Automated-Manual Transitions: Human Capabilities and Adaptive Cruise Control (original) (raw)
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Transportation Research Record: Journal of the Transportation Research Board, 2017
Automated vehicles and driving assistance systems such as adaptive cruise control (ACC) are expected to reduce traffic congestion, accidents, and levels of emissions. Field operational tests have found that drivers may prefer to deactivate ACC in dense traffic flow conditions and before changing lanes. Despite the potential effects of these control transitions on traffic flow efficiency and safety, most mathematical models evaluating the impact of ACC do not adequately represent that process. This research aimed to identify the main factors influencing drivers’ choice to resume manual control. A mixed logit model that predicted the choice to deactivate the system or overrule it by pressing the gas pedal was estimated. The data set was collected in an on-road experiment in which 23 participants drove a research vehicle equipped with full-range ACC on a 35.5-km freeway in Munich, Germany, during peak hours. The results reveal that drivers were more likely to deactivate the ACC and res...
Adaptive Cruise Control: A Categorical Imperative to the New World in 21ST Century?
Control Theory and Informatics, 2012
With the new millennium upon us, vehicle automation devices such as Adaptive Cruise Control are being offered by major motor manufactures. Over the last five years, the development of these systems has been reflected by the increasing number of publications in technical journals. However, there does not seem to have been a similar effort in the ergonomics literature devoted to the effects of vehicle automation on driving performance. The current paper investigates whether driving performance with automation changes across levels of driver skill. This issue raises substantial practical concerns. As vehicle automation becomes commonplace, the demographics of the driving population which have access to it will become increasingly variable. Therefore, the results are interpreted with respect to issues of litigation and training for inexperienced drivers with automation.
11.[1-4]Adaptive Cruise Control A Categorical Imperative to the New World in 21ST Century
With the new millennium upon us, vehicle automation devices such as Adaptive Cruise Control are being offered by major motor manufactures. Over the last five years, the development of these systems has been reflected by the increasing number of publications in technical journals. However, there does not seem to have been a similar effort in the ergonomics literature devoted to the effects of vehicle automation on driving performance. The current paper investigates whether driving performance with automation changes across levels of driver skill. This issue raises substantial practical concerns. As vehicle automation becomes commonplace, the demographics of the driving population which have access to it will become increasingly variable. Therefore, the results are interpreted with respect to issues of litigation and training for inexperienced drivers with automation.
2017
This report presents human factors research to examine the effects of cooperative adaptive cruise control (CACC) on driver performance in a variety of situations. It summarizes driving simulator experiments in which the driver was required to drive in a stream of vehicles. Participants experienced a vehicle merge in front of them as well as an emergency event that required driver intervention. The participants' preferred following time gap did not significantly affect collision avoidance. However, those participants following at shorter distances were more likely to intervene more rapidly that those following at a far distance. These findings support the idea that performance depends more on overall CACC following distance settings than with drivers' personal preferences. This will allow CACC systems to implement a single following distance gap (or set of gaps based on vehicle physics). The results show that it is critical that drivers receive clear alerts when it is necessary to take over control of the vehicle. Without such measures, it is possible that CACC implementation may not result in improved roadway safety. This report should be useful to transportation professionals, State transportation departments, and researchers interested in the effects of automation on driver behavior and performance.
Theoretical Issues in Ergonomics Science, 2019
Since returning to academia and gaining his PhD in 2013, David has been involved in a broad range of industry, UK and EU funded projects primarily concerning the design, evaluation and acceptance of novel and emerging in-vehicle interfaces and systems for both road and rail transport, and the development of experimental techniques to support this work. Professor Gary Burnett holds a chair in Transport Human Factors within the Faculty of Engineering at the University of Nottingham. He has over 25 years' experience in Human Factors research and development relating to advanced technology within road-based vehicles. His work addresses key safety, usability, and acceptance issues for advanced in-car systems and Human-Machine Interfaces (HMIs), and he is particularly concerned with the assessment of driver distraction. Rebecca Matthias works at Jaguar Land Rover in the Research Department. As a Human Factors Group Leader in Capability Research, Rebecca's work focuses on the human factors aspects of automated driving, in particularly occupant interaction with the highly automated vehicle and vehicle behaviour. Simon Thompson works at Jaguar Land Rover in the Research Department. As a Human Machine Interface Specialist, Simon focuses on technical aspects such as engineering, human factors, and psychological factors. Simon is responsible for research projects and activities including: designing system-driver interfaces; providing HMI and ergonomics guidance to engineers; competitor benchmarking and assessment; designing, organising and conducting user trials; reviewing and creating internal HMI standards; and developing technology and feature HMI strategies. Lee Skrypchuk works at Jaguar Land Rover in the Research Department. As a Human Machine Interface Technical Specialist, Lee focuses on technical aspects such as engineering, human factors, and psychological factors. Lee has led projects including head-up display, driver monitoring, and gesture control, and holds responsibility for research roadmaps in this area. Getting the Driver back into the Loop: The Quality of manual Vehicle Control following long and short non-critical Transfer-of-control Requests: TI:NS Specific vehicle automation use-cases such as traffic jams will be the first level 3 functions on the market. When the 'traffic jam pilot' nears its limits in noncritical situations, control needs to be handed back to the driver, enabling appropriate situation awareness (SA) and vehicle handling. According to previous research, operational vehicle stabilisation can be achieved within a transfer-of-control (TOC) of a few seconds in simple traffic environments, but tactical level decisions benefit from longer handover times. To date, the effects of non-critical TOCs have not been studied using set time frames. To investigate the impact of short (unplanned, 5 seconds) and long (planned, 50 seconds) TOC requests, while playing/not playing an engaging tablet game, a simulator experiment was conducted with 16 participants. Comparisons of the 60-secondperiod of manual driving following automation suggest better longitudinal vehicle control as well as more appropriate SA following the long TOC request, and automation periods without the game. However, following no engaging game, lateral performance was worse during the first 10 seconds of manual driving. Control-level visual search patterns did not change with TOC time or the game. Future research needs to consider support for drivers' SA maintenance and readiness to drive following high automation.
Behavioral adaptation to adaptive cruise control
PsycEXTRA Dataset
This test-track study assessed whether adaptive cruise control (ACC) induces behavioural adaptation in drivers. Eighteen experienced drivers drove a test vehicle while following a lead vehicle in three counterbalanced conditions: No ACC (self-maintained average headway of 2 s), ACC-Short (headway of 1.4 s) and ACC-Long (headway of 2.4 s). Results demonstrate that ACC can induce behavioural adaptation in drivers in potentially safety-critical ways. Compared to driving unsupported, participants located significantly more items per minute on a secondary task when using ACC, while their response times to a hazard detection task increased. This effect was particularly pronounced in those scoring high on a sensation-seeking scale. Using ACC resulted in significantly more lane position variability, an effect that was also more pronounced in high sensation-seekers. DriversÕ trust in ACC increased significantly after using the system, and these ratings did not change despite a simulated failure of the ACC system during the ACC-Long condition. Response time to the simulated ACC failure was related to a driverÕs locus of control: Externals intervened more slowly than Internals. All drivers reported relying on the ACC system to keep their vehicle at a safe distance from the lead vehicle. Results are consistent with similar research conducted on lane departure warning systems. Driver awareness training is a potential preventive strategy that could minimize the behavioural adaptation associated with novel in-vehicle systems such as ACC.
Behavioural adaptation to adaptive cruise control (ACC): implications for preventive strategies
Transportation Research Part F: Traffic Psychology and Behaviour, 2004
This test-track study assessed whether adaptive cruise control (ACC) induces behavioural adaptation in drivers. Eighteen experienced drivers drove a test vehicle while following a lead vehicle in three counterbalanced conditions: No ACC (self-maintained average headway of 2 s), ACC-Short (headway of 1.4 s) and ACC-Long (headway of 2.4 s). Results demonstrate that ACC can induce behavioural adaptation in drivers in potentially safety-critical ways. Compared to driving unsupported, participants located significantly more items per minute on a secondary task when using ACC, while their response times to a hazard detection task increased. This effect was particularly pronounced in those scoring high on a sensation-seeking scale. Using ACC resulted in significantly more lane position variability, an effect that was also more pronounced in high sensation-seekers. DriversÕ trust in ACC increased significantly after using the system, and these ratings did not change despite a simulated failure of the ACC system during the ACC-Long condition. Response time to the simulated ACC failure was related to a driverÕs locus of control: Externals intervened more slowly than Internals. All drivers reported relying on the ACC system to keep their vehicle at a safe distance from the lead vehicle. Results are consistent with similar research conducted on lane departure warning systems. Driver awareness training is a potential preventive strategy that could minimize the behavioural adaptation associated with novel in-vehicle systems such as ACC.
Transition to manual: Driver behaviour when resuming control from a highly automated vehicle
Transportation Research Part F: Traffic Psychology and Behaviour, 2014
A driving simulator study was designed to investigate drivers' ability to resume control from a highly automated vehicle in two conditions: (i) when automation was switched off and manual control was required at a system-based, regular interval and (ii) when transition to manual was based on the length of time drivers were looking away from the road ahead. In addition to studying the time it took drivers to successfully resume control from the automated system, eye tracking data were used to observe visual attention to the surrounding environment and the pattern of drivers' eye fixations as manual control was resumed in the two conditions. Results showed that drivers' pattern of eye movement fixations remained variable for some time after automation was switched off, if disengagement was actually based on drivers' distractions away from the road ahead. When disengagement was more predictable and system-based, drivers' attention towards the road centre was higher and more stable. Following a lag of around 10 s, drivers' lateral control of driving and steering corrections (as measured by SDLP and high frequency component of steering, respectively) were more stable when transition to manual control was predictable and based on a fixed time. Whether automation transition to manual was based on a fixed or variable interval, it took drivers around 35-40 s to stabilise their lateral control of the vehicle. The results of this study indicate that if drivers are out of the loop due to control of the vehicle in a limited self-driving situation (Level 3 automation), their ability to regain control of the vehicle is better if they are expecting automation to be switched off. As regular disengagement of automation is not a particularly practical method for keeping drivers in the loop, future research should consider how to best inform drivers of their obligation to resume control of driving from an automated system.