Relevant bibliographies by topics / The driver factors

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'The driver factors'

Author: Grafiati
Published: 4 June 2025
Last updated: 15 July 2025

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Journal articles on the topic "The driver factors"

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James, Rachel M., and Britton E. Hammit. "Identifying Contributory Factors to Heterogeneity in Driving Behavior: Clustering and Classification Approach." Transportation Research Record: Journal of the Transportation Research Board 2673, no. 10 (2019): 343–53. http://dx.doi.org/10.1177/0361198119849404.

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Previous research efforts using aerially collected trajectory-level data have confirmed the existence of inter-driver heterogeneity, where different car-following model (CFM) specifications and calibrated parameter sets are required to adequately capture drivers’ driving behavior. This research hypothesizes that there also exist clusters of drivers whose behavior is sufficiently similar to be considered a homogeneous group. To test this hypothesis, this study applies a 664-trip sample of trajectory-level data from the SHRP2 Naturalistic Driving Study to calibrate the Gipps, Intelligent Driver
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Fan, Chaojie, Shufang Huang, Shuxiang Lin, Diya Xu, Yong Peng, and Shengen Yi. "Types, Risk Factors, Consequences, and Detection Methods of Train Driver Fatigue and Distraction." Computational Intelligence and Neuroscience 2022 (March 24, 2022): 1–10. http://dx.doi.org/10.1155/2022/8328077.

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Train drivers’ inattention, including fatigue and distraction, impairs their ability to drive and is the major risk factor for human-caused train accidents. Many experts have undertaken numerous studies on train driver exhaustion and distraction, but a systematic study is still missing. Through a systematic review, this work aims to outline the types, risk factors, consequences, and detection methods of train driver fatigue and distraction. The effects of central nervous fatigue and cognitive distraction in train drivers during driving are caused by rest and sleep schedules, workload, automati
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Mueller, Alexandra S., Ian J. Reagan, and Jessica B. Cicchino. "Addressing Driver Disengagement and Proper System Use: Human Factors Recommendations for Level 2 Driving Automation Design." Journal of Cognitive Engineering and Decision Making 15, no. 1 (2021): 3–27. http://dx.doi.org/10.1177/1555343420983126.

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Level 2 driving automation has the potential to reduce crashes; however, there are known risks when using these systems, particularly as they relate to drivers becoming disengaged from driving. This paper provides data-driven recommendations for Level 2 driving automation design using the best currently available methods to encourage driver engagement and communicate where and how a system can safely be used. Our recommendations pertaining to driver engagement concern driver management systems that monitor the driver for signs of disengagement and return the driver to the loop using a multimod
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Farooq, Danish. "Statistical Evaluation of Risky Driver Behavior Factors that Influence Road Safety based on Drivers Age and Driving Experience in Budapest and Islamabad." European Transport/Trasporti Europei 80, ET.2020 (2020): 1–18. http://dx.doi.org/10.48295/et.2020.80.2.

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Driver behavior is considered as one of the most influential factors on road safety. Most of the drivers on road involve in risky driving attitudes which cause fatal and seriously injured road accidents. This study aims to evaluate and compare the risky driver behavior factors that influence road safety based on drivers age and driving experience for Budapest and Islamabad. To achieve this, the study utilized the well-proved driver behavior questionnaire (DBQ) designed on a three-point scale to analyse statistically the driver behavior responses on perceived road safety issues. The study overa
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Lee, John D. "Driving Safety." Reviews of Human Factors and Ergonomics 1, no. 1 (2005): 172–218. http://dx.doi.org/10.1518/155723405783703037.

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Driving is a common and hazardous activity that is a prominent cause of death worldwide. Driver behavior represents a predominant cause, contributing to over 90% of crashes. In this review, I will focus on how driver behavior influences driving safety by describing the types of crashes and their general causes, the driving process, the perceptual and cognitive characteristics of drivers, and driver types and impairments. Evidence from each of these perspectives suggests that breakdowns of a multilevel control process are the fundamental factors that undermine driving safety. Drivers adapt and
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Perterer, Nicole, Susanne Stadler, Alexander Meschtscherjakov, and Manfred Tscheligi. "Driving Together Across Vehicle." International Journal of Mobile Human Computer Interaction 11, no. 2 (2019): 58–74. http://dx.doi.org/10.4018/ijmhci.2019040104.

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Most research on vehicle-to-vehicle (V2V) communication is technology-driven, or focused on driver-to-driver interaction. Social communication between drivers and passengers across vehicles, with the same destination, is often neglected. Communication is influenced by context and occupant behavior, and has a significant effect on the collaborative driving scenario. An exploratory in-situ study with seven groups of two driver/co-driver pairs each, located in two separate vehicles, was conducted. On a predefined route, different subtasks had to be solved in a collaborative way. The study reveale
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Rodríguez, Daniel A., Marta Rocha, Asad J. Khattak, and Michael H. Belzer. "Effects of Truck Driver Wages and Working Conditions on Highway Safety: Case Study." Transportation Research Record: Journal of the Transportation Research Board 1833, no. 1 (2003): 95–102. http://dx.doi.org/10.3141/1833-13.

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The role of human capital and occupational factors in influencing driver safety has gained increased attention from trucking firms and policy makers. The influence of these factors, along with demographic factors, on the crash frequency of truck drivers is examined. A unique driver-level data set from a large truckload company collected over 26 months was used for estimating regression models of crash counts. On the basis of estimates from a zero-inflation Poisson regression model, results suggest that human capital and occupational factors, such as pay, job tenure, and percentage of miles dri
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Zhou, Yanhu, Jian John Lu, Edward A. Mierzejewski, and Xuewen Le. "Development of Driver Population Factors for Capacity Analysis of Signalized Intersections." Transportation Research Record: Journal of the Transportation Research Board 1710, no. 1 (2000): 239–45. http://dx.doi.org/10.3141/1710-28.

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In the Highway Capacity Manual (HCM), driver population factors are included to adjust for the impact of nonlocal drivers on freeway capacity. There are no such factors in the HCM to account for the possible change of capacity at signalized intersections caused by unfamiliar drivers in the traffic stream. The results obtained from a research study to develop driver population adjustment factors for capacity analysis of signalized intersections are summarized. Detailed procedures for quantifying driver population adjustment factors are presented. The factors were derived on the basis of data co
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Song, Woojin, Fu L. Woon, Alice Doong, et al. "Fatigue in Younger and Older Drivers: Effectiveness of an Alertness-Maintaining Task." Human Factors: The Journal of the Human Factors and Ergonomics Society 59, no. 6 (2017): 995–1008. http://dx.doi.org/10.1177/0018720817706811.

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Objective: The aim of this study was to examine the effects of an alertness-maintaining task (AMT) in older, fatigued drivers. Background: Fatigue during driving increases crash risk, and previous research suggests that alertness and driving in younger adults may be improved using a secondary AMT during boring, fatigue-eliciting drives. However, the potential impact of an AMT on driving has not been investigated in older drivers whose ability to complete dual tasks has been shown to decline and therefore may be negatively affected with an AMT in driving. Method: Younger ( n = 29) and older dri
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Farook, Fyaz, and Ravishankar Choulge. "Intelligent Advisory System for a Vehicle Driver Posture Assessment & Advisory for Fatigue-Free Drive." ARAI Journal of Mobility Technology 5, no. 3 (2025): 1713–30. https://doi.org/10.37285/ajmt.5.3.8.

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In today's competitive automotive landscape, prioritizing safety and comfort in commercial vehicles is non-negotiable. Introducing ERGO Advisor, a groundbreaking system poised to redefine the driving experience by proactively optimizing drivers' sitting posture. Acknowledging the pivotal role of a driver's behavior, we emphasize our commitment to driver well-being. Despite the myriad factors leading drivers to unknowingly deviate from optimal postures during long drives, ERGO Advisor steps in. With a strategically placed camera detecting critical comfort angles, our system issues real-time, au
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Dissertations / Theses on the topic "The driver factors"

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Johansson, Joel. "Why does a sleepy driver continue to drive?" Thesis, Department of computer and information science, Linköping University, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:vti:diva-596.

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Inom trafikforskningen är det allmänt känt att sömnighet är en starkt bidragande faktor vid trafikolyckor. Tidigare forskning har visat att sömnighet hos förare är närvarande i 16–-23 procent av alla bilolyckor. Inom flyg- och järnvägsdomänen har en metod, med en stark influens från human factors-området, kallad Fatigue risk management (FRM) använts för att undersöka hur sociala och organisatoriska faktorer påverkar personalens sömnighetsnivå. Dock har denna metod inte använts för att undersöka lastbilsförares sömnighetsnivå i någon större utsträckning. Studiens syfte var att undersöka hur las
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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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Wallén, Warner Henriette. "Factors Influencing Drivers' Speeding Behaviour." Doctoral thesis, Uppsala University, Department of Psychology, 2006. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-7308.

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<p>Every year many people all over the world are killed and severely injured in road traffic accidents. Even though driving too fast is a behaviour well known to contribute to both the number and the outcome of these accidents, drivers are still speeding. The general aim of this thesis, and its five empirical studies, is therefore to further the knowledge about drivers speeding behaviour by using the theory of planned behaviour and the model underpinning the driver behaviour questionnaire as frames of reference. The behavioural data used is obtained from field trials with intelligent speed ada
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El-Dabaja, Sarah S. "Drivers of "Driverless" Vehicles: A Human Factors Study of Connected and Automated Vehicle Technologies." Ohio University / OhioLINK, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1576670482075765.

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Körner, Julia. "Searching in lists while driving identification of factors contributing to driver workload /." [S.l.] : [s.n.], 2006. http://edoc.ub.uni-muenchen.de/archive/00005776.

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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
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Rylander, Martin, and Philip Persson. "Motivation : Vilka motivationsfaktorer driver nyexaminerade poliser." Thesis, Linnéuniversitetet, Institutionen för organisation och entreprenörskap (OE), 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:lnu:diva-35583.

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Bakgrund: Motivation är viktigt för att driva en till handling vilket alla har erfarenheter av. Oavsett vad det är för handling så ligger där alltid någon form av drivkraft bakom denna. Vi fann motivationsfaktorer inom den offentliga sektorn som mycket intressant och då främst polisyrket med deras unika arbetsuppgifter. Detta gjorde att vi ville undersöka vad poliser motiveras av.   Problemformulering: Vilka motivationsfaktorer driver nyexaminerade poliser?   Syfte: Syftet med denna studie är att söka en förståelse vad det är som motiverar nyexaminerade poliser.   Metod: Studien som gjorts är
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Tollefson, John Dietrich. "Identifying the factors that affect the severity of vehicular crashes by driver age." Thesis, University of Iowa, 2016. https://ir.uiowa.edu/etd/2285.

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Vehicular crashes are the leading cause of death for young adult drivers, however, very little life course research focuses on drivers in their 20s. Moreover, most data analyses of crash data are limited to simple correlation and regression analysis. This thesis proposes a data-driven approach and usage of machine-learning techniques to further enhance the quality of analysis. We examine over 10 years of data from the Iowa Department of Transportation by transforming all the data into a format suitable for data analysis. From there, the ages of drivers present in the crash are discretized depe
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Shafizadeh, Kevan R. "A statistical analysis of factors associated with driver-perceived road roughness on urban highways /." Thesis, Connect to this title online; UW restricted, 2002. http://hdl.handle.net/1773/10110.

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Kieliszewski, Cheryl A. "Twisted Metal: An Investigation into Observable Factors that Lead to Critical Traffic Events." Diss., Virginia Tech, 2005. http://hdl.handle.net/10919/29859.

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The purpose of this research was to explore traffic event severity relationships, evaluate the potentiality of a hazardous event, and develop a framework of observable event factors. Data was collected from three regions in Virginia, each assumed to exemplify a unique driving environment due to amount of traffic and infrastructure characteristics. In combination, a broad spectrum of site, traffic, and driver performance variables were accounted for. Observational techniques of surveillance, incident reporting, and inventorying were used to collect site, traffic, and driver data. This effor
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Books on the topic "The driver factors"

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Arun, Chatterjee, UNC Institute for Transportation Research and Education., University of Tennessee, Knoxville. Transportation Center., University Transportation Centers Program (U.S.), and Southeastern Transportation Center (U.S.), eds. Driver-related factors involved with truck accidents. University of North Carolina, Institute for Transportation Research and Education, 1994.

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Malchose, Donald Clarence. Identifying factors that predict teen driver crashes. Mountain-Plains Consortium, 2011.

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Gebers, Michael A. An inventory of California driver accident risk factors. California Dept. of Motor Vehicles, Research and Development Branch, 2003.

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Fuller, Ray. Human factors for highway engineers. Pergamon, 2002.

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R, Fuller, and Santos J. A, eds. Human factors for highway engineers. Pergamon, 2002.

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Engineers, Society of Automotive, and SAE World Congress (2007 : Detroit, Mich.), eds. Automotive lighting technology and human factors in driver vision and lighting. Society of Automotive Engineers, 2007.

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University of Michigan. Transportation Research Institute. and Turner-Fairbank Highway Research Center, eds. Human factors of in-vehicle driver information systems: An executive summary. U.S. Dept. of Transporation, Federal Highway Administration, Research and Development, Turner-Fairbank Highway Research Center, 1997.

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A, Boehm-Davis Deborah, University of Michigan. Transportation Research Institute., and Turner-Fairbank Highway Research Center, eds. Human factors of in-vehicle driver information systems: An executive summary. U.S. Dept. of Transporation, Federal Highway Administration, Research and Development, Turner-Fairbank Highway Research Center, 1997.

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United States. Office of Motor Carrier and Highway Safety., ed. Driver-related factors in crashes between large trucks and passenger vehicles. Federal Highway Administration, Office of Motor Carrier and Highway Safety, 1999.

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University of Michigan. Transportation Research Institute. and Turner-Fairbank Highway Research Center, eds. Human factors of in-vehicle driver information systems: An executive summary. U.S. Dept. of Transporation, Federal Highway Administration, Research and Development, Turner-Fairbank Highway Research Center, 1997.

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Book chapters on the topic "The driver factors"

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Parkes, Andrew, and Nick Reed. "Driver Training." In Simulators for Transportation Human Factors. CRC Press, 2017. http://dx.doi.org/10.1201/9781315609126-3.

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Naweed, Anjum. "Simulators and Train Driver Training." In Simulators for Transportation Human Factors. CRC Press, 2017. http://dx.doi.org/10.1201/9781315609126-6.

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Rahman, Md Mahmudur, Shuchisnigdha Deb, Daniel Carruth, and Lesley Strawderman. "Using Technology Acceptance Model to Explain Driver Acceptance of Advanced Driver Assistance Systems." In Advances in Human Factors of Transportation. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-20503-4_5.

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Lenné, Michael G., Trey Roady, and Jonny Kuo. "Driver State Monitoring for Decreased Fitness to Drive." In Handbook of Human Factors for Automated, Connected, and Intelligent Vehicles. CRC Press, 2020. http://dx.doi.org/10.1201/b21974-11.

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Muehlbacher, Dominik. "The Multi-Driver Simulation: A Tool to Investigate Social Interactions Between Several Drivers." In UR:BAN Human Factors in Traffic. Springer Fachmedien Wiesbaden, 2017. http://dx.doi.org/10.1007/978-3-658-15418-9_21.

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Naweed, Anjum, Janette Rose, Sangeeta Singh, and Damien Kook. "Risk Factors for Driver Distraction and Inattention in Tram Drivers." In Advances in Intelligent Systems and Computing. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-41682-3_22.

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Sharma, Sunil Kr, Sunil Kr Singh, and Subhash C. Panja. "Human Factors of Vehicle Automation." In Autonomous Driving and Advanced Driver-Assistance Systems (ADAS). CRC Press, 2021. http://dx.doi.org/10.1201/9781003048381-17.

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Auerswald, Rico, Alexander Frey, and Norbert Schneider. "Integrating Different Kinds of Driver Distraction in Controllability Validations." In UR:BAN Human Factors in Traffic. Springer Fachmedien Wiesbaden, 2017. http://dx.doi.org/10.1007/978-3-658-15418-9_29.

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Brandenburg, Stefan. "Human Factors of Automated Driving Systems." In Autonomous Driving and Advanced Driver-Assistance Systems (ADAS). CRC Press, 2021. http://dx.doi.org/10.1201/9781003048381-16.

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Maitre, Neeta, and Neeraj Hanumante. "Human Factors in Autonomous Driving Systems." In Autonomous Driving and Advanced Driver-Assistance Systems (ADAS). CRC Press, 2021. http://dx.doi.org/10.1201/9781003048381-19.

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Conference papers on the topic "The driver factors"

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Deiana, Francesco, Adria Roig, James Jackson, Cristina Periago, and Clara Cabuti Ferrer. "Driver Engagement." In 14th International Conference on Applied Human Factors and Ergonomics (AHFE 2023). AHFE International, 2023. http://dx.doi.org/10.54941/ahfe1003821.

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One of the great challenges around the advent of driver assistance systems is to ensure that drivers understand the true capability of technology, such that they can behave accordingly for safe vehicle operation. This understanding can be influenced by a range of factors including vehicle instructions, user interface and warnings, and system control behavior. Validation accounting for these important aspects is therefore central to understanding and comparing safety performance for real world use for overall system design implementations.This paper presents a test methodology specified for imp
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Diederichsa, Frederik, and Gloria Pöhlerb. "Driving Maneuver Prediction Based on Driver Behavior Observation." In Applied Human Factors and Ergonomics Conference. AHFE International, 2021. http://dx.doi.org/10.54941/ahfe100705.

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With respect to an increasing amount of driver assistance systems and automated driving functions, a higher chance of unappreciated action and intervention of these systems can be registered, which in turn lowers the acceptance by drivers and passengers. A reduction of unnecessary warnings and interventions can be achieved by making them adaptive to driver’s intentions and maneuvers planning. In order to learn which driver behavior indicates certain maneuver intentions, a rater-based method using video recordings is proposed in this paper. Three driving maneuvers, namely turning, changing lane
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C Mersinger, Molly, Daniel Graff, Carmen Van Ommen, Sabrina Ehrenfort, Jamie Talley, and Alex Chaparro. "Driver Monitoring Systems: Design Considerations for Aging Drivers." In 14th International Conference on Applied Human Factors and Ergonomics (AHFE 2023). AHFE International, 2023. http://dx.doi.org/10.54941/ahfe1003828.

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A number of automotive manufacturers including General Motors and Tesla offer vehicles with advanced semi-autonomous driving functions that the driver is expected to monitor. Monitoring by the human driver is essential given that these systems are known to have difficulty handling driving situations that human drivers negotiate easily. The human operator must, however, adjust to this new supervisory role of monitoring system operations rather than traditional driving. Additionally, drivers may trust the automation too much, believing the systems are more capable than they are and not actively
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Sabrinaabc, Beloufa, Vailleau Benjamina, Boucheix Jean-Michelb, Kemeny Andrasab, and Mérienne Frédéricb. "Eco-Driving with Electric Cars: Effect of Continuous and On-Demand Feedback on Driving Behavior and Safety." In Applied Human Factors and Ergonomics Conference. AHFE International, 2021. http://dx.doi.org/10.54941/ahfe100678.

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Analysis of driver behavior has been the purpose of many studies for several years. A new aspect is the introduction of electric vehicles on the car market and the fact drivers are more concerned with their consumptions in EV (Electric Vehicle) due to the lack of the appropriate infrastructures. However, only a few studies focusing on ecological behavior and consumption have been carried out. The primary goal of the present study was to assess empirically the impact of feedback on EV driving behavior involving autonomy management performance. We hypothesized that we could help the driver to ma
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Waters, Anthony, and Vincent Paglioni. "Advanced Driver Assistance Systems and Emotion-based Driver Behavior." In 16th International Conference on Applied Human Factors and Ergonomics (AHFE 2025). AHFE International, 2025. https://doi.org/10.54941/ahfe1006514.

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Automobiles have evolved over the decades to include an increasing number of automated systems that assist the driver or even take over control of the vehicle. As a result, the human demands from vehicles have changed so that cognitive power can be used to participate in other activities while driving. These advanced drivers assistance systems (ADAS) include features such as lane keeping assistance, adaptive cruise control, blind spot monitoring and emergency crash avoidance. Each of these systems works to improve vehicle safety, principally by decreasing the required human intervention in som
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Kikuta, Riku, Daniel Carruth, John Ball, Reuben Burch, and Ichiro Kageyama. "Risk assessment and observation of driver with pedestrian using instantaneous heart rate and HRV." In 14th International Conference on Applied Human Factors and Ergonomics (AHFE 2023). AHFE International, 2023. http://dx.doi.org/10.54941/ahfe1003827.

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Currently, human drivers outperform self-driving vehicles in many conditions such as collision avoidance. Therefore, understanding human driver behaviour in these conditions will provide insight for future autonomous vehicles. For understanding driver behaviour, risk assessment is applied so far as one of the approaches by using both subjective and objective measurement. Subjective measurement methods such as questionnaires may provide insight into driver risk assessment but there is often significant variability between drivers. Physiological measurements such as heart rate (HR), electroencep
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Soroa, Alessandro, Sabine Wollstädterb, and Andry Rakotonirainya. "Advanced In-Vehicle Applicationsto Mitigate Driver Aggression." In Applied Human Factors and Ergonomics Conference. AHFE International, 2021. http://dx.doi.org/10.54941/ahfe100698.

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Aggressive behavior at the steering wheel has been indicated as a contributing factor in a majority of crashes and anger has been compared to alcohol impairment in terms of probability to cause a crash. It has been shown that being in a state of anger or excitement while driving can decrease the drivers’ performances. . This paper reports the evaluation of 6 novel design alternatives of In-Vehicle Information Systems (IVIS) aimed at mitigating driver aggression. Each application presented was designed to tackle the following contributing factors to driver aggression: competitiveness, anonymity
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Han, Ziwen, Ying Zhao, Hao Yang, Nan Fu, and Yifan Han. "From the Driver's Point of View of Information Reception: Building a Design Strategy for Aiding Interaction with Novice Drivers." In 13th International Conference on Applied Human Factors and Ergonomics (AHFE 2022). AHFE International, 2022. http://dx.doi.org/10.54941/ahfe1001920.

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This paper focuses on the division of driving experience into novice drivers and experienced drivers, with novice drivers considered as the target group. The relationship between the two shows that novice driving is an inevitable process to become experienced driving and shows that the development and formation of driving habits is extraordinarily important. In practice, this is often the case: novice drivers are accompanied by driving instructors. However, the amount of information received by the novice driver is invariably increased. Not only do they have to receive information from the dri
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Walker, Guy, and Malcolm Calvert. "Driver Behaviour at Roadworks." In Applied Human Factors and Ergonomics Conference. AHFE International, 2021. http://dx.doi.org/10.54941/ahfe100629.

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Road networks around the world are reaching a critical stage in their lifecycle. Typically constructed in the 1960’s and 70’s, many of the structures, now over forty years old, require increasingly significant levels of maintenance in order to ensure their continued integrity and performance. Many national transport authorities while planning ahead for this use traffic microsimulation models to help them predict the likely effects of associated roadwork on traffic flow. The challenge faced is that these models consistently under-predict traffic flows, and the resultant queue lengths, even thou
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A. Banks, Victoria, and Neville A. Stanton. "Hands and Feet Free Driving: Ready or Not?" In Applied Human Factors and Ergonomics Conference. AHFE International, 2021. http://dx.doi.org/10.54941/ahfe100668.

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“Almost-driverless” cars are coming with an aim to improve the safety of our roads. Full automation of longitudinal and lateral control will enable the driver to become “hands and feet free” but without active control, one question remains. What is the driver actually doing? This paper looks at how multi-system automation that enables the driver to become “hands and feet free” may affect the driving system and the role of the driver within it. Using Operator Sequence Diagrams to explore Distributed Cognition in the driving system, the authors explore the interaction that may occur between the
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Reports on the topic "The driver factors"

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Tavakoli, Arash, Vahid Balali, and Arsalan Heydarian. How do Environmental Factors Affect Drivers’ Gaze and Head Movements? Mineta Transportation Institute, 2021. http://dx.doi.org/10.31979/mti.2021.2044.

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Studies have shown that environmental factors affect driving behaviors. For instance, weather conditions and the presence of a passenger have been shown to significantly affect the speed of the driver. As one of the important measures of driving behavior is the gaze and head movements of the driver, such metrics can be potentially used towards understanding the effects of environmental factors on the driver’s behavior in real-time. In this study, using a naturalistic study platform, videos have been collected from six participants for more than four weeks of a fully naturalistic driving scenar
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Ghanipoor Machiani, Sahar, Aryan Sohrabi, and Arash Jahangiri. Impact of Regular and Narrow AV-Exclusive Lanes on Manual Driver Behavior. Mineta Transportation Institute, 2020. http://dx.doi.org/10.31979/mti.2020.1922.

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This study attempts to answer the question of how a narrow (9-ft) lane dedicated to Automated Vehicles (AVs) would affect the behavior of drivers in the adjacent lane to the right. To this end, a custom driving simulator environment was designed mimicking the Interstate 15 smart corridor in San Diego. A group of participants was assigned to drive next to the simulated 9-ft narrow lane while a control group was assigned to drive next to a regular 12-ft AV lane. Driver behavior was analyzed by measuring the mean lane position, mean speed, and mental effort (self-reported/subjective measure). In
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Pulugurtha, Srinivas S., Sarvani Duvvuri, and Sonu Mathew. Risk Factors Associated with Crash Injury Severity Involving Trucks. Mineta Transportation Institute, 2022. http://dx.doi.org/10.31979/mti.2022.2117.

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Nearly 499,000 motor vehicle crashes involving trucks were reported across the United States in 2018, out of which 22% resulted in fatalities and injuries. Given the growing economy and demand for trucking in the future, it is crucial to identify the risk factors to understand where, when, and why the likelihood of getting involved in a severe or moderate injury crash with a truck is higher. This research, therefore, focuses on capturing and exploring risk factors associated with surrounding land use and demographic characteristics in addition to crash, driver, and on-network characteristics b
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Ekambaram, Karthikeyan, Bethany Frox, Niamh Bull, and Emma Lyndon. Pedal Misapplication Study. TRL Limited, 2023. http://dx.doi.org/10.58446/omrt5829.

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Pedal misapplication is when the driver applies the wrong pedal of a vehicle, for example: accelerating instead of braking. When followed by the inability to regain control, this can result in collisions, causing damage to vehicles, infrastructure, and potentially, fatal injury. Current figures of pedal misapplication occurrences are potentially underestimated as depends heavily on driver statements, which are often unreliable. As a result, investigators are reliant on other data sources such as camera footage and examining the vehicle controls to determine the cause of the collision. This stu
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Mansfield, Layla. Bumps along the long and winding road: Factors related to truck driver turnover and job-induced tension. Portland State University Library, 2000. http://dx.doi.org/10.15760/etd.1874.

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Debs, Luciana, Yanchao Zheng, Jesutoba Ademiloye, Yunfeng Chen, and Jiansong Zhang. Synthesis Study on Employing Snowplow Driving Simulators in Training. Purdue University, 2023. http://dx.doi.org/10.5703/1288284317614.

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Departments of Transportation (DOTs) need to mobilize workers under harsh weather conditions for winter operations.Traditional snowplow driver training at INDOT is usually conducted annually before the snow season; therefore, it does not replicate the conditions which drivers will be exposed to during winter operations. To this point, some state DOTs have incorporated simulators in their snowplow driver training. Despite this raised interest, few studies have (1) surveyed other state DOTs about the use of this equipment in winter operations driver training, or (2) provided a systematic conside
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Carter, R. J., F. S. Barickman, P. F. Spelt, R. L. Schmoyer, and J. R. Kirkpatrick. Feasibility of developing a portable driver performance data acquisition system for human factors research: Technical tasks. Volume 1. Office of Scientific and Technical Information (OSTI), 1998. http://dx.doi.org/10.2172/629463.

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Carter, R. J., and F. S. Barickman. Feasibility of developing a portable driver performance data acquisition system for human factors research: Design specifications. Volume 3. Office of Scientific and Technical Information (OSTI), 1998. http://dx.doi.org/10.2172/629464.

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9

Valencia J., Adriana M., Daniela Valdivia Llerena, Rodrigo Navas, and Martin Walter. The Mining Sector as a Driver of Energy and Technological Progress: Challenges and Enabling Factors for Private Investment and Sustainability. IDB Invest, 2025. https://doi.org/10.18235/0013387.

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The mining sector plays a crucial role in the energy transition, providing essential materials for developing advanced technologies. With their vast resources, countries in Latin America and the Caribbean have the potential to become key drivers of this transition. This DEBrief summarizes the challenges and enabling factors for fostering private sector investment in the sustainable extraction of critical minerals for the energy transition, highlighting key points from recent IDB publications.
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Fernandez, Andres, Andres Gonzalez, and Diego Rodriguez. Sharing a Ride on the Commodities Roller Coaster: Common Factors in Business Cycles of Emerging Economies. Inter-American Development Bank, 2015. http://dx.doi.org/10.18235/0011716.

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Fluctuations in commodity prices are an important driver of business cycles in small emerging market economies (EMEs). This paper documents how these fluctuations correlate strongly with the business cycle in EMEs. A commodity sector is then embedded into a multi-country EMEs business cycle model where exogenous fluctuations in commodity prices follow a common dynamic factor structure and coexist with other driving forces. The estimated model assigns to commodity shocks 42 percent of the variance in income, of which a considerable part is linked to the common factor. A further amplification me
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