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Dissertations / Theses on the topic 'Driver behavior'
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Ogle, Jennifer Harper. "Quantitative assessment of driver speeding behavior using instrumented vehicles." Diss., Georgia Institute of Technology, 2005. http://etd.gatech.edu/theses/available/etd-04182005-034536/unrestricted/ogle%5Fjennifer%5Fh%5F200505%5Fphd.pdf.
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Thesis (Ph. D.)--Civil and Environmental Engineering, Georgia Institute of Technology, 2005.Includes bibliographical references (p. 310-316). Also available online via the Georgia Institute of Technology, website (http://etd.gatech.edu/).
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Graves, Mark. "Avoidance Behavior in the Elderly Driver." TopSCHOLAR®, 1996. http://digitalcommons.wku.edu/theses/873.
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Do older drivers modify their driving habits in response to functional impairment? Older drivers who avoid challenging driving situations were compared with non-avoiders, to determine whether functional limitations were related to avoidance and whether avoidance is related to reducing crash risk. Results showed that, on the average, older drivers reported avoiding driving at night, on high traffic roads, on high speed roads, and in rush hour traffic while not avoiding left turns, driving in the rain, and driving alone. Subjects were placed into groups based on their cognitive and visual abilities. It was found that older drivers with an impaired UFOV and either 0, 1-2, or 3-4 vision problems reported avoiding significantly more than those with unimpaired cognition and vision. The number of at-fault crashes incurred in the 5 years prior to 1990 was positively related to driving avoidance (those who reported avoidance had a history of more crashes than those who did not report avoidance). However, the number of crashes incurred in the 3 years subsequent to 1990 was negatively related to avoidance (those who reported avoidance in 1990 had fewer crashes in future years than those who did not report avoidance). These results imply that older drivers modify their driving in response to crash involvement and/or functional limitations and that this "self-regulation" may reduce future crash risk.
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Miyajima, Chiyomi, Yoshihiro Nishiwaki, Koji Ozawa, Toshihiro Wakita, Katsunobu Itou, Kazuya Takeda, and Fumitada Itakura. "Driver Modeling Based on Driving Behavior and Its Evaluation in Driver Identification." IEEE, 2007. http://hdl.handle.net/2237/9623.
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Hamdar, Samer Hani. "Towards modeling driver behavior under extreme conditions." College Park, Md. : University of Maryland, 2004. http://hdl.handle.net/1903/2141.
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Thesis (M.S.)--University of Maryland, College Park, 2004.Includes vita. Includes bibliographical references (p. 118-123). Also available online via the Digital Repository at the University of Maryland (https://drum.umd.edu/dspace/).
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Garcia, Ortiz Michael [Verfasser]. "Prediction of driver behavior / Michael Garcia Ortiz." Bielefeld : Universitätsbibliothek Bielefeld, 2014. http://d-nb.info/1049523555/34.
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Parwathaneni, Rajiv. "Effect of Roadside Vegetation on Driver Behavior." Cleveland State University / OhioLINK, 2016. http://rave.ohiolink.edu/etdc/view?acc_num=csu1481555419869409.
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Amer, Ahmed. "Statistical and Behavioral Modeling of Driver Behavior on Signalized Intersection Approaches." Diss., Virginia Tech, 2010. http://hdl.handle.net/10919/77995.
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The onset of a yellow indication is typically associated with the risk of vehicle crashes resulting from dilemma-zone and red-light-running problems. Such risk of vehicle crashes is greater for high-speed signalized intersection approaches. The research presented in this dissertation develops statistical as well as behavioral frameworks for modeling driver behavior while approaching high-speed signalized intersection approaches at the onset of a yellow indication. The analysis in this dissertation utilizes two sources of data. The main source is a new dataset that was collected as part of this research effort during the summer of 2008. This experiment includes two instructed speeds; 72.4 km/h (45 mph) with 1727 approaching trials (687 running and 1040 stopping), and 88.5 km/h (55 mph) with 1727 approaching trials (625 running and 1102 stopping). The complementary source is an existing dataset that was collected earlier in the spring of 2005 on the Virginia Smart Road facility. This dataset includes a total of 1186 yellow approaching trials (441 running and 745 stopping).
The adopted analysis approach comprises four major parts that fulfill the objectives of this dissertation. The first part is concerned with the characterization of different driver behavioral attributes, including driver yellow/red light running behavior, driver stop-run decisions, driver perception-reaction times (PRT), and driver deceleration levels. The characterization of these attributes involves analysis of variance (ANOVA) and frequency distribution analyses, as well as the calibration of statistical models. The second part of the dissertation introduces a novel approach for computing the clearance interval duration that explicitly accounts for the reliability of the design (probability that drivers do not encounter a dilemma zone). Lookup tables are developed to assist practitioners in the design of yellow timings that reflects the stochastic nature of driver PRT and deceleration levels. An extension of the proposed approach is presented that can be integrated with the IntelliDriveSM initiative.
Furthermore, the third part of the dissertation develops an agent-based Bayesian statistics approach to capture the stochastic nature of the driver stop-run decision. The Bayesian model parameters are calibrated using the Markov Chain Monte Carlo (MCMC) slice procedure implemented within the MATLAB® software. In addition, two procedures for the Bayesian model application are illustrated; namely Cascaded regression and Cholesky decomposition. Both procedures are demonstrated to produce replications that are consistent with the Bayesian model realizations, and capture the parameter correlations without the need to store the set of parameter realizations. The proposed Bayesian approach is ideal for modeling multi-agent systems in which each agent has its own unique set of parameters. Finally, the fourth part of the dissertation introduces and validates a state-of-the-art behavioral modeling framework that can be used as a tool to simulate driver behavior after the onset of a yellow indication until he/she reaches the intersection stop line. The behavioral model is able to track dilemma zone drivers and update the information available to them every time step until they reach a final decision. It is anticipated that this behavioral model will be implemented in microscopic traffic simulation software to enhance the modeling of driver behavior as they approach signalized intersections.Ph. D.
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Xu, Feng. "Driver behavior and gap acceptance studies at roundabouts." abstract and full text PDF (free order & download UNR users only), 2007. http://0-gateway.proquest.com.innopac.library.unr.edu/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqdiss&rft_dat=xri:pqdiss:1442865.
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Vogel, Katja. "Modeling driver behavior : a control theory based approach /." Linköping : Univ, 2002. http://www.bibl.liu.se/liupubl/disp/disp2002/tek751s.pdf.
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Lwambagaza, Lina. "Modeling Older Driver Behavior on Freeway Merging Ramps." UNF Digital Commons, 2016. http://digitalcommons.unf.edu/etd/646.
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Merging from on-ramps to mainline traffic is one of the most challenging driving maneuvers on freeways. The challenges are further heightened for older drivers, as they are known to have longer perception-reaction times, larger acceptance gaps, and slower acceleration rates. In this research, VISSIM, a microscopic traffic simulation software, was used to evaluate the influence of the aging drivers on the operations of a typical diamond interchange. First, drivers were recorded on video cameras as they negotiated joining the mainline traffic from an on-ramp acceleration lane at two sites along I-75 in Southwest Florida. Several measures of effectiveness were collected including speeds, gaps, and location of entry to the mainline lanes. This information was used as either model input or for verification purposes. Two VISSIM models were developed for each site – one for the existing conditions and verification, and another for a sensitivity analysis, varying the percentage of older drivers and Level of Service (from A to E), to determine their influence on ramp operational characteristics. According to the results, there was a significant difference in driving behavior between older, middle-aged, and younger drivers, based on the measures of effectiveness analyzed in this study. Additionally, as the level of service and percentage of older adult motorists increased, longer queues were observed with slower speeds on the acceleration lanes and the right-most travel lane of the mainline traffic.
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Gadepally, Vijay Narasimha. "Estimation of Driver Behavior for Autonomous Vehicle Applications." The Ohio State University, 2013. http://rave.ohiolink.edu/etdc/view?acc_num=osu1365952195.
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Kircher, Katja. "Modeling driver behavior : a control theory based approach /." Linköping : Univ, 2002. http://www.bibl.liu.se/liupubl/disp/disp2002/tek751s.pdf.
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Haroun, Antoine. "Observed minimum headways as an index of driver behavior." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1997. http://www.collectionscanada.ca/obj/s4/f2/dsk2/ftp01/MQ29391.pdf.
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Chong, Linsen. "Modeling Naturalistic Driver Behavior in Traffic Using Machine Learning." Thesis, Virginia Tech, 2011. http://hdl.handle.net/10919/76834.
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This research is focused on driver behavior in traffic, especially during car-following situations and safety critical events. Driving behavior is considered as a human decision process in this research which provides opportunities for an artificial driver agent simulator to learn according to naturalistic driving data. This thesis presents two mechine learning methodologies that can be applied to simulate driver naturalistic driving behavior including risk-taking behavior during an incident and lateral evasive behavior which have not yet been captured in existing literature. Two special machine learning approaches Backpropagation (BP) neural network and Neuro-Fuzzy Actor Critic Reinforcement Learning (NFACRL) are proposed to model driver behavior during car-following situation and safety critical events separately. In addition to that, as part of the research, state-of-the-art car-following models are also analyzed and compared to BP neural network approach. Also, driver heterogeneity analyzed by NFACRL method is discussed. Finally, it presents the findings and limitations drawn from each of the specific issues, along with recommendations for further research.Master of Science
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Zubritsky, Adam David. "Fatal Crashes Caused by Light Trucks Relative to Cars: A Test of the Offsetting Behavior Hypothesis." Master's thesis, University of Central Florida, 2005. http://digital.library.ucf.edu/cdm/ref/collection/ETD/id/3098.
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This thesis presents an econometric test of the offsetting behavior hypothesis concerning drivers of light trucks relative to cars. The main objective is to determine whether drivers of light trucks offset perceived safety benefits associated with larger vehicles by driving more aggressively than drivers of cars, subsequently causing more fatal crashes, holding all else constant. An empirical model using data on pedestrian fatalities across the United States over a five-year period is developed and analyzed in order to capture the desired results. Estimates provide substantial evidence in support of the offsetting behavior hypothesis. To strengthen the case for driver offsetting behavior beyond previous studies, the model is estimated again using pedalcyclist fatalities. The results also point to interesting conclusions regarding the effects of increased speed limits on the behavior of drivers.M.A.A.E.
Department of Economics
Business Administration
Applied Economics
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Wright, Priscilla. "Communication Training and Nonemergency Transportation Driver Perception of Challenging Behavior." ScholarWorks, 2017. https://scholarworks.waldenu.edu/dissertations/4115.
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Nonemergency transportation drivers play a critical role in helping individuals with Intellectual Disabilities (ID) gain access to community integration opportunities. Challenging behaviors can limit access to enrichment opportunities and possibly increase the likelihood that individuals with ID will be isolated from community enrichment activities. The purpose of this study was to determine if positive behavior support training improved nonemergency transportation drivers' perceptions of challenging behaviors displayed by individuals with ID. For purposes of this study, perception was defined as staff (driver) beliefs about the causes of challenging behavior. A convenience sample of 52 nonemergency transportation drivers was chosen from a Logisticare provider list using local zip codes. Data were collected using the Challenging Behavior Attribution Scale (CHABA) before and after training using the Positive Behavior Support Curriculum 2nd Edition. A 2-way ANOVA revealed no statistically significant differences in perception before or after training. Analysis of the data indicated that training had no impact on driver perception of challenging behavior. The drivers who participated in this study appeared to have positive perceptions of challenging behavior, and, as a result, no statistically significant results were found. Perhaps the results of this study might lead community organizations that support individuals with ID to include transportation drivers in team meetings when there are concerns regarding challenging behavior. The drivers' positive perceptions regarding challenging behaviors may be an asset to support teams in developing positive behavior support strategies that improve the quantity of life for persons with ID.
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Truong, Y.-Thao. "Observation and analysis of driver behavior at intersections in malfunction flash mode." Thesis, Atlanta, Ga. : Georgia Institute of Technology, 2008. http://hdl.handle.net/1853/26561.
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Thesis (M. S.)--Civil and Environmental Engineering, Georgia Institute of Technology, 2009.Committee Chair: Hunter, Michael; Committee Member: Meyer, Michael; Committee Member: Rodgers, Michael. Part of the SMARTech Electronic Thesis and Dissertation Collection.
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Karlsson, Rikard. "Evaluating driver distraction countermeasures." Thesis, Linköping University, Department of Computer and Information Science, 2004. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-2456.
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Statistics showing that in-vehicle driver distraction is a major contributing cause in road accidents is presented. Driver distraction is defined building on the driving theory by Gibson and Crooks. The idea to use driver distraction countermeasures as a way of mitigating the effects of the driver distraction problem is then introduced. A requirement list is formulated with ten requirements that distraction countermeasures should meet. A simplification of regarding distraction as a gaze direction problem makes way for designing an experiment to evaluate two driver distraction countermeasures in which new eye- tracking technology plays a key role. The experiment also makes use of a simulator, a surrogate in-vehicle information system as a distractor, and thirty subjects. The most important dependent measures were in-vehicle glance time and a steering wheel reaction time measure. The evaluated countermeasures – a blue flash at middle of the road position and a kinesthetic brake pulse – could, however, not be shown to meet the most important of the requirements formulated. The lack of effect of the countermeasures in the experiment may either depend on their actual inefficiency or on methodological shortcomings of the experiment. These alternatives are discussed. It is speculated that the biggest problems with the possible lack of actual efficiency have to do with that the theoretical basis for using a flash did not transfer to the driving setting, and that the brake pulse used was too weak. The methodological problems have to do with the non-validated dependent measures used, missing data, nuisance warnings, insufficient distractors, non-precise hypotheses, and difficulties with separating the effect of the countermeasures from the psychological force to look on the road.
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Ferguson, Catherine A. "An exploration of the relationship between attitudes and behavior in young drivers : an application of the theory of planned behavior." Thesis, Edith Cowan University, Research Online, Perth, Western Australia, 2008. https://ro.ecu.edu.au/theses/227.
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Young drivers are over represented in traffic crashes throughout the world and despite considerable efforts to date, there is still considerable work to be undertaken to develop interventions that will aid in the reduction of this road trauma. Historically, road safety research has been more focused on evaluative research rather than the application of theory and this has effects on the success of interventions. This research used a well supported social psychological theory (Theory of Planned Behavior [TPB]) to investigate the relationship between attitudes and behavior in young drivers with a view to determining if there was an opportunity to move towards acceptable and appropriate interventions to reduce young drivers' involvement in traffic crashes.
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Konduru, Karun K. "Long run changes in driver behavior due to variable tolls." Texas A&M University, 2003. http://hdl.handle.net/1969.1/293.
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As many variable pricing projects are still in the implementation stage, long-run driver responses to the variable tolls are largely unknown. This research examined the long-run changes in driver behavior in an existing variable pricing project in Lee County, Florida. Using empirical evidence, it was found that over time the price elasticities of demand on the Lee County toll bridges have decreased from -0.42 to -
0.11 (Midpoint Memorial Bridge) and from -0.31 to -0.06 (Cape Coral Bridge) during the early morning discount period. The elasticities have decreased, but to a lesser extent, during the late morning and early afternoon discount periods. A discount period volume spreading ratio was also developed to analyze these changes. The results from this analysis confirmed the elasticity results. In addition to the empirical analysis of travel patterns discussed above, a telephone survey of drivers was conducted. The survey results indicated that certain driver characteristics such as higher frequency of trips, commute trip purpose, full-time employment status, more people in the household, higher education, and age between 25-34 years, were all indicators that the participant may increase his or her variable pricing usage over time. Other characteristics, including being retired and having a household income less than $16,000, were indicators that the driver may not increase variable pricing participation. Binary logit and semiparametric models were also developed to examine socio-economic and commute characteristics that may influence a driver increasing his or her participation in a variable pricing program. The results from these two variable toll bridges in Lee County indicated a decrease in variable toll price elasticity over time. However, these results may not be typical for variable pricing projects. Factors such as alternative routes, different traveler demographics, traffic congestion levels, and size of the toll discount may influence the results obtained from other variable pricing projects. However, the methodology developed in this research can be applied to other projects in order to determine those toll price elasticities of demand.
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Durkee, Shaun Michael. "The effect of simulation attributes on driver perception and behavior." Thesis, Montana State University, 2010. http://etd.lib.montana.edu/etd/2010/durkee/DurkeeS0810.pdf.
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Transportation systems in today's world are complex, diverse, and dangerous. Drivers execute many tasks in order to safely and efficiently maneuver their vehicles in these systems. Evaluation of vehicle speed (ego motion) and inter-vehicle distance (egocentric distance) are crucial skills and constant demands while operating a motor vehicle. Common maneuvers such as braking, obstacle avoidance, and overtaking rely heavily on such skills. Driving skills and transportation safety concerns in general have been studied over the years by many research methodologies. One such methodology, the driving simulator, has emerged as a leading research tool to help understand driver behavior and mitigate traffic safety concerns. The overall effectiveness of driving simulation as a research tool is linked to how accurately modern technology can model reality. Therefore determining how valid simulators are in representing reality is a chief concern among researchers, as validity ensures accuracy and credibility of research efforts. Simulation validity is established both physically and behaviorally. The objective of this project was to conduct a driving simulator experiment to examine the perceptual and behavioral effects of various parameters of the simulation deemed relevant from theories of ego motion. Twenty drivers completed speed and following distance perception tasks (absolute production, fixed-increase production, and ratio production) while driving through rural road scenarios that varied in the presentation of motion, field of view, and optic flow. Tasks and dependent variables assessed driver perception of speeds (25-65 MPH) and following distances (150-300 ft) common in everyday driving. The study concluded that field of view (FOV) and optic flow simulation parameters were significant to the perception of absolute speed, with high levels of each parameter (large FOV, high optic flow) resulting in more accurate perception than low levels (small FOV, low optic flow). Also, participants perceived a high level of field of view as significantly more natural than a low level of field of view. The results of this study will add to the existing simulator body of knowledge and will also allow the researchers to quantify the relative importance of simulation parameters as a basis for future behavioral validation of the driving simulator.
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Every, Joshua Lee. "Development of a Driver Behavior Based Active Collision Avoidance System." The Ohio State University, 2015. http://rave.ohiolink.edu/etdc/view?acc_num=osu1429800895.
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Edwards, Michelle. "Evaluation of traveler information on driver behavior in southeast Wyoming." Laramie, Wyo. : University of Wyoming, 2008. http://proquest.umi.com/pqdweb?did=1799711391&sid=1&Fmt=2&clientId=18949&RQT=309&VName=PQD.
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Yekhshatyan, Lora. "Detecting distraction and degraded driver performance with visual behavior metrics." Diss., University of Iowa, 2010. https://ir.uiowa.edu/etd/910.
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Driver distraction contributes to approximately 43% of motor-vehicle crashes and 27% of near-crashes. Rapidly developing in-vehicle technology and electronic devices place additional demands on drivers, which might lead to distraction and diminished capacity to perform driving tasks. This situation threatens safe driving. Technology that can detect and mitigate distraction by alerting drivers could play a central role in maintaining safety. Correctly identifying driver distraction in real time is a critical challenge in developing distraction mitigation systems, and this function has not been well developed. Moreover, the greatest benefit may be from real-time distraction detection in advance of dangerous breakdowns in driver performance.
Based on driver performance, two types of distraction - visual and cognitive - are identified. These types of distraction have very different effects on visual behavior and driving performance; therefore, they require different algorithms for detection. Distraction detection algorithms typically rely on either eye measures or driver performance measures because the effect of distraction on the coordination of measures has not been established. Combining both eye glance and vehicle data could enhance the ability of algorithms to detect and differentiate visual and cognitive distraction.
The goal of this research is to examine whether poor coordination between visual behavior and vehicle control can identify diminished attention to driving in advance of breakdowns in lane keeping. The primary hypothesis of this dissertation is that detection of changes in eye-steering relationship caused by distraction could provide a prospective indication of vehicle state changes. Three specific aims are pursued to test this hypothesis. The first aim examines the effect of distracting activity on eye and steering movements to assess the degree to which the correlation parameters are indicative of distraction. The second aim applies a control-theoretic system identification approach to the eye movement and steering data to distinguish between distracted and non-distracted conditions. The third aim examines whether changes of eye-steering coordination associated with distraction provide a prospective indication of breakdowns in driver performance, i.e., lane departures.
Together, the three aims show how that a combination of visual and steering behavior, i.e., eye-steering model, can differentiate between non-distracted and distracted state. This model revealed sensitivity to distraction associated with off-road glances. The models derived for different drivers have similar structure and fit to data from other drivers reasonably well. In addition, the differences in model order and model coefficients indicate the variability in driving behavior: some people generate more complex behavior than others. As was expected, eye-steering correlation on straight roads is not as strong as observed on curvy roads. However, eye-steering correlation measured through correlation coefficient and time delay between two movements is sensitive to different types of distraction. Time delay mediates changes in lane position and the eye-steering system predicts breakdowns in lane keeping. This dissertation contributes to developing a distraction detection system that integrates visual and steering behavior. More broadly, these results suggest that integrating eye and steering data can be helpful in detecting and mitigating impairments beyond distraction, such as those associated with alcohol, fatigue, and aging.
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Toussant, Erica A. "Analyzing the Impacts of Driver Familiarity/Unfamiliarity at Roundabouts." Ohio University / OhioLINK, 2016. http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1451907184.
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Malta, Lucas, Chiyomi Miyajima, and Kazunori Takeda. "A Study of Driver Behavior Under Potential Threats in Vehicle Traffic." IEEE, 2009. http://hdl.handle.net/2237/13901.
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Chen, Rong. "Driver Behavior in Car Following - The Implications for Forward Collision Avoidance." Diss., Virginia Tech, 2016. http://hdl.handle.net/10919/71785.
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Forward Collision Avoidance Systems (FCAS) are a type of active safety system which have great potential for rear-end collision avoidance. These systems use either radar, lidar, or cameras to track objects in front of the vehicle. In the event of an imminent collision, the system will warn the driver, and, in some cases, can autonomously brake to avoid a crash. However, driver acceptance of the systems is paramount to the effectiveness of a FCAS system. Ideally, FCAS should only deliver an alert or intervene at the last possible moment to avoid nuisance alarms, and potentially have drivers disable the system. A better understanding of normal driving behavior can help designers predict when drivers would normally take avoidance action in different situations, and customize the timing of FCAS interventions accordingly. The overall research object of this dissertation was to characterize normal driver behavior in car following events based on naturalistic driving data.
The dissertation analyzed normal driver behavior in car-following during both braking and lane change maneuvers. This study was based on the analysis of data collected in the Virginia Tech Transportation Institute 100-Car Naturalistic Driving Study which involved over 100 drivers operating instrumented vehicles in over 43,000 trips and 1.1 million miles of driving. Time to Collision in both braking and lane change were quantified as a function of vehicle speed and driver characteristics. In general, drivers were found to brake and change lanes more cautiously with increasing vehicle speed. Driver age and gender were found to have significant influence on both time to collision and maximum deceleration during braking. Drivers age 31-50 had a mean braking deceleration approximately 0.03 g greater than that of novice drivers (age 18-20), and female drivers had a marginal increase in mean braking deceleration as compared to male drivers. Lane change maneuvers were less frequent than braking maneuvers. Driver-specific models of TTC at braking and lane change were found to be well characterized by the Generalized Extreme Value distribution. Lastly, driver's intent to change lanes can be predicted using a bivariate normal distribution, characterizing the vehicle's distance to lane boundary and the lateral velocity of the vehicle.
This dissertation presents the first large scale study of its kind, based on naturalistic driving data to report driver behavior during various car-following events. The overall goal of this dissertation is to provide a better understanding of driver behavior in normal driving conditions, which can benefit automakers who seek to improve FCAS effectiveness, as well as regulatory agencies seeking to improve FCAS vehicle tests.Ph. D.
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Fry, Patrick J. "Safety Evaluation of Billboard Advertisements on Driver Behavior in Work Zones." Ohio University / OhioLINK, 2013. http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1366489662.
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Higgs, Bryan James. "Emotional Impacts on Driver Behavior: An Emo-Psychophysical Car-Following Model." Diss., Virginia Tech, 2014. http://hdl.handle.net/10919/64901.
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This research effort aims to create a new car-following model that accounts for the effects of emotion on driver behavior. This research effort is divided into eight research milestones: (1) the development of a segmentation and clustering algorithm to perform new investigations into driver behavior; (2) the finding that driver behavior is different between drivers, between car-following periods, and within a car-following period; (3) the finding that there are patterns in the distribution of driving behaviors; (4) the finding that driving states can result in different driving actions and that the same driving action can be the result of multiple driving states; (5) the finding that the performance of car-following models can be improved by calibration to state-action clusters; (6) the development of a psychophysiological driving simulator study; (7) the finding that the distribution of driving behavior is affected by emotional states; and (8) the development of a car-following model that incorporates the influence of emotions.Ph. D.
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Kondyli, Alexandra. "Breakdown probability model at freeway-ramp merges based on driver behavior." [Gainesville, Fla.] : University of Florida, 2009. http://purl.fcla.edu/fcla/etd/UFE0024857.
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Kyung, Gyouhyung. "An integrated human factors approach to design and evaluation of the driver workspace and interface: Driver perceptions, behaviors, and objective measures." Diss., Virginia Tech, 2008. http://hdl.handle.net/10919/27939.
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An ergonomic driver workspace and interface design is essential to ensure a healthier and comfortable driving experience in terms of driver perceptions, postures, and interface pressures. Developing more effective methods for driver-side interior design and evaluation, hence, requires thorough investigation of: 1) which perceptual responses are more relevant to ensuring ergonomic quality of a design, 2) the interrelationships among perceptual responses and objective measures, and 3) whether current assumptions regarding driver behaviors, and tools for specifying these behaviors, are valid for the design and evaluation. Existing studies, however, have rarely addressed these topics comprehensively, and often have been conducted with unsubstantiated assumptions. In contrast, this work sought to address these topics in a way that jointly considers characteristics of driver perceptions, behaviors, and objective measures to develop an improved design and evaluation methodology for driver workspace and interface, and that can also investigate the validity of implicit assumptions regarding perceptual relevance and driversâ behaviors.
The first part of this work investigated driversâ perceptions in relation to driver workspace design and evaluation. Specifically, it examined the efficacy of several perceptual ratings, when used for evaluating automobile interface design. Results showed that comfort ratings were more effective at distinguishing among interface designs, in contrast to the current common practice of using discomfort ratings for designing and evaluating interface designs. Two distinct decision processes to relate local to global perceptions were also identified (i.e., global comfort as an average of local comforts, and global discomfort predominantly influenced by maximal local discomforts). These findings were observed consistently across age and cultural groups. In addition, this work provided empirical support for an earlier hypothetical comfort/discomfort model, which posited comfort and discomfort are complementary, yet independent entities.
In order to facilitate the integration of driver perceptions and dynamic behaviors into driver workspace design and evaluation, the second part of this work clarified the relationships between perceptual ratings and various types of driver-seat interface pressure. Interface pressure was found to be more strongly related to overall and comfort ratings than to discomfort ratings, which is also in marked contrast with existing work that has focused on identifying association between discomfort and interface pressure. Specific pressure interface requirements for comfortable driver workspace design and evaluation were also provided.
Lastly, this work specified more rigorous driving postures for digital human models (DHMs), based on actual driversâ perceptions, postural sensitivity, and static behavioral characteristics, to facilitate proactive design and evaluation that enables cost/time efficient vehicle development. Driversâ behavioral characteristics observed in this work were applied to the driver workspace design. First, postural sensitivity obtained by using a psychophysics concept has been applied to determination of core seat track ranges. Second, postural data have been used: 1) to review relevant industry standards on driver accommodation, 2) to investigate whether driving postures are bilaterally asymmetric, 3) to provide comfortable joint ranges, and lastly 4) to identify driversâ postural strategies for interacting with a vehicle.
Overall, this work identified three important behavioral characteristics, specifically a bilateral imbalance in terms of interface pressure, bilaterally asymmetric joint posture, and postural strategies identified by cluster analysis. Such characteristics can be embedded in DHMs to describe more accurately actual driver behaviors inside a driver workspace, which is deemed to be a fundamental step to improved virtual ergonomic vehicle design and evaluation. In addition, the strategy-based classification method used in this work can be extended to simulate and predict more complex human motions. Practical and fundamental findings of this work will facilitate efficient and proactive design and evaluation of driver workspace and interface, and will help provide a healthier driving experience for a broader range of individuals.Ph. D.
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Amata, Hideomi, Chiyomi Miyajima, Takanori Nishino, Norihide Kitaoka, and Kazuya Takeda. "Prediction model of driving behavior based on traffic conditions and driver types." IEEE, 2009. http://hdl.handle.net/2237/13899.
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Fu, Ting. "Effects of adverse winter weather conditions on highway traffic and driver behavior." Thesis, McGill University, 2014. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=123259.
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This research looks into the impact of adverse winter weather conditions on highway driver behaviors using microscopic data from loop detectors and video cameras (e.g., hourly average speed, trajectories, lane changes, time-to-collisions measures). This thesis is composed of two main sections in addition to the introductory section: i) direct and lagged effects of adverse weather on hourly speeds and volumes; and ii) direct effect of adverse weather on driver behaviors (microscopic) measured at the vehicle level using video data. The first part of the thesis presents a review of literature related to past research on the topic. The second part investigates the direct and lagged effects of adverse winter weather conditions on the operating speed in a number of highway segments in Ontario using a time-series approach. This is complemented by the analysis of hourly traffic volumes in the region of Montreal, Canada, using data from magnetic loop detectors as well. In speed modeling, the effect of adverse weather was studied using data from multiple sites including both urban and rural highways, considering weekdays versus weekends separately. For this purpose, a large dataset containing hourly traffic data, weather variables (e.g., temperature, snow, wind speed), and surface conditions was used. A few previous studies have examined the effect of snowstorms on traffic parameters; however, little research has been done regarding the spillover effects (lagged effects) that adverse weather conditions may have on travel demand and traffic patterns. Extreme events or weather conditions might have a strong effect on traffic conditions not only during the events, but also before and after the events. In this study, time-series regression techniques―in particular, Autoregressive Integrated Moving Average (ARIMA) models―were used to model the highway operating speed. These methods are able to consider the serial correlation among error terms. The results indicate that snowstorms have a statistically significant effect on the speed. The lagged effects are however offset by the time and intensity of winter maintenance operations during and after the event. The effect of weather also varies depending on the type of site (urban or rural) and day of the week. Similarly, the effects of different weather variables including their lagged effects were analyzed using hourly traffic volume data. Despite the fact that information of the road surface condition was not available, this analysis is in accordance with previous finding, showing the utility of ARIMA approaches in modeling the highway volume as well. The results of this study can be applied in quantifying the mobility effect of winter weather and benefits of winter road maintenance. In recent years, driver behavior analysis using microscopic (vehicle level) data is a topic that is attracting more attention in road safety analysis. This popularity has brought about research in many different innovative techniques and microscopic measures used to quantify and analyze driver behavior. In the second part of this thesis, it demonstrates a method of analyzing driver behavior using video data approach. This thesis elucidates both a manual and an automated, computer-based method to analyze driver behavior. It also uses the computer-based method to evaluate the effect of adverse winter weather conditions on the driver behavior of highway users. Both the manual and the automated approaches have been used with 15 video recordings obtained from three different locations on the Don Valley Parkway (DVP) in Toronto, Ontario. The results demonstrate the effectiveness of the automated method in analyzing driver behavior, as well as in evaluating the impact of adverse winter weather conditions on driver behavior.La thèse présente l'impact des conditions météorologiques hivernales défavorables sur les comportements des conducteurs de la route à l'aide de données microscopiques de détecteurs de mouvement et des caméras vidéo (e.g., la vitesse horaire moyenne, les trajectoires, les changements de voie, des mesures de temps à la collision) La thèse est composée de deux sections principaux, en plus de l'introduction: i) les effets directs et décalés des conditions météorologiques défavorables sur la vitesse et le volume horaire; et ii) l'effet direct des conditions météorologiques défavorables sur le comportement microscopique des conducteurs mesurées au niveau du véhicule à l'aide de données vidéo.La première partie de la thèse propose une revue de la littérature sur le sujet. La deuxième partie examine les effets directs et décalés des conditions météorologiques hivernales défavorables sur la vitesse opérationnelle dans un certain nombre de segments de la route en Ontario en utilisant une approche de séries chronologiques. Ceci est complété par l'analyse des volumes de trafic horaires dans la région de Montréal, au Canada, en utilisant également les données de détecteurs de boucles magnétiques. Pour modéliser la vitesse, l'effet des conditions météorologiques défavorables a été étudié en utilisant des données provenant de plusieurs sites, dont deux autoroutes urbaines et rurales. Les jours de semaine et les week-ends ont été considérés séparément. Certaines études antérieures ont examiné l'effet de tempêtes de neige sur les paramètres de trafic, mais peu a été fait en ce qui concerne les effets d'entraînement (effets différés) que les conditions météorologiques défavorables peuvent avoir sur la demande de voyage et sur les modèles de trafic. Dans cette étude, les techniques de régression chronologique - en particulier les modèles autorégressives moyennes mobiles intégré (ARIMA) - ont été utilisées pour modéliser la vitesse opérationnelle de l'autoroute. A partir des résultats, on peut déduire que les tempêtes de neige ont un effet statistiquement significatif sur la vitesse. Les effets décalés sont toutefois compensés par la durée et l'intensité des opérations d'entretien hivernal pendant et après l'événement. L'effet de la météo varie aussi en fonction du type de site (urbain ou rural) et le jour de la semaine. Les résultats de cette étude peuvent être appliqués pour quantifier l'effet de la mobilité des conditions météorologiques et les avantages de l'entretien des routes en hiver. De même, les effets des différentes variables météorologiques, y compris leurs effets décalés ont été analysés à l'aide des données de volume de trafic. Malgré que l'information de l'état de surface de la route n'était pas disponible, cette analyse est conforme aux financements antérieurs, montrant également l'utilité des approches ARIMA sur le volume de la route. Au cours des dernières années, le comportement du conducteur en utilisant des données microscopique (niveau du véhicule) est un sujet qui attire plus d'attention à l'analyse de la sécurité routière. Cette popularité a entraîné des recherches sur de nombreux techniques novatrices et le développement de mesures microscopiques utilisées pour quantifier et analyser le comportement du conducteur. Dans la deuxième partie de cette thèse, une méthode est démontrée pour analyser le comportement du conducteur en utilisant l'approche de données vidéo. Cette thèse présente à la fois une démarche manuel et une méthode informatique automatisée pour analyser le comportement du conducteur. Les méthodes manuel et automatique sont utilisées sur 15 enregistrements vidéo obtenus à trois endroits différents sur le Don Valley Parkway (DVP) à Toronto, en Ontario. Les résultats démontrent l'efficacité de la méthode automatisée pour analyser le comportement du conducteur, ainsi que dans l'évaluation de l'impact des conditions météorologiques hivernales défavorables sur le comportement des conducteurs.
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Aria, Erfan. "Investigation of automated vehicle effects on drivers behavior and traffic performance." Thesis, Linköpings universitet, Kommunikations- och transportsystem, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-126600.
Full textAbstract:
Advanced Driver Assistance Systems (ADAS) offer the possibility of helping drivers to fulfill their driving tasks. Automated vehicles are capable of communicating with surrounding vehicles (V2V) and infrastructure (V2I) in order to collect and provide essential information about driving environment. Studies have proved that automated vehicles have a potential to decrease traffic congestion on road networks by reducing the time headway, enhancing the traffic capacity and improving the safety margins in car following. Furthermore, vehicle movement and drivers behavior of conventional vehicles will be affected by the presence of automated vehicles in traffic networks. Despite different encouraging factors, automated driving raises some concerns such as possible loss of situation awareness, overreliance on automation and degrading driving skills in absence of practice. Moreover, coping with complex scenarios, such as merging at ramps and overtaking, in terms of interaction between automated vehicles and conventional vehicles need more research. This thesis work aims to investigate the effects of automated vehicles on drivers behavior and traffic performance. A broad literature review in the area of driving simulators and psychological studies was performed to examine the automated vehicle effects on drivers behavior. Findings from the literature survey, which has been served as setup values in the simulation study of the current work, reveal that the conventional vehicles, which are driving close to the platoon of automated vehicles with short time headway, tend to reduce their time headway and spend more time under their critical time headway. Additionally, driving highly automated vehicles is tedious in a long run, reduce situation awareness and can intensify driver drowsiness, exclusively in light traffic. In order to investigate the influences of automated vehicles on traffic performance, a microscopic simulation case study consisting of different penetration rates of automated vehicles (0, 50 and 100 percentages) was conducted in VISSIM software. The scenario network is a three-lane autobahn segment of 2.9 kilometers including an off-ramp, on-ramp and a roundabout with some surrounding urban roads. Outputs of the microscopic simulation in this study reveal that the positive effects of automated vehicles on roads are especially highlighted when the network is crowded (e.g. peak hours). This can definitely count as a constructive point for the future of road networks with higher demands. In details, average density of autobahn segment remarkably decreased by 8.09% during p.m. peak hours in scenario with automated vehicles. Besides, Smoother traffic flow with less queue in the weaving segment was observed. Result of the scenario with 50% share of automated vehicles moreover shows a feasible interaction between conventional vehicles and automated vehicles. Meaningful outputs of this case study, based on the input data from literature review, demonstrate the capability of VISSIM software to simulate the presence of automated vehicles in great extent, not only as an automated vehicle scenario but also a share of them, in traffic network. The validity of the output values nonetheless needs future research work on urban and rural roads with different traffic conditions.
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Brown, Sarah Beth. "Effects of Haptic and Auditory Warnings on Driver Intersection Behavior and Perception." Thesis, Virginia Tech, 2005. http://hdl.handle.net/10919/31844.
Full textAbstract:
Intersection crashes account for over one-third of all crashes in the U.S., and 39% of these result in injury or death. As part of a larger effort to develop and evaluate in-vehicle countermeasures to reduce the number of intersection-related crashes, haptic warnings and a combined haptic/auditory warning were explored and compared to combined visual/auditory warnings.
The first phase of this study determined which haptic brake pulse warning candidate most often resulted in the driver successfully stopping for an intersection. Five brake pulse warnings were tested (varied with respect to jerk, duration, and the number of pulses). Participants receiving the haptic warnings were 38 times more likely to stop at the intersection than those receiving no warning and 7.6 times more likely to stop than those receiving a combined visual/auditory tone warning. The 600ms-3 pulses condition was advanced to the second phase because it provided the longest warning and had a more favorable subjective rating; it was then combined with an auditory verbal warning (urgent â STOPâ ). This phase determined whether the added verbal warning resulted in differences from the haptic warning alone. Although the warning was activated 7.62 m (25 ft) closer to the intersection in the second phase than in the first phase, there were no significant differences for the reaction times and distance to stop bar. Participants receiving the haptic plus auditory verbal warning were also 1.5 times more likely to stop than those who received the haptic warning alone. Overall, this study shows that haptic warnings show promise for warning drivers of impending intersection violations. Guidelines for haptic intersection warnings were developed, including a recommendation that haptic warnings be combined with auditory verbal warnings for increased warning effectiveness.
Master of Science
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Toth, Christopher Stephen. "Empirical study of the effect of offramp queues on freeway mainline traffic flow." Diss., Georgia Institute of Technology, 2014. http://hdl.handle.net/1853/53098.
Full textAbstract:
The dissertation examines the relationship between the number of lane changes, the speed of the ramp lane, and the location upstream of the ramp split. Analyses indicate the number of lane changes exhibits a parabolic relationship with respect to the ramp lane speed, and the number of lane changes exhibits gamma-distributed relationship with respect to the distance upstream of the ramp. The macroscopic lane changing model presented is best characterized as the development of generalized lane-changing relationships, and provides a starting point from which more complex corridor-level models can be developed. This study also identifies an unusual car-following behavior exhibited by certain lane-changing drivers. When the target lane is moving slowly, some lane-changing drivers will slow down, causing a disruption in their initial lane. Regression analysis is used to estimate the speed upstream of the initial lane to indicate the disruption is responsible for the lateral propagation of congestion. The lane choice of exiting vehicles is also studied. Lane choice appears to be a function of origin/destination, and freeway speed. As speeds in the general purpose lanes decrease, exiting vehicles are more likely to wait longer to move into the exit ramp lanes, resulting in an increased lane changing density.
Results from this study are expected to have the greatest impact on microscopic lane-change model validation. Additionally, results have implications for design and safety issues associated with freeway ramps. As data collection technologies improve and data becomes increasingly available, this research provides the basis for the further development of more elaborate lane-changing models.
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Heracles, Martin [Verfasser]. "Vision-based prediction of human driver behavior in urban traffic environments / Martin Heracles." Bielefeld : Universitätsbibliothek Bielefeld, 2014. http://d-nb.info/1060824329/34.
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CATANI, LORENZO. "A Simulation-Based Study on Driver Behavior when Negotiating Curves with Sight Limitations." Doctoral thesis, Politecnico di Torino, 2019. http://hdl.handle.net/11583/2732874.
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Bronaugh, Louise J. "Driving under the influence of positive behavior support : a behavior management program for students who ride the school bus /." Thesis, Connect to title online (Scholars' Bank) Connect to title online (ProQuest), 2008. http://hdl.handle.net/1794/8161.
Full textAbstract:
Thesis (Ph. D.)--University of Oregon, 2008.Typescript. Includes vita and abstract. Includes bibliographical references (leaves 100-104). Also available online in Scholars' Bank; and in ProQuest, free to University of Oregon users.
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Jun, Jungwook. "Potential Crash Measures Based on GPS-Observed Driving Behavior Activity Metrics." Diss., Georgia Institute of Technology, 2006. http://hdl.handle.net/1853/19832.
Full textAbstract:
Identifying and understanding the relationships between observed driving behavior over long-term periods and corresponding crash involvement rates is paramount to enhancing safety improvement programs and providing useful insights for transportation safety engineers, policy markers, insurance industries, and the public. Unlike previous data collection methods, recent advancement in mobile computing and accuracy of global positioning systems (GPS) allow researchers to monitor driving activities of large fleets of vehicles, for long-time study periods, at great detail.
This study investigates the driving patterns of drivers who have and who have not experienced crashes during a 14-month study period using the longitudinally collected GPS data during a six-month Commute Atlanta study. This investigation allows an empirical investigation to assess whether drivers with recent crash experiences exhibit different driving or activity patterns (travel mileage, travel duration, speed, acceleration, speed stability duration, frequency of unfamiliar roadway activities, frequency of turn movement activities, and previous crash location exposures). This study also discusses various techniques of implementing GPS data streams in safety analyses. Finally, this study provides useful guidance for researchers who plan to evaluate the relationships between driver driving behavior and crash risk with large sample data and proposes driving behavior activity exposure metrics of individual drivers for possible safety surrogate measures as well as for driver re-training and education programs.
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McLaughlin, Shane Brendan. "Measurement of Driver Preferences and Intervention Responses as Influenced by Adaptive Cruise Control Deceleration Characteristics." Thesis, Virginia Tech, 1998. http://hdl.handle.net/10919/9751.
Full textAbstract:
In comparison to conventional cruise control, adaptive cruise control (ACC) vehicles are capable of sensing forward traffic and slowing to accommodate as necessary. When no forward vehicles are present, ACC function is the same as conventional cruise control. However, with ACC, when a slower vehicle is detected, the ACC system will decelerate and follow at a selected time-based distance. While slowing to follow, the driver will experience a system-controlled deceleration of the ACC vehicle. An experiment was conducted to evaluate driver preferences for the distance at which the primary deceleration occurs and the level of deceleration that is obtained. Driver intervention was required in one trial and driver response behavior was measured. Ten men and ten women in two age groups evaluated the decelerations from a cruise speed of 70mph to a following speed of 55mph behind a confederate lead vehicle on the highway. Evaluations can be made using four scales: Good vs. Bad, Comfortable vs. Uncomfortable, Jerky vs. Smooth, and Early vs. Late. Decelerations of approximately 0.06g which occur approximately 200ft to 250ft behind the lead vehicle were most preferred. Prior to intervention, foot position ranged from a point directly below the brake pedal to 16.4in from the brake pedal. Foot motion began between 21.12s time-to-collision (TTC) and 3.97s TTC. Eighty percent of the participants paused to "cover" the brake before final motion to activate the brake. The older age group intervened (braked) later than the younger age group. Driver braking after intervention ranged from 0.16g to 0.32g.Master of Science
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Gellatly, Andrew William. "The Use of Speech Recognition Technology in Automotive Applications." Diss., Virginia Tech, 1997. http://hdl.handle.net/10919/30373.
Full textAbstract:
The research objectives were (1) to perform a detailed
review of the literature on speech recognition technology
and the attentional demands of driving; (2) to develop
decision tools that assist designers of in-vehicle systems;
(3) to experimentally examine automatic speech recognition
(ASR) design parameters, input modalities, and driver
ages; and (4) to provide human factors recommendations
for the use of speech recognition technology in automotive
applications. Two experiments were conducted to
determine the effects of ASR design parameters, input
modality, and age on driving performance, system usability,
and driver preference/acceptance. Eye movement
behavior, steering input behavior, speed maintenance
behavior, reaction time to forward scene event, task
completion time, and task completion errors when driving
and performing in-vehicle tasks were measured. Driver
preference/acceptance subjective data were also recorded.
The results showed that ASR design parameters
significantly affected measures of driving performance,
system usability, and driver preference/acceptance.
However, from a practical viewpoint, ASR design
parameters had a nominal effect on driving performance.
Differences measured in driving performance brought on by
changes in ASR system design parameters were small
enough that alternative ASR system designs could be
considered without impacting driving performance. No
benefits could be claimed for ASR systems improving
driving safety/performance compared to current
manual-control systems. Speech recognition system design
demonstrated a moderate influence on the usability of
in-vehicle tasks. Criteria such as task completion times and
task completion errors were shown to be different between
speech-input and manual-input control methods, and under
different ASR design configurations. Therefore, trade-offs
between ASR system designs, and between speech-input
and manual-input systems, could be evaluated in terms of
usability. Finally, ASR system design had a nominal effect
on driver preference/acceptance. Further research is
warranted to determine if long-term use of ASR systems
with less than optimal design parameters would result in
significantly lower values for driver preference/acceptance
compared to data collected in this research effort. Human
factors recommendations for the use of ASR technology in
automotive applications are included. The
recommendations are based on the empirical research and
the literature review on speech recognition technology and
the attentional demands of driving.Ph. D.
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Reyes, Michelle Lynn. "Examining driver performance in response to work zone interventions in a driving simulator." Thesis, University of Iowa, 2010. https://ir.uiowa.edu/etd/729.
Full textAbstract:
Reductions in speed and, more critically, speed variability between vehicles are thought to reduce crash risk in work zones. Numerous factors, such as lane width and lateral clearance and activity level, have been shown to influence speed but very little research has considered how multiple factors might interact to affect driver performance in work zones. This study evaluated the effect of work zone barrier type, presence of a lateral buffer, and work zone activity level on measures of speed and lane position. Twelve middle aged and twelve senior subjects drove in a National Advanced Driving Simulator (NADS) MiniSim. The subjects drove faster and with less variability in work zones with concrete barriers. Measures of speed and lane position were more heterogeneous across groups with 42-inch channelizers compared to drums. Speed was reduced and more variable in work areas with a high level of activity than in areas with a low level of activity. On the whole, the presence of a lateral buffer reduced speed variability in the high activity areas but this response was not uniform across all drivers. This research demonstrates that driving simulators can be used to evaluate how work zone factors may interact with one another to affect driver performance for different driver groups. While the results from this study corresponded to observations from actual work zones, the driving simulator must be validated with on-road data before generalizations can be made.
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Schnelle, Scott C. "Development of Personalized Lateral and Longitudinal Driver Behavior Models for Optimal Human-Vehicle Interactive Control." The Ohio State University, 2016. http://rave.ohiolink.edu/etdc/view?acc_num=osu1480362246357462.
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Doerzaph, Zachary R. "Intersection Stopping Behavior as Influenced by Driver State: Implications for Intersection Decision Support Systems." Thesis, Virginia Tech, 2004. http://hdl.handle.net/10919/9935.
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It is estimated that as many as 2.7 million crashes occur each year at intersections or are intersection related; resulting in over 8500 fatalities each year. These statistics have prompted government and corporate sponsored research into collision countermeasure systems that can enhance safety at intersections. Researchers are investigating technologies to provide an infrastructure-based or infrastructure-cooperative Intersection Decision Support (IDS) systems. Such systems would use pre-specified algorithms to identify drivers that have a high likelihood of violating the traffic signal and thus increase the risk of a collision. The system would subsequently warn the violating driver to stop though an in-vehicle or infrastructure-mounted interface. An IDS algorithm must be designed to provide adequate time for the driver to perceive, react, and stop the vehicle, while simultaneously avoiding a high false alarm rate.
Prior to developing these algorithms, scientists must understand how drivers respond to traffic signals. Little research has focused on the influence of driver state on red-light running behavior or methods for distinguishing red light violators from non-violators. The objective of the present study was to define trends associated with intersection crossings under different driver states and to explore the point detection method of predicting red light running upstream of the intersection. This was accomplished through a test-track mixed-factor experiment with 28 participants. Each participant experienced a baseline (complete a full stop at the red light), distracted (misses signal phase change due to inattention), and willful (driver knowingly makes a late crossing in an attempt to 'beat the light') driver state conditions. To provide the opportunity for red-light running behavior from participants, the amber change interval began at five different distances from the intersection. These distances were located near and within the dilemma zone, a region in which drivers have a difficult time deciding whether to go or to stop. Data collected from in-vehicle sensors was statistically analyzed to determine significant effects between driver states, and to investigate point detection algorithms.Master of Science
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Alshatti, Danah Ahmed. "Examining Driver Risk Factors in Road Departure Conflicts Using SHRP2 Data." University of Dayton / OhioLINK, 2018. http://rave.ohiolink.edu/etdc/view?acc_num=dayton152534759506242.
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Lee, Dongkwan. "Driver Demographics, Built Environment, and Car Crashes:Implications for Urban Planning." The Ohio State University, 2015. http://rave.ohiolink.edu/etdc/view?acc_num=osu1420677824.
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Conran, Charles Arthur. "Modeling Microscopic Driver Behavior under Variable Speed Limits: A Driving Simulator and Integrated MATLAB-VISSIM Study." Thesis, Virginia Tech, 2017. http://hdl.handle.net/10919/78234.
Full textAbstract:
Variable speed limits (VSL) are dynamic traffic management systems designed to increase the efficiency and safety of highways. While the macroscopic performance of VSL systems is well explored in the existing literature, there is a need to further understand the microscopic behavior of vehicles driving in VSL zones. Specifically, driver compliance to advisory VSL systems is quantified based on a driving-simulation experiment and introduced into a broader microscopic behavior model. Statistical analysis indicates that VSL compliance can be predicted based upon several VSL design parameters. The developed two-state microscopic model is calibrated to driving-simulation trajectory data. A calibrated VSL microscopic model can be utilized for new VSL control and macroscopic performance studies, adding an increased dimension of realism to simulation work. As an example, the microscopic model is implemented within VISSIM (overriding the default car-following model) and utilized for a safety-mobility performance assessment of an incident-responsive VSL control algorithm implemented in a MATLAB COM interface. Examination of the multi-objective optimization frontier reveals an inverse relationship between safety and mobility under different control algorithm parameters. Engineers are thus faced with a decision between performing multi-objective optimization and selecting a dominant VSL control objective (e.g. maximizing safety versus mobility performance).Master of Science
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Sims, Brian K. "Driving and Thriving: School Bus Drivers and the Behavior Management Strategies They Use." Digital Commons @ East Tennessee State University, 2014. https://dc.etsu.edu/etd/2423.
Full textAbstract:
The purpose of this study was first to determine the satisfaction level of bus drivers pertaining to school building administration, transportation department, and student behaviors, and second to identify the common behavior management strategies used by bus driver in a particular school system in east Tennessee. I also compared the common behavior management strategies used by school bus drivers who are also employed by the school system in some position in addition to this vocation with school bus drivers who are not employed by the school system other than driving the school bus. I also compared behavior management strategies in the following categories: age, years of experience, and gender.
For this quantitative element of the study, I requested bus drivers who met the criteria complete an anonymous survey. The survey had 20 items that focus on the bus drivers' satisfaction in areas of school building administration, transportation department, and student behavior. Bus drivers responded to each item by selecting responses on a 5-point scale from extremely dissatisfied to extremely satisfied, with neutral being the middle point. A single sample t-test was conducted and the results showed bus drivers were satisfied to a significant extent with school building administration and transportation department, while bus drivers were neither satisfied or dissatisfied with student behavior. Bus drivers also ranked their top five behavior management strategies. Results were categorized by age, years of experience, gender, and whether they were employed by the school system in another position. The overall top five behavior management strategies by bus drivers were 1) Assigning a student to a particular seat, 2) Reporting students to school building administration, 3) Moving a student to a particular seat during the bus route, 4) Use of video surveillance, and 5) Discussing a student's behavior with a parent or guardian.
I also interviewed 10 school building administrators in the same school system for their perspective on student behavior management strategies recommended for bus drivers to use on school buses and also their perspective on the impact student behavior on a school bus has on a student at school. Responses were also solicited from school building administrators of their perspective of driver management practices that seem most and least conducive to managing and preventing behaviors on buses. I recorded the responses given to these questions and listed the responses along with any additional comments from administrators. Most of the responses correspond with the responses bus drivers gave in their interviews. Half of the administrators stated school buses should be operated like a classroom with rules and consequences.
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Kryschtal, Pamela Jean. "Driver Response to Dynamic Message Sign Safety Campaign Messages." Thesis, Virginia Tech, 2020. http://hdl.handle.net/10919/96703.
Full textAbstract:
Unsafe driving habits increase the severity of roadway accidents. The behaviors that are generally associated with unsafe driving are influenced by drivers and their decision to engage in dangerous habits. In order to solve this problem, Departments of Transportation use roadside safety campaigns. To gain a comprehensive understanding of the effectiveness of these campaigns, this research study captured five different metrics of effectiveness to understand what messages are effective and how to target messages to different groups of people. Since reading and interpreting the messages produces cognitive activation among participants, a neuroimaging technology called functional near-infrared spectroscopy (fNIRS) was used to measure neurocognitive activation as a proxy for response. The fNIRS system captures this cognitive activation by measuring change in oxygenated blood (oxy-Hb). An increase in oxy-Hb is a proxy for increased task engagement. The first journal paper provides an understanding of what types of messages are perceived as effective, are misunderstood, are memorable, are considered inappropriate, and cause the greatest increase in cognitive engagement. Overall, drivers perceive messages to be effective at changing behavior, but particular messages are perceived as more effective than others. Messages about distracted driving and driving without a seat belt, messages that are intended to produce a negative emotional response, and messages with statistics are the behaviors, emotions, and themes that are most likely to be perceived to change driver behavior. Messages about distracted driving and messages about statistics are most likely to be remembered by drivers. In general, drivers do not find messages used in safety campaigns to be inappropriate. Drivers elicit more cognitive attention to signs about distracted driving and signs with a humorous emotion. The second journal considers the effectiveness of these messages with different target demographics by further investigating the first journal's results by different dependent variables, including age, gender, and risky driving habits of the participants. In the second study, the results from the first study are further examined to determine if some campaigns are more effective among different demographics of drivers. The behavioral results indicated that females, drivers over 65, low-risk and high-risk drivers, and urban and rural drivers perceive the safety campaigns as more effective. The neurological data revealed that younger drivers had more activation in the ventrolateral prefrontal cortex, an area known for semantics and word processing, which might indicate more cognitive attention to these types of messages. This study provides a unique application of using neuroimaging techniques to understand driver response to safety messages. The recommendations for an effective safety campaign are to use messages about distracted driving, messages with an emotional stimulus, and messages about statistics. Messages about word play and rhyme are recommended for appealing to younger demographics.Master of Science
Messages like "New year, new you, use your blinker" and "May the 4th be with you, text I will not" are increasingly used to catch drivers' attention. The development and use of these non-traditional safety messages are distinctly different than messages previously displayed on highway signs because the intent of these messages is to modify driver behavior rather than just provide information. Unfortunately, there is little empirical evidence measuring how effective these messages are at changing driver behavior or guidance on how to target messages for specific groups of people. The goal of this study was to understand what types of non-traditional safety messages are effective and how to target these messages to different target audiences. Roadway collisions are made more severe when the cause of the incident involves dangerous driving habits, such as distracted, impaired, or aggressive driving. The problem is made even more severe by the fact that the habits that make driving dangerous are affected by the driver's decision to engage in risky driving behavior. The solution to this problem is to gain an understanding of driver preferences and response, a research effort this study will address. Reading and interpreting the messages produces cognitive activation among participants. The study uses functional near-infrared spectroscopy (fNIRS), which allows researchers to capture this cognitive activation by measuring change in oxygenated blood (oxy-Hb). This provides not only the ability to gain a more detailed understanding of driver response, but the ability to triangulate this with what drivers perceive as effective in changing driver behavior. In the first study, the participants felt that campaigns targeting distracted driving, messages with a negative emotion, and campaigns about statistics were significantly more effective at changing driver behavior compared to other behaviors, emotions, and themes. The neurological data revealed that drivers respond more to campaigns about distracted driving. However, the neurological data indicates that humorous messages and messages that fit under the theme word play and rhyme elicit a greater cognitive response. The second study furthers the first study and revealed that females, drivers over 65, low-risk and high-risk drivers, and urban and rural drivers perceive the safety campaigns as more effective. The neurological data revealed that younger and older males and older high-risk drivers respond with greater peak oxy-Hb when compared to other groups of people. This study advances the applicability of fNIRS in traffic related studies.