' behavior"> drivers' behavior</a>, <a href="https://publications.waset.org/abstracts/search?q=driving%20simulator" title=" driving simulator"> driving simulator</a>, <a href="https://publications.waset.org/abstracts/search?q=eye-Tracking%20system" title=" eye-Tracking system"> eye-Tracking system</a>, <a href="https://publications.waset.org/abstracts/search?q=GLM" title=" GLM"> GLM</a> </p> <a href="https://publications.waset.org/abstracts/118543/the-effects-of-billboard-content-and-visible-distance-on-driver-behavior" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/118543.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">128</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2806</span> A Multi-Agent Urban Traffic Simulator for Generating Autonomous Driving Training Data</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Florin%20Leon">Florin Leon</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper describes a simulator of traffic scenarios tailored to facilitate autonomous driving model training for urban environments. With the rising prominence of self-driving vehicles, the need for diverse datasets is very important. The proposed simulator provides a flexible framework that allows the generation of custom scenarios needed for the validation and enhancement of trajectory prediction algorithms. Its controlled yet dynamic environment addresses the challenges associated with real-world data acquisition and ensures adaptability to diverse driving scenarios. By providing an adaptable solution for scenario creation and algorithm testing, this tool proves to be a valuable resource for advancing autonomous driving technology that aims to ensure safe and efficient self-driving vehicles. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=autonomous%20driving" title="autonomous driving">autonomous driving</a>, <a href="https://publications.waset.org/abstracts/search?q=car%20simulator" title=" car simulator"> car simulator</a>, <a href="https://publications.waset.org/abstracts/search?q=machine%20learning" title=" machine learning"> machine learning</a>, <a href="https://publications.waset.org/abstracts/search?q=model%20training" title=" model training"> model training</a>, <a href="https://publications.waset.org/abstracts/search?q=urban%20simulation%20environment" title=" urban simulation environment"> urban simulation environment</a> </p> <a href="https://publications.waset.org/abstracts/182587/a-multi-agent-urban-traffic-simulator-for-generating-autonomous-driving-training-data" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/182587.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">61</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2805</span> The Effects of Sleep Deprivation on Vigilance, Fatigue, and Performance during Simulated Train Driving</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Clara%20Theresia">Clara Theresia</a>, <a href="https://publications.waset.org/abstracts/search?q=Hardianto%20Iridiastadi"> Hardianto Iridiastadi</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Drowsiness is one of the main factors that contribute to the occurrence of accidents, particularly in the transportation sector. While the effects of sleep deprivation on cognitive functions have been reported, the exact relationships remain a critical issue. This study aimed at quantifying the effects of extreme sleep deprivation on vigilance, fatigue, and performance during simulated train driving. A total of 12 participants were asked to drive a train simulator continuously for 4 hours, either in a sleep deprived condition (2-hr of sleep) or normal (8-hr of sleep) condition. Dependent variables obtained during the task included Psychomotor Vigilance Task (PVT) parameters, degree of fatigue (assessed via Visual Analogue Scale/VAS) and sleepiness (reported using Karolinska Sleepiness Scale/KSS), and driving performance (the number of speed limit violations). Findings from this study demonstrated substantial decrements in vigilance in the sleep-deprived condition. This condition also resulted in 75% increase in speed violation and a two-fold increase in the degree of fatigue and sleepiness. Extreme sleep deprivation was clearly associated with substantially poorer response. The exact effects, however, were dependent upon the types of responses. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=cognitive%20function" title="cognitive function">cognitive function</a>, <a href="https://publications.waset.org/abstracts/search?q=psychomotor%20vigilance%20task" title=" psychomotor vigilance task"> psychomotor vigilance task</a>, <a href="https://publications.waset.org/abstracts/search?q=sleep%20deprivation" title=" sleep deprivation"> sleep deprivation</a>, <a href="https://publications.waset.org/abstracts/search?q=train%20simulator" title=" train simulator"> train simulator</a> </p> <a href="https://publications.waset.org/abstracts/80174/the-effects-of-sleep-deprivation-on-vigilance-fatigue-and-performance-during-simulated-train-driving" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/80174.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">186</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2804</span> Distracted Driving among Young Drivers in Qatar</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Khaled%20Shaaban">Khaled Shaaban</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Distracted driving, which includes anything that distracts a driver from the main task of driving, is one of the main causes of traffic accidents in modern societies. The objective of this research was to understand the type of activities that young drivers perform while driving in Qatar and to identify which activities cause the most distraction to the driver based on their experience. The data was collected through administered questionnaires in the city of Doha, Qatar. According to the participants, the majority reported that they use their cell phone all the time or occasionally while driving. Other significantly cited activities while driving included listening to music or radio, talking with passengers, and eating, drinking or smoking. When asked about the activities that distract the driver, using cell phone was listed as the most distracting activity followed by mental activities and adjusting GPS and audio device vehicle. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=driver%20distraction" title="driver distraction">driver distraction</a>, <a href="https://publications.waset.org/abstracts/search?q=young%20drivers" title=" young drivers"> young drivers</a>, <a href="https://publications.waset.org/abstracts/search?q=cell%20phone%20use" title=" cell phone use"> cell phone use</a>, <a href="https://publications.waset.org/abstracts/search?q=Qatar" title=" Qatar"> Qatar</a> </p> <a href="https://publications.waset.org/abstracts/16281/distracted-driving-among-young-drivers-in-qatar" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/16281.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">493</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2803</span> A Systematic Review of Situational Awareness and Cognitive Load Measurement in Driving</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Aly%20Elshafei">Aly Elshafei</a>, <a href="https://publications.waset.org/abstracts/search?q=Daniela%20Romano"> Daniela Romano</a> </p> <p class="card-text"><strong>Abstract:</strong></p> With the development of autonomous vehicles, a human-machine interaction (HMI) system is needed for a safe transition of control when a takeover request (TOR) is required. An important part of the HMI system is the ability to monitor the level of situational awareness (SA) of any driver in real-time, in different scenarios, and without any pre-calibration. Presenting state-of-the-art machine learning models used to measure SA is the purpose of this systematic review. Investigating the limitations of each type of sensor, the gaps, and the most suited sensor and computational model that can be used in driving applications. To the author’s best knowledge this is the first literature review identifying online and offline classification methods used to measure SA, explaining which measurements are subject or session-specific, and how many classifications can be done with each classification model. This information can be very useful for researchers measuring SA to identify the most suited model to measure SA for different applications. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=situational%20awareness" title="situational awareness">situational awareness</a>, <a href="https://publications.waset.org/abstracts/search?q=autonomous%20driving" title=" autonomous driving"> autonomous driving</a>, <a href="https://publications.waset.org/abstracts/search?q=gaze%20metrics" title=" gaze metrics"> gaze metrics</a>, <a href="https://publications.waset.org/abstracts/search?q=EEG" title=" EEG"> EEG</a>, <a href="https://publications.waset.org/abstracts/search?q=ECG" title=" ECG"> ECG</a> </p> <a href="https://publications.waset.org/abstracts/157210/a-systematic-review-of-situational-awareness-and-cognitive-load-measurement-in-driving" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/157210.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">119</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2802</span> Boundary Alert System for Powered Wheelchair in Confined Area Training</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Tsoi%20Kim%20Ming">Tsoi Kim Ming</a>, <a href="https://publications.waset.org/abstracts/search?q=Yu%20King%20Pong"> Yu King Pong</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Background: With powered wheelchair, patients can travel more easily and conveniently. However, some patients suffer from other difficulties, such as visual impairment, cognitive disorder, or psychological issues, which make them unable to control powered wheelchair safely. Purpose: Therefore, those patients are required to complete a comprehensive driving training by therapists on confined area, which simulates narrow paths in daily live. During the training, therapists will give series of driving instruction to patients, which may be unaware of patients crossing out the boundary of area. To facilitate the training, it is needed to develop a device to provide warning to patients during training Method: We adopt LIDAR for distance sensing started from center of confined area. Then, we program the LIDAR with linear geometry to remember each side of the area. The LIDAR will sense the location of wheelchair continuously. Once the wheelchair is driven out of the boundary, audio alert will be given to patient. Result: Patients can pay their attention to the particular driving situation followed by audio alert during driving training, which can learn how to avoid out of boundary in similar situation next time. Conclusion: Instead of only instructed by therapist, the LIDAR can facilitate the powered wheelchair training by patients actively pay their attention to driving situation. After training, they are able to control the powered wheelchair safely when facing difficult and narrow path in real life. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=PWC" title="PWC">PWC</a>, <a href="https://publications.waset.org/abstracts/search?q=training" title=" training"> training</a>, <a href="https://publications.waset.org/abstracts/search?q=rehab" title=" rehab"> rehab</a>, <a href="https://publications.waset.org/abstracts/search?q=AT" title=" AT"> AT</a> </p> <a href="https://publications.waset.org/abstracts/159535/boundary-alert-system-for-powered-wheelchair-in-confined-area-training" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/159535.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">105</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2801</span> Gender Differences in the Prediction of Smartphone Use While Driving: Personal and Social Factors </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Erez%20Kita">Erez Kita</a>, <a href="https://publications.waset.org/abstracts/search?q=Gil%20Luria"> Gil Luria</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This study examines gender as a boundary condition for the relationship between the psychological variable of mindfulness and the social variable of income with regards to the use of smartphones by young drivers. The use of smartphones while driving increases the likelihood of a car accident, endangering young drivers and other road users. The study sample included 186 young drivers who were legally permitted to drive without supervision. The subjects were first asked to complete questionnaires on mindfulness and income. Next, their smartphone use while driving was monitored over a one-month period. This study is unique as it used an objective smartphone monitoring application (rather than self-reporting) to count the number of times the young participants actually touched their smartphones while driving. The findings show that gender moderates the effects of social and personal factors (i.e., income and mindfulness) on the use of smartphones while driving. The pattern of moderation was similar for both social and personal factors. For men, mindfulness and income are negatively associated with the use of smartphones while driving. These factors are not related to the use of smartphones by women drivers. Mindfulness and income can be used to identify male populations that are at risk of using smartphones while driving. Interventions that improve mindfulness can be used to reduce the use of smartphones by male drivers. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=mindfulness" title="mindfulness">mindfulness</a>, <a href="https://publications.waset.org/abstracts/search?q=using%20smartphones%20while%20driving" title=" using smartphones while driving"> using smartphones while driving</a>, <a href="https://publications.waset.org/abstracts/search?q=income" title=" income"> income</a>, <a href="https://publications.waset.org/abstracts/search?q=gender" title=" gender"> gender</a>, <a href="https://publications.waset.org/abstracts/search?q=young%20drivers" title=" young drivers"> young drivers</a> </p> <a href="https://publications.waset.org/abstracts/118529/gender-differences-in-the-prediction-of-smartphone-use-while-driving-personal-and-social-factors" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/118529.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">172</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2800</span> Exergy Losses Relation with Driving Forces in Heat Transfer Process</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=S.%20Ali%20Ashrafizadeh">S. Ali Ashrafizadeh</a>, <a href="https://publications.waset.org/abstracts/search?q=M.%20Amidpour"> M. Amidpour</a>, <a href="https://publications.waset.org/abstracts/search?q=N.%20Hedayat"> N. Hedayat </a> </p> <p class="card-text"><strong>Abstract:</strong></p> Driving forces along with transfer coefficient affect on heat transfer rate, on the other hand, with regard to the relation of these forces with irriversibilities they are effective on exergy losses. Therefore, the driving forces can be used as a relation between heat transfer rate, transfer coefficients and exergy losses. In this paper, first, the relation of the exergetic efficiency and resistant forces is obtained, next the relation between exergy efficiency, relative driving force, heat transfer rate and heat resistances is considered. In all cases, results are argued graphically. Finally, a case study inspected by obtained results. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=heat%20transfer" title="heat transfer">heat transfer</a>, <a href="https://publications.waset.org/abstracts/search?q=exergy%20losses" title=" exergy losses"> exergy losses</a>, <a href="https://publications.waset.org/abstracts/search?q=exergetic%20efficiency" title=" exergetic efficiency"> exergetic efficiency</a>, <a href="https://publications.waset.org/abstracts/search?q=driving%20forces" title=" driving forces"> driving forces</a> </p> <a href="https://publications.waset.org/abstracts/30134/exergy-losses-relation-with-driving-forces-in-heat-transfer-process" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/30134.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">606</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2799</span> Eco-Drive Predictive Analytics</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Sharif%20Muddsair">Sharif Muddsair</a>, <a href="https://publications.waset.org/abstracts/search?q=Eisels%20Martin"> Eisels Martin</a>, <a href="https://publications.waset.org/abstracts/search?q=Giesbrecht%20Eugenie"> Giesbrecht Eugenie </a> </p> <p class="card-text"><strong>Abstract:</strong></p> With development of society increase the demand for the movement of people also increases gradually. The various modes of the transport in different extent which expat impacts, which depends on mainly technical-operating conditions. The up-to-date telematics systems provide the transport industry a revolutionary. Appropriate use of these systems can help to substantially improve the efficiency. Vehicle monitoring and fleet tracking are among services used for improving efficiency and effectiveness of utility vehicle. There are many telematics systems which may contribute to eco-driving. Generally, they can be grouped according to their role in driving cycle. • Before driving - eco-route selection, • While driving – Advanced driver assistance, • After driving – remote analysis. Our point of interest is regulated in third point [after driving – remote analysis]. TS [Telematics-system] make it possible to record driving patterns in real time and analysis the data later on, So that driver- classification-specific hints [fast driver, slow driver, aggressive driver…)] are given to imitate eco-friendly driving style. Together with growing number of vehicle and development of information technology, telematics become an ‘active’ research subject in IT and the car industry. Telematics has gone a long way from providing navigation solution/assisting the driver to become an integral part of the vehicle. Today’s telematics ensure safety, comfort and become convenience of the driver. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=internet%20of%20things" title="internet of things">internet of things</a>, <a href="https://publications.waset.org/abstracts/search?q=iot" title=" iot"> iot</a>, <a href="https://publications.waset.org/abstracts/search?q=connected%20vehicle" title=" connected vehicle"> connected vehicle</a>, <a href="https://publications.waset.org/abstracts/search?q=cv" title=" cv"> cv</a>, <a href="https://publications.waset.org/abstracts/search?q=ts" title=" ts"> ts</a>, <a href="https://publications.waset.org/abstracts/search?q=telematics%20services" title=" telematics services"> telematics services</a>, <a href="https://publications.waset.org/abstracts/search?q=ml" title=" ml"> ml</a>, <a href="https://publications.waset.org/abstracts/search?q=machine%20learning" title=" machine learning"> machine learning</a> </p> <a href="https://publications.waset.org/abstracts/31164/eco-drive-predictive-analytics" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/31164.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">306</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2798</span> From Comfort to Safety: Assessing the Influence of Car Seat Design on Driver Reaction and Performance</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Sabariah%20Mohd%20Yusoff">Sabariah Mohd Yusoff</a>, <a href="https://publications.waset.org/abstracts/search?q=Qamaruddin%20Adzeem%20Muhamad%20Murad"> Qamaruddin Adzeem Muhamad Murad</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This study investigates the impact of car seat design on driver response time, addressing a critical gap in understanding how ergonomic features influence both performance and safety. Controlled driving experiments were conducted with fourteen participants (11 male, 3 female) across three locations chosen for their varying traffic conditions to account for differences in driver alertness. Participants interacted with various seat designs while performing driving tasks, and objective metrics such as braking and steering response times were meticulously recorded. Advanced statistical methods, including regression analysis and t-tests, were employed to identify design factors that significantly affect driver response times. Subjective feedback was gathered through detailed questionnaires—focused on driving experience and knowledge of response time—and in-depth interviews. This qualitative data was analyzed thematically to provide insights into driver comfort and usability preferences. The study aims to identify key seat design features that impact driver response time and to gain a deeper understanding of driver preferences for comfort and usability. The findings are expected to inform evidence-based guidelines for optimizing car seat design, ultimately enhancing driver performance and safety. The research offers valuable implications for automotive manufacturers and designers, contributing to the development of seats that improve driver response time and overall driving safety. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=car%20seat%20design" title="car seat design">car seat design</a>, <a href="https://publications.waset.org/abstracts/search?q=driver%20response%20time" title=" driver response time"> driver response time</a>, <a href="https://publications.waset.org/abstracts/search?q=cognitive%20driving" title=" cognitive driving"> cognitive driving</a>, <a href="https://publications.waset.org/abstracts/search?q=ergonomics%20optimization" title=" ergonomics optimization"> ergonomics optimization</a> </p> <a href="https://publications.waset.org/abstracts/190738/from-comfort-to-safety-assessing-the-influence-of-car-seat-design-on-driver-reaction-and-performance" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/190738.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">24</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2797</span> The Effects of Using Telephone and Social Media Applications While Driving in Kuwait</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Bashaiar%20Alsanaa">Bashaiar Alsanaa</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Social media have totally converged with social life all around the globe. Using social media applications and mobile phones have become somewhat of an addiction to most people. Driving while using mobile applications falls under such addiction when usage is not of urgency. This study aims to investigate the impact of using such applications while driving in the small rich state of Kuwait, where most people juggle more than one phone for different purposes. Positive and negative effects will be explored in detail as well as causes for these effects and possible reasons. A full range of recommendations will be presented so as to give other countries a specific case study upon which to build solutions and remedies to this emerging and dangerous social phenomenon. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=social%20media" title="social media">social media</a>, <a href="https://publications.waset.org/abstracts/search?q=driving" title=" driving"> driving</a>, <a href="https://publications.waset.org/abstracts/search?q=mobile%20applications" title=" mobile applications"> mobile applications</a>, <a href="https://publications.waset.org/abstracts/search?q=communication" title=" communication"> communication</a> </p> <a href="https://publications.waset.org/abstracts/50264/the-effects-of-using-telephone-and-social-media-applications-while-driving-in-kuwait" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/50264.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">362</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2796</span> Optimal Driving Strategies for a Hybrid Street Type Motorcycle: Modelling and Control</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Jhon%20Vargas">Jhon Vargas</a>, <a href="https://publications.waset.org/abstracts/search?q=Gilberto%20Osorio-Gomez"> Gilberto Osorio-Gomez</a>, <a href="https://publications.waset.org/abstracts/search?q=Tatiana%20Manrique"> Tatiana Manrique</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This work presents an optimal driving strategy proposal for a 125 c.c. street-type hybrid electric motorcycle with a parallel configuration. The results presented in this article are complementary regarding the control proposal of a hybrid motorcycle. In order to carry out such developments, a representative dynamic model of the motorcycle is used, in which also are described different optimization functionalities for predetermined driving modes. The purpose is to implement an off-line optimal driving strategy which distributes energy to both engines by minimizing an objective torque requirement function. An optimal dynamic contribution is found from the optimization routine, and the optimal percentage contribution for vehicle cruise speed is implemented in the proposed online PID controller. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=dynamic%20model" title="dynamic model">dynamic model</a>, <a href="https://publications.waset.org/abstracts/search?q=driving%20strategies" title=" driving strategies"> driving strategies</a>, <a href="https://publications.waset.org/abstracts/search?q=parallel%20hybrid%20motorcycle" title=" parallel hybrid motorcycle"> parallel hybrid motorcycle</a>, <a href="https://publications.waset.org/abstracts/search?q=PID%20controller" title=" PID controller"> PID controller</a>, <a href="https://publications.waset.org/abstracts/search?q=optimization" title=" optimization"> optimization</a> </p> <a href="https://publications.waset.org/abstracts/133692/optimal-driving-strategies-for-a-hybrid-street-type-motorcycle-modelling-and-control" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/133692.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">189</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2795</span> Social Media Effects on Driving: An Exploratory Study Applied to Drivers in Kuwait </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Bashaiar%20Alsanaa">Bashaiar Alsanaa</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Social media have totally converged with social life all around the globe. Using social media applications and mobile phones have become somewhat of an addiction to most people. Driving while using mobile applications falls under such addiction when usage is not of urgency. This study aims to investigate the impact of using such applications while driving in the small, rich state of Kuwait, where most people juggle more than one phone for different purposes. Positive and negative effects will be explored in detail as well as causes for these effects and possible reasons. A full range of recommendations will be presented so as to give other countries a specific case study upon which to build solutions and remedies to this emerging and dangerous social phenomenon. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=communications" title="communications">communications</a>, <a href="https://publications.waset.org/abstracts/search?q=driving" title=" driving"> driving</a>, <a href="https://publications.waset.org/abstracts/search?q=mobile" title=" mobile"> mobile</a>, <a href="https://publications.waset.org/abstracts/search?q=social%20media" title=" social media"> social media</a> </p> <a href="https://publications.waset.org/abstracts/52571/social-media-effects-on-driving-an-exploratory-study-applied-to-drivers-in-kuwait" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/52571.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">334</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2794</span> Research on Morning Commuting Behavior under Autonomous Vehicle Environment Based on Activity Method</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Qing%20Dai">Qing Dai</a>, <a href="https://publications.waset.org/abstracts/search?q=Zhengkui%20Lin"> Zhengkui Lin</a>, <a href="https://publications.waset.org/abstracts/search?q=Jiajia%20Zhang"> Jiajia Zhang</a>, <a href="https://publications.waset.org/abstracts/search?q=Yi%20Qu"> Yi Qu</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Based on activity method, this paper focuses on morning commuting behavior when commuters travel with autonomous vehicles (AVs). Firstly, a net utility function of commuters is constructed by the activity utility of commuters at home, in car and at workplace, and the disutility of travel time cost and that of schedule delay cost. Then, this net utility function is applied to build an equilibrium model. Finally, under the assumption of constant marginal activity utility, the properties of equilibrium are analyzed. The results show that, in autonomous driving, the starting and ending time of morning peak and the number of commuters who arrive early and late at workplace are the same as those in manual driving. In automatic driving, however, the departure rate of arriving early at workplace is higher than that of manual driving, while the departure rate of arriving late is just the opposite. In addition, compared with manual driving, the departure time of arriving at workplace on time is earlier and the number of people queuing at the bottleneck is larger in automatic driving. However, the net utility of commuters and the total net utility of system in automatic driving are greater than those in manual driving. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=autonomous%20cars" title="autonomous cars">autonomous cars</a>, <a href="https://publications.waset.org/abstracts/search?q=bottleneck%20model" title=" bottleneck model"> bottleneck model</a>, <a href="https://publications.waset.org/abstracts/search?q=activity%20utility" title=" activity utility"> activity utility</a>, <a href="https://publications.waset.org/abstracts/search?q=user%20equilibrium" title=" user equilibrium"> user equilibrium</a> </p> <a href="https://publications.waset.org/abstracts/128666/research-on-morning-commuting-behavior-under-autonomous-vehicle-environment-based-on-activity-method" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/128666.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">111</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2793</span> A Conceptual Model of the 'Driver – Highly Automated Vehicle' System</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=V.%20A.%20Dubovsky">V. A. Dubovsky</a>, <a href="https://publications.waset.org/abstracts/search?q=V.%20V.%20Savchenko"> V. V. Savchenko</a>, <a href="https://publications.waset.org/abstracts/search?q=A.%20A.%20Baryskevich"> A. A. Baryskevich</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The current trend in the automotive industry towards automatic vehicles is creating new challenges related to human factors. This occurs due to the fact that the driver is increasingly relieved of the need to be constantly involved in driving the vehicle, which can negatively impact his/her situation awareness when manual control is required, and decrease driving skills and abilities. These new problems need to be studied in order to provide road safety during the transition towards self-driving vehicles. For this purpose, it is important to develop an appropriate conceptual model of the interaction between the driver and the automated vehicle, which could serve as a theoretical basis for the development of mathematical and simulation models to explore different aspects of driver behaviour in different road situations. Well-known driver behaviour models describe the impact of different stages of the driver's cognitive process on driving performance but do not describe how the driver controls and adjusts his actions. A more complete description of the driver's cognitive process, including the evaluation of the results of his/her actions, will make it possible to more accurately model various aspects of the human factor in different road situations. This paper presents a conceptual model of the 'driver – highly automated vehicle' system based on the P.K. Anokhin's theory of functional systems, which is a theoretical framework for describing internal processes in purposeful living systems based on such notions as goal, desired and actual results of the purposeful activity. A central feature of the proposed model is a dynamic coupling mechanism between the decision-making of a driver to perform a particular action and changes of road conditions due to driver’s actions. This mechanism is based on the stage by stage evaluation of the deviations of the actual values of the driver’s action results parameters from the expected values. The overall functional structure of the highly automated vehicle in the proposed model includes a driver/vehicle/environment state analyzer to coordinate the interaction between driver and vehicle. The proposed conceptual model can be used as a framework to investigate different aspects of human factors in transitions between automated and manual driving for future improvements in driving safety, and for understanding how driver-vehicle interface must be designed for comfort and safety. A major finding of this study is the demonstration that the theory of functional systems is promising and has the potential to describe the interaction of the driver with the vehicle and the environment. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=automated%20vehicle" title="automated vehicle">automated vehicle</a>, <a href="https://publications.waset.org/abstracts/search?q=driver%20behavior" title=" driver behavior"> driver behavior</a>, <a href="https://publications.waset.org/abstracts/search?q=human%20factors" title=" human factors"> human factors</a>, <a href="https://publications.waset.org/abstracts/search?q=human-machine%20system" title=" human-machine system"> human-machine system</a> </p> <a href="https://publications.waset.org/abstracts/123623/a-conceptual-model-of-the-driver-highly-automated-vehicle-system" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/123623.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">146</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2792</span> Optimal Trajectories for Highly Automated Driving</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Christian%20Rathgeber">Christian Rathgeber</a>, <a href="https://publications.waset.org/abstracts/search?q=Franz%20Winkler"> Franz Winkler</a>, <a href="https://publications.waset.org/abstracts/search?q=Xiaoyu%20Kang"> Xiaoyu Kang</a>, <a href="https://publications.waset.org/abstracts/search?q=Steffen%20M%C3%BCller"> Steffen Müller</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this contribution two approaches for calculating optimal trajectories for highly automated vehicles are presented and compared. The first one is based on a non-linear vehicle model, used for evaluation. The second one is based on a simplified model and can be implemented on a current ECU. In usual driving situations both approaches show very similar results. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=trajectory%20planning" title="trajectory planning">trajectory planning</a>, <a href="https://publications.waset.org/abstracts/search?q=direct%20method" title=" direct method"> direct method</a>, <a href="https://publications.waset.org/abstracts/search?q=indirect%20method" title=" indirect method"> indirect method</a>, <a href="https://publications.waset.org/abstracts/search?q=highly%20automated%20driving" title=" highly automated driving"> highly automated driving</a> </p> <a href="https://publications.waset.org/abstracts/22622/optimal-trajectories-for-highly-automated-driving" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/22622.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">533</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2791</span> Improvement of Brige Weigh-In-Motion Technique Considering the Driving Conditions of Vehicles</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Changgil%20Lee">Changgil Lee</a>, <a href="https://publications.waset.org/abstracts/search?q=Jooyoung%20Park"> Jooyoung Park</a>, <a href="https://publications.waset.org/abstracts/search?q=Seunghee%20Park"> Seunghee Park</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this study, bridge weigh-in-motion (BWIM) system was simulated under various driving conditions of vehicles to improve the performance of the BWIM system. Two driving conditions were considered. One was the number of the axle of the vehicles. Since the vehicles have different number of axle according to the types of the vehicle, the vehicles were modeled considering the number of the axle. The other was the speed of the vehicles because the speed of the vehicles is not consistent on the bridge. To achieve the goal, the dynamic characteristics of a bridge such as modal parameters were considered in numerical simulation by analyzing precision models. Also, the driving vehicles were modeled as mass-spring-damping systems reflecting the axle information. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=bridge%20weigh-in-motion%20%28BWIM%29%20system" title="bridge weigh-in-motion (BWIM) system">bridge weigh-in-motion (BWIM) system</a>, <a href="https://publications.waset.org/abstracts/search?q=driving%20conditions" title=" driving conditions"> driving conditions</a>, <a href="https://publications.waset.org/abstracts/search?q=precision%20analysis%20model" title=" precision analysis model"> precision analysis model</a>, <a href="https://publications.waset.org/abstracts/search?q=the%20number%20of%20axle" title=" the number of axle"> the number of axle</a>, <a href="https://publications.waset.org/abstracts/search?q=the%20speed%20of%20vehicle" title=" the speed of vehicle"> the speed of vehicle</a> </p> <a href="https://publications.waset.org/abstracts/57266/improvement-of-brige-weigh-in-motion-technique-considering-the-driving-conditions-of-vehicles" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/57266.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">469</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2790</span> Simulation Research of City Bus Fuel Consumption during the CUEDC Australian Driving Cycle</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=P.%20Kacejko">P. Kacejko</a>, <a href="https://publications.waset.org/abstracts/search?q=M.%20Wendeker"> M. Wendeker</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The fuel consumption of city buses depends on a number of factors that characterize the technical properties of the bus and driver, as well as traffic conditions. This parameter related to greenhouse gas emissions is regulated by law in many countries. This applies to both fuel consumption and exhaust emissions. Simulation studies are a way to reduce the costs of optimization studies. The paper describes simulation research of fuel consumption city bus driving. Parameters of the developed model are based on experimental results obtained on chassis dynamometer test stand and road tests. The object of the study was a city bus equipped with a compression-ignition engine. The verified model was applied to simulate the behavior of a bus during the CUEDC Australian Driving Cycle. The results of the calculations showed a direct influence of driving dynamics on fuel consumption. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Australian%20Driving%20Cycle" title="Australian Driving Cycle">Australian Driving Cycle</a>, <a href="https://publications.waset.org/abstracts/search?q=city%20bus" title=" city bus"> city bus</a>, <a href="https://publications.waset.org/abstracts/search?q=diesel%20engine" title=" diesel engine"> diesel engine</a>, <a href="https://publications.waset.org/abstracts/search?q=fuel%20consumption" title=" fuel consumption"> fuel consumption</a> </p> <a href="https://publications.waset.org/abstracts/106701/simulation-research-of-city-bus-fuel-consumption-during-the-cuedc-australian-driving-cycle" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/106701.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">122</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2789</span> Effects of Low Sleep Efficiency and Sleep Deprivation on Driver Physical Fatigue</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Chen-Yu%20%20Tsai">Chen-Yu Tsai</a>, <a href="https://publications.waset.org/abstracts/search?q=Wen-Te%20%20Liu"> Wen-Te Liu</a>, <a href="https://publications.waset.org/abstracts/search?q=Chen-Chen%20%20Lo"> Chen-Chen Lo</a>, <a href="https://publications.waset.org/abstracts/search?q=Kang%20%20Lo"> Kang Lo</a>, <a href="https://publications.waset.org/abstracts/search?q=Yin-Tzu%20%20Lin"> Yin-Tzu Lin</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Background: Driving drowsiness related to insufficient or disordered sleep accounts for a major percentage of vehicular accidents. Sleep deprivation is the primary reason related to low sleep efficiency. Nevertheless, the mechanism of sleep deprivation induces driving fatigue to remain unclear. Objective: The objective of this study is to associate the relationship between insufficient sleep efficiency and driving fatigue. Methodologies: The physical condition while driving was obtained from the questionnaires to classify the state of driving fatigue. Sleep efficiency was quantified as the polysomnography (PSG), and the sleep stages were sentenced by the reregistered Technologist during examination in a hospital in New Taipei City (Taiwan). The independent T-test was used to investigate the correlation between sleep efficiency, sleep stages ratio, and driving drowsiness. Results: There were 880 subjects recruited in this study, who had been done polysomnography for evaluating severity for obstructive sleep apnea syndrome (OSAS) as well as completed the driver condition questionnaire. Four-hundred-eighty-four subjects (55%) were classified as fatigue group, and 396 subjects (45%) were served as the control group. The ratio of stage three sleep (N3) (0.032 ± 0.056) in fatigue group were significantly lower than the control group (p < 0.01). The significantly higher value of snoring index (242.14 ± 205.51 /hours) was observed in the fatigue group (p < 0.01). Conclusion: We observe the considerable correlation between deep sleep reduce and driving drowsiness. To avoid drowsy driving, the sleep deprivation, and the snoring events during the sleeping time should be monitored and alleviated. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=driving%20drowsiness" title="driving drowsiness">driving drowsiness</a>, <a href="https://publications.waset.org/abstracts/search?q=sleep%20deprivation" title=" sleep deprivation"> sleep deprivation</a>, <a href="https://publications.waset.org/abstracts/search?q=stage%20three%20sleep" title=" stage three sleep"> stage three sleep</a>, <a href="https://publications.waset.org/abstracts/search?q=snoring%20index" title=" snoring index"> snoring index</a> </p> <a href="https://publications.waset.org/abstracts/110120/effects-of-low-sleep-efficiency-and-sleep-deprivation-on-driver-physical-fatigue" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/110120.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">146</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2788</span> Risky Driving Behavior among Bus Driver in Jakarta</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Ratri%20A.%20Benedictus">Ratri A. Benedictus</a>, <a href="https://publications.waset.org/abstracts/search?q=Felicia%20M.%20Yolanda"> Felicia M. Yolanda</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Public transport is a crucial issue for capital city in developing country, such as Jakarta. Inadequate number and low quality of public transport services resulting personal vehicles as the main option. As a result, traffic jams are getting worse in Jakarta. The low quality of public transport, particularly buses, compounded by the risk behavior of the driver. Traffic accidents involving public bus in Jakarta were often the case, even result in fatality. The purpose of this study is to get a description of risk behavior among the public bus drivers in Jakarta. 132 bus drivers become respondent of this study. Risky Driving Behavior scale of Dorn were used. Data were analyzed using descriptive statistics. 51.5% of respondents felt often showing risky behavior while on driving. The highest type of risky driving behavior is still using the unsafe bus (62%). Followed by trespass the bus line (30%), over speed (21%), violate the road signs (15%) and driving with unhealthy physical condition (4%). Results of this study suggested that high understanding of the bus drivers on their risk behaviors have not lead to the emergence of safe driving behavior. Therefore, together with technical engineering and instrumentation work intervention over this issue, psychological aspects also need to be considered, such as: risk perception, safety attitude,safety culture, locus of control and Fatalism. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=bus%20driver" title="bus driver">bus driver</a>, <a href="https://publications.waset.org/abstracts/search?q=psychological%20factors" title=" psychological factors"> psychological factors</a>, <a href="https://publications.waset.org/abstracts/search?q=public%20transportation" title=" public transportation"> public transportation</a>, <a href="https://publications.waset.org/abstracts/search?q=risky%20driving%20behavior" title=" risky driving behavior"> risky driving behavior</a> </p> <a href="https://publications.waset.org/abstracts/41503/risky-driving-behavior-among-bus-driver-in-jakarta" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/41503.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">360</span> </span> </div> </div> <ul class="pagination"> <li class="page-item disabled"><span class="page-link">&lsaquo;</span></li> <li class="page-item active"><span class="page-link">1</span></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=cognitive%20driving&page=2">2</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=cognitive%20driving&page=3">3</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=cognitive%20driving&page=4">4</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=cognitive%20driving&page=5">5</a></li> <li class="page-item"><a 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