Cooperative warning systems: The impact of false and unnecessary alarms on drivers’ compliance

Naujoks, Frederik; Kiesel, Andrea; Neukum, Alexandra

doi:10.1016/j.aap.2016.09.009

Cited by 57 publications

(22 citation statements)

References 46 publications

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“…Tijerina et al (2017) showed that a 'cry wolf' effect occurs if the uncertainty notification was issued frequently without an actual need for a response. Similarly, a study evaluating the effects of advisory warning systems in automated driving showed that false alarms caused a cry-wolf effect (Naujoks, Kiesel, and Neukum (2016). In the cry-wolf effect, Type I errors (false alarms) cause a reduction in reliance.…”

Section: Monitoring Requests and Uncertainty Presentationmentioning

confidence: 99%

Beyond mere take-over requests: The effects of monitoring requests on driver attention, take-over performance, and acceptance

Zhang

Feldhütter

et al. 2019

Transportation Research Part F: Traffic Psychology and Behaviou

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In conditionally automated driving, drivers do not have to monitor the road, whereas in partially automated driving, drivers have to monitor the road permanently. We evaluated a dynamic allocation of monitoring tasks to human and automation by providing a monitoring request (MR) before a possible takeover request (TOR), with the aim to better prepare drivers to take over safely and efficiently. In a simulator-based study, an MR+TOR condition was compared with a TOR-only condition using a within-subject design with 41 participants. In the MR+TOR condition, an MR was triggered 12 s before a zebra crossing, and a TOR was provided 7 s after the MR onset if pedestrians crossing the road were detected. In the TOR-only condition, a TOR was provided 5 s before the vehicle would collide with a pedestrian if the participant did not intervene. Participants were instructed to perform a self-paced visual-motor non-driving task during automated driving. Eye tracking results showed that participants in the MR+TOR condition responded to the MR by looking at the driving environment. They also exhibited better takeover performance, with a shorter response time to the TOR and a longer minimum time to collision as compared to the TOR-only condition. Subjective evaluations also showed advantages of the MR: participants reported lower workload, higher acceptance, and higher trust in the MR+TOR condition as compared to the TOR-only condition. Participants' reliance on automation was tested in a third drive (MR-only condition), where automation failed to provide a TOR after an MR. The MR-only condition resulted in later responses (and errors of omission) as compared to the MR+TOR condition. It is concluded that MRs have the potential to increase safety and acceptance of automated driving as compared to systems only providing TORs. Drivers' trust calibration and reliance on automation will need further investigation.

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Section: Monitoring Requests and Uncertainty Presentationmentioning

confidence: 99%

Beyond mere take-over requests: The effects of monitoring requests on driver attention, take-over performance, and acceptance

Zhang

Feldhütter

et al. 2019

Transportation Research Part F: Traffic Psychology and Behaviou

View full text Add to dashboard Cite

show abstract

“…Startling the driver by the use of inappropriately urgent HMI messages might inhibit these preparatory processes and worsen NDRT performance [95]. Consequently, it could be argued that non-urgent status information should be unimodal (e.g., solely visual) and urgent information multimodal [64,104]. However, modality is not the only way to convey urgency.…”

Section: Recommendation 1: Adapt the Urgency Of Messagesmentioning

confidence: 99%

“…However, modality is not the only way to convey urgency. More detailed information and further examples of how to design HMI messages with different urgency (e.g., by semantic content [3,5], intonation [49] or loudness) can be found both in literature on driver warnings [5,47,64,78,80] and take-over requests [65,79].…”

Section: Recommendation 1: Adapt the Urgency Of Messagesmentioning

confidence: 99%

The Importance of Interruption Management for Usefulness and Acceptance of Automated Driving

Naujoks

Wiedemann

Schömig

2017

Proceedings of the 9th International Conference on Automotive User Interfaces and Interactive Vehicular Applications

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To increase the safety in use of automated vehicles, Human Factors research has focused primarily on driver performance during takeover situations. However, surveys on public opinion on automated vehicles still report a lack of acceptance of the technology. In this review, we give an overview on how taking the changed role of the driver into account when designing Human-Machine Interfaces (HMI) of automated vehicles could increase the usefulness of the technology, which might in turn result in increased public acceptance. We propose that balancing the driver's need of being informed about the automated vehicle's status, actions and intentions with the desire to engage in non-driving related tasks (NDRTs) is likely to play an important role in this process.

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“…On the other hand, one of the most critical factors of the SSMs employed in the FCWS and EBS is driver's compliance, which is highly correlated with the system reliability [17]. For example, a conservative SSM designed particularly for passive drivers will give frequent alerts to aggressive drivers in most cases.…”

Section: Introductionmentioning

confidence: 99%

A Comparison Analysis of Surrogate Safety Measures with Car-Following Perspectives for Advanced Driver Assistance System

Tak

Kim

Lee

et al. 2018

Journal of Advanced Transportation

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Surrogate Safety Measure (SSM) is one of the most widely used methods for identifying future threats, such as rear-end collision. Various SSMs have been proposed for the application of Advanced Driver Assistance Systems (ADAS), including Forward Collision Warning System (FCWS) and Emergency Braking System (EBS). The existing SSMs have been mainly used for assessing criticality of a certain traffic situation or detecting critical actions, such as severe braking maneuvers and jerking before an accident. The ADAS shows different warning signals or movements from drivers’ driving behaviours depending on the SSM employed in the system, which may lead to low reliability and low satisfaction. In order to explore the characteristics of existing SSMs in terms of human driving behaviours, this study analyzes collision risks estimated by three different SSMs, including Time-To-Collision (TTC), Stopping Headway Distance (SHD), and Deceleration-based Surrogate Safety Measure (DSSM), based on two different car-following theories, such as action point model and asymmetric driving behaviour model. The results show that the estimated collision risks of the TTC and SHD only partially match the pattern of human driving behaviour. Furthermore, the TTC and SHD overestimate the collision risk in deceleration process, particularly when the subject vehicle is faster than its preceding vehicle. On the other hand, the DSSM shows well-matched results to the pattern of the human driving behaviour. It well represents the collision risk even when the preceding vehicle moves faster than the follower one. Moreover, unlike other SSMs, the DSSM shows a balanced performance to estimate the collision risk in both deceleration and acceleration phase. These research findings suggest that the DSSM has a great potential to enhance the driver’s compliance to the ADAS, since it can reflect how the driver perceives the collision risks according to the driving behaviours in the car-following situation.

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Cooperative warning systems: The impact of false and unnecessary alarms on drivers’ compliance

Cited by 57 publications

References 46 publications

Beyond mere take-over requests: The effects of monitoring requests on driver attention, take-over performance, and acceptance

Beyond mere take-over requests: The effects of monitoring requests on driver attention, take-over performance, and acceptance

The Importance of Interruption Management for Usefulness and Acceptance of Automated Driving

A Comparison Analysis of Surrogate Safety Measures with Car-Following Perspectives for Advanced Driver Assistance System

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