Modifications of Driver Attention Post-distraction: A Detection Response Task Study

Winzer, Oliver M.; Conti, Antonia S.; Olaverri-Monreal, Cristina; Bengler, Klaus

doi:10.1007/978-3-319-58481-2_31

Cited by 7 publications

(4 citation statements)

References 11 publications

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“…Delaying engagement in secondary tasks until the vehicle is stationary at traffic lights, while likely to reduce risk, is far from a solution to distracted driving. Indeed, research suggests that residual interference from distracting tasks may persist well beyond task completion [19, 20]. It is also noteworthy that several cases were observed in the current study where drivers did not disengage from phone tasks that were initiated when stationary once the traffic lights had turned green.…”

Section: Discussionmentioning

confidence: 47%

What contextual and demographic factors predict drivers’ decision to engage in secondary tasks?

Young

Osborne

Charlton

et al. 2019

IET Intelligent Transport Systems

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Section: Discussionmentioning

confidence: 47%

What contextual and demographic factors predict drivers’ decision to engage in secondary tasks?

Young

Osborne

Charlton

et al. 2019

IET Intelligent Transport Systems

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“…As described in [4] when acting as monitor of an automated system, a driver's response time and intervention after having realized a problem has occurred can be critical. Studies have confirmed that driver reaction time (RT) to visual stimuli did not return to its baseline performance level immediately after a period of distraction [5,6]. Therefore, RT depends on whether the driver has been engaged in secondary tasks as well as the type of these tasks.…”

Section: Introductionmentioning

confidence: 99%

“…Figures 5,6 and 7 depict respectively the deceleration time, reaction time distribution and steering wheel angle over scenarios and subjects. Results regarding the reaction time, collision, steering wheel angle and deceleration in all scenarios are illustrated in Figure8.For the number of collisions variable, the results fell between the baseline and scenario 1 situation where χ 2 (1, N = 24) = 2.083.The two-tailed p-value was 0.1489 and therefore, by conventional criteria, this difference was considered not statistically significant.Similarly, for scenarios 1 and 2 no statistically significant differences applied, χ 2 (1, N = 24) = 3.2 with a p-value of 0.0736.…”

mentioning

confidence: 99%

Automated Driving: Interactive Automation Control System to Enhance Situational Awareness in Conditional Automation

Olaverri-Monreal

Kumar

Díaz-Álvarez

2018

2018 IEEE Intelligent Vehicles Symposium (IV)

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Human drivers in autonomous vehicles will monitor the system and be ready to resume control in ambiguous or emergency situations. As a driver's reaction time to intervene after having realized a problem has occurred can be critical, we present the Interactive Automation Control System (IACS) to assist the driver when their takeover is required. The system displays manual or automated mode in an unobstrusive location in the vehicle, signaling when a Take Over Request (TOR) is necessary. We evaluate the system's performance during a situation in which the automation has not been defined to operate and study its impact on the overall driving performance, specifically the driver's reaction time to a TOR. Results showed significant improvements in driving performance with the proposed system. Both the response time to the TOR and the number of collisions decreased when the IACS was activated. Subjective ratings of the system regarding its performance showed high satisfaction levels.

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“…The reaction time (RT) to a TOR after the driver has been involved in a non-driving related task (NDRT) does not return to its baseline performance level immediately after the distraction. This means that drivers can be distracted up to 27 s after finishing a highly distracting task and up to 15 s after interacting with a moderately distracting system [17], and secondary tasks may affect the driver even after a task/distraction phase has been completed [18].…”

mentioning

confidence: 99%

Automated Driving: A Literature Review of the Take over Request in Conditional Automation

Morales-Alvarez

Sipele

Léberon³

et al. 2020

Electronics

Self Cite

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In conditional automation (level 3), human drivers can hand over the Driving Dynamic Task (DDT) to the Automated Driving System (ADS) and only be ready to resume control in emergency situations, allowing them to be engaged in non-driving related tasks (NDRT) whilst the vehicle operates within its Operational Design Domain (ODD). Outside the ODD, a safe transition process from the ADS engaged mode to manual driving should be initiated by the system through the issue of an appropriate Take Over Request (TOR). In this case, the driver’s state plays a fundamental role, as a low attention level might increase driver reaction time to take over control of the vehicle. This paper summarizes and analyzes previously published works in the field of conditional automation and the TOR process. It introduces the topic in the appropriate context describing as well a variety of concerns that are associated with the TOR. It also provides theoretical foundations on implemented designs, and report on concrete examples that are targeted towards designers and the general public. Moreover, it compiles guidelines and standards related to automation in driving and highlights the research gaps that need to be addressed in future research, discussing also approaches and limitations and providing conclusions.

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Modifications of Driver Attention Post-distraction: A Detection Response Task Study

Cited by 7 publications

References 11 publications

What contextual and demographic factors predict drivers’ decision to engage in secondary tasks?

What contextual and demographic factors predict drivers’ decision to engage in secondary tasks?

Automated Driving: Interactive Automation Control System to Enhance Situational Awareness in Conditional Automation

Automated Driving: A Literature Review of the Take over Request in Conditional Automation

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