Relevant bibliographies by topics / The driver

Contents

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

Academic literature on the topic 'The driver'

Author: Grafiati
Published: 4 June 2021
Last updated: 27 April 2022

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Journal articles on the topic "The driver"

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Chen, Desheng, and Qiaoning Xu. "A Swinging and Self-Actuating Friction Drive Device Used in Large-Scale Rotary Devices." Recent Patents on Mechanical Engineering 13, no. 1 (February 12, 2020): 41–48. http://dx.doi.org/10.2174/2212797612666191119102558.

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Background: Large-scale rotary devices often employ friction drives in order to be manufactured easily and usually select a large driving radius to reduce the friction forces needed. In traditional devices, the driver and driven friction wheels are required to be of higher roundness to avoid slipping between them. This makes the driven friction wheel difficult to be machined. In addition, generating adequate contact load between contacting surfaces is essential for friction drives, and the best way to achieve it is self-actuating loading. Objective: The purpose of this paper is to propose and analyze a patent about a new friction drive device, in which the driver friction wheel can roll along with the driven friction wheel throughout, and the contact load between the driver and driven friction wheels can be generated on the torque demand. Methods: By using two swinging gearboxes, the two driver friction wheels are both swinging, and thus both can roll along with the driven friction wheel floatingly. Therefore, the driven wheel can have some deviation in roundness. Besides, this design offers a condition to construct a torque-actuated loading mechanism. Driven by the input torque, each driver wheel turns and exerts a friction force on the driven wheel, and then the driven wheel applies a reactive force to each driver wheel. This reactive force tends to pull the driver wheel to the driven wheel, producing a wedging action. Thus, an appreciable amount of contact load between the driver and driven wheels will be generated. Results: The results show the contact load between the driver and driven friction wheels is directly proportional to the resistant torque acting on the friction drive device. The results also show that a “frictional locking” condition for the device to avoid slipping between the driver and driven friction wheels is needed and it depends on the geometric parameters of the device. Conclusion: A swinging and self-actuating friction drive device is developed by using two swinging gearboxes. Design principles were described and a design example for this friction drive device was demonstrated. This kind of friction drive device not only offers an alternative way to drive large-scale rotary devices, but also develops a new method to realize self-actuating loading for friction drives.
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Yang, Shiyan, Jonny Kuo, and Michael G. Lenné. "Analysis of Gaze Behavior to Measure Cognitive Distraction in Real-World Driving." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 62, no. 1 (September 2018): 1944–48. http://dx.doi.org/10.1177/1541931218621441.

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Cognitive distraction can impair drivers’ situation awareness and control performance in driving. An on-road study was conducted to examine the efficacy in the detection of driver cognitive distraction based on the driver monitoring system developed by Seeing Machines. Participants completed a 25-km test drive on the local public roads whilst engaging in a series of secondary tasks that were designed to trigger different types of cognitive distraction, such as conversation, comprehension, N-back, and route-planning tasks. The findings showed that percent road center (PRC), one of the promising gaze metrics, increased significantly with cognitive distraction when compared to baseline, but failed to distinguish between different forms of cognitive distraction Moreover, PRC’s sensitivity to cognitive distraction was found to be affected by the chosen radius of road center area. These findings of driver cognitive distraction measurement provide data-driven suggestions for the development of real-time driver monitoring systems in the wild.
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Palac, Daniel, Iiona D. Scully, Rachel K. Jonas, John L. Campbell, Douglas Young, and David M. Cades. "Advanced Driver Assistance Systems (ADAS): Who’s Driving What and What’s Driving Use?" Proceedings of the Human Factors and Ergonomics Society Annual Meeting 65, no. 1 (September 2021): 1220–24. http://dx.doi.org/10.1177/1071181321651234.

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The emergence of vehicle technologies that promote driver safety and convenience calls for investigation of the prevalence of driver assistance systems as well as of their use rates. A consumer driven understanding as to why certain vehicle technology is used remains largely unexplored. We examined drivers’ experience using 13 different advanced driver assistance systems (ADAS) and several reasons that may explain rates of use through a nationally-distributed survey. Our analysis focused on drivers’ levels of understanding and trust with their vehicle’s ADAS as well as drivers’ perceived ease, or difficulty, in using the systems. Respondents’ age and experience with Level 0 or Level 1 technologies revealed additional group differences, suggesting older drivers (55+), and those with only Level 0 systems as using ADAS more often. These data are interpreted using the Driver Behavior Questionnaire framework and offer a snapshot of the pervasiveness of certain driver safety systems.
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Abraham, Hillary, Bryan Reimer, and Bruce Mehler. "Advanced Driver Assistance Systems (ADAS): A Consideration of Driver Perceptions on Training, Usage & Implementation." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 61, no. 1 (September 2017): 1954–58. http://dx.doi.org/10.1177/1541931213601967.

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As the first phase of a larger project, drivers were recruited to drive for a month one of two different vehicles with a range of advanced driver assistance systems (ADAS). Training methods for introducing the systems and questionnaire and structured interview methods were tested for collecting driver perceptions and understanding of the technologies. Participant perceptions and selected observations are detailed.
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Farooq, Danish, Sarbast Moslem, Rana Faisal Tufail, Omid Ghorbanzadeh, Szabolcs Duleba, Ahsen Maqsoom, and Thomas Blaschke. "Analyzing the Importance of Driver Behavior Criteria Related to Road Safety for Different Driving Cultures." International Journal of Environmental Research and Public Health 17, no. 6 (March 14, 2020): 1893. http://dx.doi.org/10.3390/ijerph17061893.

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Driver behavior has been considered as the most critical and uncertain criteria in the study of traffic safety issues. Driver behavior identification and categorization by using the Fuzzy Analytic Hierarchy Process (FAHP) can overcome the uncertainty of driver behavior by capturing the ambiguity of driver thinking style. The main goal of this paper is to examine the significant driver behavior criteria that influence traffic safety for different traffic cultures such as Hungary, Turkey, Pakistan and China. The study utilized the FAHP framework to compare and quantify the driver behavior criteria designed on a three-level hierarchical structure. The FAHP procedure computed the weight factors and ranked the significant driver behavior criteria based on pairwise comparisons (PCs) of driver’s responses on the Driver Behavior Questionnaire (DBQ). The study results observed “violations” as the most significant driver behavior criteria for level 1 by all nominated regions except Hungary. While for level 2, “aggressive violations” is observed as the most significant driver behavior criteria by all regions except Turkey. Moreover, for level 3, Hungary and Turkey drivers evaluated the “drive with alcohol use” as the most significant driver behavior criteria. While Pakistan and China drivers evaluated the “fail to yield pedestrian” as the most significant driver behavior criteria. Finally, Kendall’s agreement test was performed to measure the agreement degree between observed groups for each level in a hierarchical structure. The methodology applied can be easily transferable to other study areas and our results in this study can be helpful for the drivers of each region to focus on highlighted significant driver behavior criteria to reduce fatal and seriously injured traffic accidents.
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Schmidt, Jürgen, Mariella Dreißig, Wolfgang Stolzmann, and Matthias Rötting. "The Influence of Prolonged Conditionally Automated Driving on the Take-Over Ability of the Driver." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 61, no. 1 (September 2017): 1974–78. http://dx.doi.org/10.1177/1541931213601972.

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Other than during manual and partly automated driving, the driver will not need to constantly observe and correct the path of his/her car with future conditionally automated driving (CAD) systems. The driver will be only responsible to stay alert and be ready to take-over the driving in a preset handover time, if requested. The aim of this simulator study was to examine the reactions of drivers, when requested to take-over after a long, monotonous conditionally automated drive. The conditionally automated drives of 20 drivers (mean driving time of 2:51 ± 0:18 h) were evaluated. To test their reaction and take-over ability, the drivers experienced four easy take-over situations and were additionally challenged with a demanding situation in their worst state regarding fatigue. There was no significant influence found of their fatigue state on the take-over time and quality. The different take-over times in different situations point merely towards an adaption of the drivers’ reactions onto the specific necessities of the different driving situations.
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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 (May 18, 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 Model, and Wiedemann 99 CFMs. Using the calibrated parameter coefficients, this research provides evidence of the existence of homogeneous groups of driving behavior using the expectation maximization clustering algorithm. Four classification algorithms are then applied to classify the trip’s cluster ID according to driver demographics. Driver age, income, and marital status were most commonly identified as important classification attributes, while gender, work status, and living status appear less significant. The classification algorithms, which sought to classify a trip’s behavioral cluster ID by the driver-specific attributes, achieved the highest accuracy rate when predicting the desired velocity car-following parameter clusters. This effort illustrates that some drivers drive sufficiently alike to form a cluster of similar behavior; moreover, it was confirmed that driver-specific attributes can be utilized to classify drivers into these homogeneous driver groups.
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Hanowski, Richard J., Robert J. Carroll, Walter W. Wierwille, and Rebecca L. Olson. "Light Vehicle-Heavy Vehicle Interactions: A Preliminary Assessment Using Critical Incident Analysis." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 46, no. 22 (September 2002): 1844–47. http://dx.doi.org/10.1177/154193120204602214.

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Two recently completed on-road in situ data collection efforts, one involving local/short haul trucking and the other long-haul trucking, provided a large data set in which to conduct an examination of critical incidents (crashes and near-crashes) that occurred between light vehicles and heavy vehicles. Video and non-video data collected during the two studies were used to characterize critical incidents that were recorded between light vehicle and heavy vehicle drivers. Across both studies, 210 light vehicle-heavy vehicle (LV-HV) critical incidents were recorded. Of these, 78 percent were initiated by the light vehicle driver. Aggressive driving on the part of the light vehicle driver was found to be the primary contributing factor for light vehicle driver initiated incidents. For heavy vehicle driver initiated incidents, the primary contributing factor was poor driving technique. The results suggest that efforts at addressing LV-HV interaction incidents should focus on light vehicle drivers who drive aggressively. Additionally, it is recommended that heavy vehicle drivers might benefit from improved driver training that includes instruction on defensive driving.
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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 (January 20, 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 multimodal escalation process with attention reminders, countermeasures for sustained noncompliance to the attention reminders, and proactive methods for keeping drivers engaged with respect to driver-system interactions and system functionality considerations. We also provide guidance on how the operational design domain (ODD), driver responsibilities, and system limitations should be communicated and how these systems must be self-limited within the ODD. In addition, we discuss the benefits and limitations of training to emphasize the importance of making these systems intuitive to all users, regardless of training, to ensure proper use. These recommendations should be applied as a whole, because selectively adhering to only some may inadvertently exacerbate the dangers of driver disengagement.
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Desmond, Paula A., Peter A. Hancock, and Janelle L. Monette. "Fatigue and Automation-Induced Impairments in Simulated Driving Performance." Transportation Research Record: Journal of the Transportation Research Board 1628, no. 1 (January 1998): 8–14. http://dx.doi.org/10.3141/1628-02.

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A driving simulator study investigated the effect of automation of the driving task on performance under fatiguing driving conditions. In the study, drivers performed both a manual drive, in which they had full control over the driving task, and an automated drive, in which the vehicle was controlled by an automated driving system. During both drives, three perturbing events occurred at early, intermediate, and late phases in the drives: in the automated drive, a failure in automation caused the vehicle to drift toward the edge of the road; in the manual drive, wind gusts resulted in the vehicle drifting in the same direction and magnitude as the “drifts” in the automated drive. Following automation failure, drivers were forced to control the vehicle manually until the system became operational again. Drivers’ lateral control of the vehicle was assessed during three phases of manual control in both drives. The results indicate that performance recovery was better when drivers had full manual control of the vehicle throughout the drive, rather than when drivers were forced to drive manually following automation failure. Drivers also experienced increased tiredness, and physical and perceptual fatigue symptoms following both drives. The findings have important implications for the design of intelligent transportation systems. Systems that reduce the driver’s perceptions of task demands of driving are likely to undermobilize effort in fatigued drivers. Thus, the results strongly support the contention that human-centered transportation strategies, in which the driver is involved in the driving task, are superior to total automation.
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Dissertations / Theses on the topic "The driver"

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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 lastbilsförare upplever, motarbetar och motverkar sömnighet i deras dagliga arbetssituation. Resultaten visar att lastbilsförare i sitt arbete möter en stor mängd trötthetsbidragande faktorer, som kan härledas både till organisatoriska faktorer och individuellt beteende. Möjliga sätt att motverka sömnighet bland lastbilsförare, riktade mot både individen och organisationen, föreslås.
In the traffic domain it is commonly known that sleepiness is a highly contributing factor in traffic accidents. Research has shown that sleepiness among drivers is present in about 16-–23 per cent of all car accidents. In the aviation and railway industry a method or framework with some shared influences from the Human Factors approach, called Fatigue Risk Management (FRM) has been used to investigate how social and organisational factors affect the personnel’s level of sleepiness. The overall aims of this study are to investigate how truck drivers’ experience, fight and counteract sleepiness in their daily work environment. The results show that drivers face a wide variety of sleep contributing factors, stemming from both organisational factors and individual behaviour. Possible ways of counteracting truck driver sleepiness, concerning both the individual and the organisation, are also suggested.
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de, Souza Lamas Jose Raphael. "An investigation into a driver-to-driver communication device to manage and improve the interaction between drivers." Thesis, University of Nottingham, 2018. http://eprints.nottingham.ac.uk/51362/.

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Drivers must communicate with other road users to make their intentions clear, thereby enhancing the quality of the driving experience, improving safety on the roads and avoiding accidents. This interaction can be made either formally using legal signals approved by legislative bodies (e.g. use of indicators), or informally (e.g. hand gestures). However, this informal interaction may not be clearly understood by all drivers, and may lead to stress, strong emotional responses or aggressive driving behaviour. Moreover, a single informal interaction, e.g. flashing the headlights, can have several different meanings such as “Your headlights are on”, “Thank you”, or “I want to overtake you”, depending on the situation. Driver interaction could be enhanced by an electronic driver-to-driver communication device (DDCD), which would allow motorists to exchange messages with each other. The technology associated with connected vehicles could be used for the design of this communication device. For example, wireless devices and sensors already allow vehicles to exchange information with other vehicles (V2V) and road infrastructure (V2I) at any time. This PhD research initially introduces a driver-to-driver communication framework depicting a set of variables or factors that have a decisive effect on the communication process. The framework is also comprised of a task analysis for the DDCD. The framework is later expanded to include a specific set of design recommendations linked back to the variables that affect the communication process. These recommendations are specifically related to the DDCD and are based on a review of the literature and results from empirical studies conducted as part of the PhD. A mixed-methods approach was adopted in this research to elicit opinions and attitudes of drivers, including interviews, observations, a workshop with academic experts and questionnaires. In total, five studies are described in the thesis, with STUDY A being an exploratory investigation on the feasibility of the DDCD. The second and third studies focused specifically on the task of receiving messages, with academic experts (STUDY B) and with regular drivers (STUDY C). A fourth study (STUDY D) involved on-road trials to investigate how drivers would identify a vehicle to send a message to. The final experiment (STUDY E) consisted of an evaluation in a driving simulator of a low-fidelity prototype of the communication device to send messages. The studies were based on a set of driving communication scenarios, which facilitated the exploration of potential issues with the use of a proposed technology before implementation. The scenarios represented different examples of how, why and when drivers might communicate with one another, and were used as the focal point with study participants. The findings from this research indicate that drivers would be willing to use an electronic communication device in situations directly related to the road context in which there is a decisive effect on their safety or that may alter their driving behaviour, such as a problem with their vehicle or a hazard on the road. There are many factors investigated in this research that have a significant effect on drivers’ communication process. These factors include, but are not limited to, time criticality, trust issues in message content, the effect of passengers, sender anonymity and the general purpose of communication. These research findings will significantly contribute to the limited academic research currently available on social and connected vehicles and can also provide invaluable information for the automotive industry.
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Karl, Charles A. "The learning driver meeting traveller information needs /." Swinburne Research Bank, 2003. http://adt.lib.swin.edu.au/public/adt-VSWT20060906.102946.

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Thesis (DBA) -- Swinburne University of Technology, Graduate School of Entrepreneurship, 2003.
Submitted for the degree of Doctor of Business Administration, Graduate School of Entrepreneurship, 2003. Typescript. Includes bibliographical references (p. 212-224).
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Karacik, Burak. "Driver Management for Less-than-Truckload Carriers." Diss., Georgia Institute of Technology, 2007. http://hdl.handle.net/1853/14465.

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The trucking industry is vitally important to the economy, providing an essential service by transporting goods between businesses and consumers. The less-than-truckload (LTL) industry is an important segment, serving businesses that ship quantities between 150 lbs and 10,000 lbs. Large LTL carriers use thousands of drivers to move loads between terminals in their network, and each driver may be used for multiple dispatches between rest periods. Driver wages are a major component of transportation costs. Consequently, cost-effective driver management is of crucial importance for the profitability of LTL carriers. This thesis investigates a variety of issues related to driver management. In this thesis, we describe a dynamic driver scheduling scheme developed for a large U.S. LTL carrier. Dynamic driver scheduling is challenging because drivers must abide by a complex set of rules, including government and union regulations, and trucking moves are not pre-scheduled. The technology developed combines greedy search with enumeration of time-feasible driver duties, and is capable of generating cost-effective schedules covering 15,000 20,000 loads in minutes. One of the key tactical questions faced by an LTL carrier is how many drivers to locate at each terminal. Unionized carriers have bid drivers that can only move loads between their domicile and a designated region. The developed allocation technology determines the number of drivers to allocate to each terminal as well as the designated region for bid drivers. Computational experiments based on real-life dispatch data demonstrate the effectiveness of our domiciling methodology, and show that union rules may result in substantially larger driver fleets, in some cases up to 50% larger. Finally, we investigate a fundamental question related to driver management in order to obtain some fundamental insights: determining the minimum number of drivers required to cover a set of loaded moves. The problem is shown to be polynomially solvable without any restrictions on driver schedules. For variants with restrictions, several easily computable lower bounds are derived, integer programming formulations are presented, and fast heuristics are designed and analyzed. A computational study provides insights into the quality of the lower bounds and heuristic solutions.
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Kusano, Stephanie Marie. "Feasibility of Restricted Driver Licenses for Suspended New Jersey Drivers." Thesis, Virginia Tech, 2012. http://hdl.handle.net/10919/76857.

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In 2010, there were 6,714,288 total registered drivers in New Jersey. Approximately 4% (267,485) of these drivers had a suspended driver's license. The intent of suspending a driver's license is to keep hazardous drivers off of the roads, in hopes of having a safer driving environment for others on the road. Drivers in New Jersey can have their driver's license suspended for a number of reasons. These include dangerous driving behaviors such as reckless driving and driving under the influence of alcohol or drugs. However, there are also reasons for suspension that have little or nothing to do with driver behavior, such as failure to pay child support, failure to pay MVC insurance surcharge, or failure to appear in court. While these offenses are all due of consequence, they have little or nothing to do with driver behavior. This research program will conduct an analysis of the issues and implications of implementing a restricted-use license program for suspended New Jersey drivers, detailing key issues associated with restricted-use license programs. It was found that over two-thirds of suspended drivers in New Jersey receive driver's license suspensions for both driving and non-driving-related offenses, whereas only about four-percent of suspended drivers in New Jersey receive a driver's license suspension for driving-related reasons only. It was also found that drivers suspended for non-driving related reasons have different driver behavior than drivers suspended for driving related reasons. Surveying both New Jersey police chiefs, as well as U.S. state motor vehicle agencies, it was found that there is a generally positive perception of restricted driver's license programs. Overall, it is recommended that the New Jersey Motor Vehicle Commission implement a restricted driver's license program in New Jersey.
Master of Science
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Ali, Ahmed M. "DRIVING SIMULATION AND REACTION TIME INVESTIGATION ON DRIVER FOOTEDNESS." University of Akron / OhioLINK, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=akron1561991269668204.

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Ribak, Judith H. "Characteristics of Older and Oldest Adult Drivers: Understanding Risky Driving." University of Cincinnati / OhioLINK, 2008. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1211932852.

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Mottaghi, Yashar, and Gabriel Adel. "Triac Driver Platform." Thesis, Linköpings universitet, Institutionen för systemteknik, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-77806.

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In the electronic industrials, power control of AC motors is commonly used. For example power control of a washing machine motor, a vacuum cleaner motor or a coffee machine motor. The company Rejlers Ingenjörer AB has many projects where power control of AC motors is included. A prototype card for this task can save time and money for the company in the future and this is the reason for this thesis. The motors are power controlled by a TRIAC and control of the trigging pulses to the TRIAC. This card is modularly built and can easily be adapted for future projects where the power control of AC motors are included. The prototype card can be used as a subsystem in a larger electronics projects or as it is in lab environment for testing and evaluating new motors.
Inom elektronikbranschen, exempelvis vitvarutillverkare är effektstyrning av ACmotorer vanligt förekommande. Det kan handla om effektstyrning av en diskmaskinsmotor, en dammsugarmotor eller en tvättmaskinsmotor. Företaget Rejlers ingenjörer AB har flera gånger fått uppdrag där effektstyrning av AC-motorer ingått och har behov av ett prototypkort för detta som ska kunna återanvändas i framtida projekt för att spara tid och pengar. Effektstyrningen av motorerna sker med hjälp av en triac och styrning av tändpulserna till denna triac. Detta kort är modulärt uppbyggd så att det enkelt kan anpassas till framtida projekt där effektstyrning av AC-motorer ingår. Prototypkortet kan användas som ett delsystem i ett större elektronikprojekt eller i labbmiljö för test och utvärdering av nya motorer.
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Chatterjee, Prateek. "Classic Driver VR." Digital WPI, 2018. https://digitalcommons.wpi.edu/etd-theses/1251.

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A VR car-driving simulator for evaluating the user experience of new drivers by helping them to learn driving rules and regulations. The Classic VR Driver helps new drivers to learn driving rules and regulations using various audio and visual feedback. The simulator helps them to get acquainted with the risks and mistakes associated with real life driving. In addition, the users have to play the game in an immersive environment using a Virtual Reality system. This project attempts to fulfill two important goals. The major goal is to evaluate whether the user can learn driving rules and regulations of the road. The game allows the users to take a road test. The road test determines the type of mistakes the user makes and it also determines if they passed or failed in it. I have conducted A/B testing and let the testers participate in user-interviews and user-survey. The testing procedure allowed me to analyze the effectiveness of learning driving rules from the simulator as compared to learning rules from the RMV (Registry of Motor Vehicles) manual. Secondly, the user experience was evaluated by allowing users to participate in user-interviews and user-surveys. It helped me to understand the positives and drawbacks of the game. These feedback are taken into consideration for future improvement. All these factors were considered to make the game as enjoyable and useful in terms of skill training.
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Li, Anying M. Eng Massachusetts Institute of Technology. "Learning driver gaze." Thesis, Massachusetts Institute of Technology, 2017. http://hdl.handle.net/1721.1/119533.

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Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2017.
This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.
Cataloged from student-submitted PDF version of thesis.
Includes bibliographical references (pages 65-69).
Driving is a singularly complex task that humans manage to perform successfully day in and day out, guided only by what their eyes can see. Given how prevalent, complex, and not to mention dangerous driving is, it's surprising that we don't really understand how drivers actually use vision to drive. The release of a large scale driving dataset with eye tracking data, DrEyeVe [1], makes analyzing the role of vision feasible. In this thesis, we 1) study the impact of various external features on driver attention, and 2) present a two-path deep-learning model that exploits both static and dynamic information for modeling driver gaze. Our model shows promising results against state-of-the-art saliency models, especially on sequences when the driver is not just looking straight ahead on the road. This model enables us to estimate important regions that the driver should be aware of, and potentially allows an automatic driving assistant to alert drivers of hazards on the road they haven't seen yet.
by Anying Li.
M. Eng.
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Books on the topic "The driver"

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Elman, Richard. Taxi driver. Milano: Bompiani, 1988.

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Mitchelhill, Barbara. The driver. Aylesbury: Ginn, 1989.

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Sallis, James. Driver: Roman. München: Heyne, 2011.

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Hill, Walter. The driver. London): Hollywood Scripts (Enterprise House, Cathles Road, London SW12 9LD, 1990.

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Schrader, Paul. Taxi driver. London: Faber and Faber, 1990.

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Niro, Robert De. Taxi driver. Culver City, Calif: Columbia TriStar Home Video, 1999.

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My driver. London: Telegram, 2009.

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ill, Ulrich George, ed. Truck driver. Mahwah, N.J: Troll Associates, 1989.

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Dale, Earnhardt. Driver #8. New York: Grand Central Publishing, 2009.

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Shrader, Paul. Taxi driver. London: Faber, 1990.

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Book chapters on the topic "The driver"

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Wang, Jianqiang, Lei Zhang, Xiaojia Lu, and Keqiang Li. "Driver driver Characteristics driver characteristics Based on Driver driver Behavior driver behavior." In Encyclopedia of Sustainability Science and Technology, 3099–108. New York, NY: Springer New York, 2012. http://dx.doi.org/10.1007/978-1-4419-0851-3_785.

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Wang, Jianqiang, Lei Zhang, Xiaojia Lu, and Keqiang Li. "Driver driver Characteristics driver characteristics Based on Driver driver Behavior driver behavior." In Transportation Technologies for Sustainability, 385–94. New York, NY: Springer New York, 2013. http://dx.doi.org/10.1007/978-1-4614-5844-9_785.

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Weik, Martin H. "driver." In Computer Science and Communications Dictionary, 462. Boston, MA: Springer US, 2000. http://dx.doi.org/10.1007/1-4020-0613-6_5611.

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Wang, Chao, Jing Gu, Jacques Terken, and Jun Hu. "Driver-to-Driver Communication on the Highway: What Drivers Want." In Lecture Notes in Computer Science, 315–27. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-14112-1_25.

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Parnell, Katie J., Neville A. Stanton, and Katherine L. Plant. "Introduction." In Driver Distraction, 1–6. Boca Raton : Taylor & Francis, a CRC title, part of the Taylor &: CRC Press, 2018. http://dx.doi.org/10.1201/9780429466809-1.

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Parnell, Katie J., Neville A. Stanton, and Katherine L. Plant. "Conclusions." In Driver Distraction, 195–206. Boca Raton : Taylor & Francis, a CRC title, part of the Taylor &: CRC Press, 2018. http://dx.doi.org/10.1201/9780429466809-10.

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Parnell, Katie J., Neville A. Stanton, and Katherine L. Plant. "Driver Distraction, Technology and the Sociotechnical Systems Approach." In Driver Distraction, 7–18. Boca Raton : Taylor & Francis, a CRC title, part of the Taylor &: CRC Press, 2018. http://dx.doi.org/10.1201/9780429466809-2.

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Parnell, Katie J., Neville A. Stanton, and Katherine L. Plant. "Driver Distraction Methodology." In Driver Distraction, 19–40. Boca Raton : Taylor & Francis, a CRC title, part of the Taylor &: CRC Press, 2018. http://dx.doi.org/10.1201/9780429466809-3.

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Parnell, Katie J., Neville A. Stanton, and Katherine L. Plant. "Exploring the Mechanisms of Driver Distraction." In Driver Distraction, 41–62. Boca Raton : Taylor & Francis, a CRC title, part of the Taylor &: CRC Press, 2018. http://dx.doi.org/10.1201/9780429466809-4.

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Parnell, Katie J., Neville A. Stanton, and Katherine L. Plant. "What’s the Law Got to Do with It? Legislation Regarding In-Vehicle Technology Use and Its Impact on Driver Distraction." In Driver Distraction, 63–88. Boca Raton : Taylor & Francis, a CRC title, part of the Taylor &: CRC Press, 2018. http://dx.doi.org/10.1201/9780429466809-5.

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Conference papers on the topic "The driver"

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EL Rashidy, Rawia Ahmed Hassan. "DRIVER COMPETENCE PERFORMANCE INDICATORS USING OTMR." In CIT2016. Congreso de Ingeniería del Transporte. Valencia: Universitat Politècnica València, 2016. http://dx.doi.org/10.4995/cit2016.2016.3417.

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The current practice for assessing driver competence performance is in-cab riding by driver managers. However, this paper investigates whether real-world driving data extracted from on-train monitoring recorders data (OTMR) can be used to assess the driver performance. A number of indicators were used to evaluate the drivers’ performance. These include: their use of the emergency bypass switch, the driver's reminder appliance as well as the driver’s reaction time. A study case illustrated the applicability of OTMR data to estimate the proposed indicators, which suggests that the indicators can be useful in the driver management system in addition to the current indicators. Furthermore, the proposed indicators could be used to tailor the driver training schemes up to their individual needs and evaluate their effectiveness. They could even be used for improving driver competence performance and reducing crash involvement by revealing potentially detrimental driving performance.DOI: http://dx.doi.org/10.4995/CIT2016.2016.3417
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Brandsness, M., and I. Sealy. "Drive-Through Driver Training." In SPE International Conference on Health, Safety, and Environment in Oil and Gas Exploration and Production. Society of Petroleum Engineers, 2004. http://dx.doi.org/10.2118/86833-ms.

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Lamas, Raphael, Catherine Harvey, Gary Burnett, and Sue Cobb. "A Driver-to-Driver Communication Device to Improve Drivers' Interaction." In the 6th International Conference. New York, New York, USA: ACM Press, 2014. http://dx.doi.org/10.1145/2667239.2667427.

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Hidajat, Taofik, Agung Hendra Kusuma, and Achmad Sulchan. "Gamification in Ride-Hailing: What Drives a Driver to Drive." In The 3rd International Conference on Banking, Accounting, Management and Economics (ICOBAME 2020). Paris, France: Atlantis Press, 2020. http://dx.doi.org/10.2991/aebmr.k.210311.047.

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Samper Mejia, Juan Pablo, Paul A. Theodosis, and J. Christian Gerdes. "Using a Path-Fitting Algorithm to Analyze the Racing Techniques of a Skilled Driver." In ASME 2013 Dynamic Systems and Control Conference. American Society of Mechanical Engineers, 2013. http://dx.doi.org/10.1115/dscc2013-4106.

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Racecar drivers are skilled at tracking a path, avoiding accidents, and controlling their vehicles at the limits of handling. Better understanding of how a skilled driver selects and drives a racing line, could potentially lead to a new technique for obstacle avoidance. To investigate this, the characteristics of a racecar driver’s line must be captured mathematically. This paper describes an algorithm for fitting a path to the GPS data of a driver’s racing line. A family of path primitives composed of straights, clothoids, and constant radius arcs are used to describe the racing line. The fitted paths provide a method for analyzing racing lines and the different techniques used by skilled drivers to navigate the track.
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Taher, Matt, Dragan Ristanovic, Cyrus Meher-Homji, and Pradeep Pillai. "Matching of Synchronous Motors and Centrifugal Compressors: Oil and Gas Industry Practice." In ASME Turbo Expo 2020: Turbomachinery Technical Conference and Exposition. American Society of Mechanical Engineers, 2020. http://dx.doi.org/10.1115/gt2020-15643.

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Abstract Synchronous motor driven centrifugal compressors are widely used in the oil and gas industry. In evaluating the optimum selection of synchronous motor drivers for centrifugal compressors, it is important to understand the factors influencing a proper match for a centrifugal compressor and its synchronous motor driver. The buyer should specify process requirements and define possible operating scenarios for the entire life of the motor driven centrifugal compressor train. The compressor designer will use the buyer-specified process conditions to model the aerothermodynamic behavior of the compressor and characterize its performance. Performance, controllability, starting capabilities as well as the optimum power margin required for a future-oriented design must also be considered. This paper reviews the criteria for evaluating the optimal combination of a centrifugal compressor and its synchronous motor driver as an integral package. It also addresses API standard requirements on synchronous motor driven centrifugal compressors. Design considerations for optimal selection and proper sizing of compressor drivers include large starting torque requirements to enable compressor start from settle-out conditions and to prevent flaring are addressed. Start-up capabilities of the motor driver can significantly impact the reliability and operability of the compressor train. API 617 on centrifugal compressors refers to API 546 for synchronous motor drivers. In this paper, requirements of API 617 and 546 are reviewed and several important design and sizing requirements are presented. In the effort to optimize plant design, and maintain the performance requirements, the paper discusses optimization options, such as direct on-line starting method to explore the motor rating limits, and the use of synchronous motors for power factor correction to eliminate or reduce the need for reactive power compensation by capacitor banks. This paper presents a novel approach to show constant reactive power lines on traditional V curves. It also complements capability curves of synchronous motors with lines of constant efficiency. The paper discusses variable frequency drive options currently used for synchronous motors in compressor applications. The paper addresses the available variable frequency drive types, their impact on the electrical grid, and motor design considerations with a view to summarizing factors important to the selection of variable frequency drives.
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Hardy, A. F., and J. D. Hill. "Creating Scanning Pattern Maps of Driver Fixations During Hazards." In 2013 Joint Rail Conference. American Society of Mechanical Engineers, 2013. http://dx.doi.org/10.1115/jrc2013-2459.

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Previous research has shown that drivers only look for a train about 33% of the time at railroad crossings. With driver inattention composing a large proportion of reported accidents, there exists a need to be able to quantify exactly what a driver fixates on over the course of a drive. This paper presents a method using simulated railroad situations as a hazard-medium to create driving scan pattern maps over the course of a long drive.
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Chinta, Kiran Kumar, and Fred Barez. "Driver Distraction Detection and Recognition." In ASME 2020 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2020. http://dx.doi.org/10.1115/imece2020-24474.

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Abstract Statistics have shown that the main reason for traffic accidents is human error. Modern vehicles are equipped to protect occupants in the event of a crash. The latest advanced vehicles come with driver behavior monitoring systems in recent years, and many have been proven to be effective systems in the prevention of accidents. However, these systems do not provide a complete solution and can only detect driver fatigue or driver distraction. This project aims to build an AI model for sensing the distraction of drivers and identifying the kind of distraction using the Kinect sensor and the Brio camera and reorient driver’s attention on driving. For this, the system is divided into three sub-segments; calling arm position (arms up or down, arms right or left), facial expressions (blinking and mouth), and head orientation. Each segment develops important info for gauging the distraction of a driver based on the depth mapping of data and color from the Kinect sensor and Brio camera respectively. Testing on a driving simulator is completed on 4 different drivers of diverse ethnicity, sex, and age along with over 240 mins of recorded material. Since all the segments were recorded and prepared separately, they can further be taken to build different outcomes and can be implemented for real car systems.
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Zheng, Yu, Jing Yuan, Wenlei Xie, Xing Xie, and Guangzhong Sun. "Drive Smartly as a Taxi Driver." In Trusted Computing (UIC/ATC). IEEE, 2010. http://dx.doi.org/10.1109/uic-atc.2010.19.

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"Attention of Driver during Simulated Drive." In International Conference on Health Informatics. SCITEPRESS - Science and and Technology Publications, 2014. http://dx.doi.org/10.5220/0004934905430550.

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Reports on the topic "The driver"

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Kulhandjian, Hovannes. Detecting Driver Drowsiness with Multi-Sensor Data Fusion Combined with Machine Learning. Mineta Transportation Institute, September 2021. http://dx.doi.org/10.31979/mti.2021.2015.

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In this research work, we develop a drowsy driver detection system through the application of visual and radar sensors combined with machine learning. The system concept was derived from the desire to achieve a high level of driver safety through the prevention of potentially fatal accidents involving drowsy drivers. According to the National Highway Traffic Safety Administration, drowsy driving resulted in 50,000 injuries across 91,000 police-reported accidents, and a death toll of nearly 800 in 2017. The objective of this research work is to provide a working prototype of Advanced Driver Assistance Systems that can be installed in present-day vehicles. By integrating two modes of visual surveillance to examine a biometric expression of drowsiness, a camera and a micro-Doppler radar sensor, our system offers high reliability over 95% in the accuracy of its drowsy driver detection capabilities. The camera is used to monitor the driver’s eyes, mouth and head movement and recognize when a discrepancy occurs in the driver's blinking pattern, yawning incidence, and/or head drop, thereby signaling that the driver may be experiencing fatigue or drowsiness. The micro-Doppler sensor allows the driver's head movement to be captured both during the day and at night. Through data fusion and deep learning, the ability to quickly analyze and classify a driver's behavior under various conditions such as lighting, pose-variation, and facial expression in a real-time monitoring system is achieved.
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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, October 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 addition to AV lane width, the experimental design took into consideration AV headway, gender, and right lane traffic to investigate possible interaction effects. The results showed no significant differences in the speed and mental effort of drivers while indicating significant differences in lane positioning. Although the overall effect of AV lane width was not significant, there were some significant interaction effects between lane width and other factors (i.e., driver gender and presence of traffic on the next regular lane to the right). Across all the significant interactions, there was no case in which those factors stayed constant while AV lane width changed between the groups, indicating that the significant difference stemmed from the other factors rather than the lane width. However, the trend observed was that drivers driving next to the 12-ft lane had better lane centering compared to the 9ft lane. The analysis also showed that while in general female drivers tended to drive further away from the 9-ft lane and performed worse in terms of lane centering, they performed better than male drivers when right-lane traffic was present. This study contributes to understanding the behavioral impacts of infrastructure adaptation to AVs on non-AV drivers.
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Conroy, Sarah. Driver Preparedness: A 2014 Survey of Drivers Age 30+. AARP Research, November 2014. http://dx.doi.org/10.26419/res.00090.001.

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Kuriyagawa, Yukiyo, and Ichiro Kageyama. Surveillance Study on Driver Support System for Aged Drivers. Warrendale, PA: SAE International, September 2005. http://dx.doi.org/10.4271/2005-08-0427.

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Conroy, Sarah. Driver Preparedness: A 2014 Survey of Drivers Age 30+: Infographic. AARP Research, November 2014. http://dx.doi.org/10.26419/res.00090.002.

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Chen, Stanley, Yaobin Chen, Renran Tian, Lingxi Li, Donglin Liu, Jue Zhou, and Dan Shen. Alternate Interchange Signing Study for Indiana Highways. Purdue University, 2022. http://dx.doi.org/10.5703/1288284317439.

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The main objectives of this research were to (1) understand signing issues from the perspective of drivers and (2) develop recommendations for improving interchange signing in Indiana to aid driver understanding and increase the safety and efficiency of highway traffic operations. An online survey with specific questions was designed and distributed through email, social media, online newspapers, and a survey company with the goal of better understanding driver thinking when approaching decision-making areas on the interstate. The analysis of the survey results revealed the following. •Drivers usually do not know the interchange types as they approach an interchange on the freeway. •Drivers are most interested in which lanes they should be in when approaching an interchange, even in advance of typical signing locations. •Drivers do not like signs that require cognitive work since it will delay their driving decision by creating uncertainty. •Different drivers need different types of information from signs, such as cardinal direction, destination name, road name, and lane assignments. Therefore, a perfect sign for one driver may be confusing or information overload for another driver. •In some instances, a driver who is familiar with the area is confused by the signs because the sign information contradicts the driver’s knowledge.
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Ehst, D. A., K. Jr Evans, D. R. Mikkelsen, D. W. Ignat, and T. K. Mau. Noninductive current drive for INTOR: A comparison of four driver options. Office of Scientific and Technical Information (OSTI), January 1987. http://dx.doi.org/10.2172/6919458.

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G.W. Foster, W. Chou and E. Malamud. Proton Driver Study II. Office of Scientific and Technical Information (OSTI), July 2002. http://dx.doi.org/10.2172/797300.

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Campbell, R. C., C. H. Campbell, C. M. Knerr, and S. L. Burroughs. M1 Tank Driver Tests. Fort Belvoir, VA: Defense Technical Information Center, February 1985. http://dx.doi.org/10.21236/ada156803.

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Batavia, Parag H. Driver Adaptive Warning Systems. Fort Belvoir, VA: Defense Technical Information Center, March 1998. http://dx.doi.org/10.21236/ada594468.

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