| 3. |
- Strand, Niklas, 1981-, et al.
(författare)
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Report on simulator test results and driver acceptance of PROSPECT functions
- 2019
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Rapport (övrigt vetenskapligt/konstnärligt)abstract
- The process of developing new automotive systems includes various testing cycles to assure a save operation in traffic. Physical system testing on test tracks is very important for this purpose, but rather expensive and might only become possible in later stages of the development process. Using a virtual simulation environment offers a safe possibility of testing new systems in early stages of development. Aditionally, driver-in-the-loop tests at test track and in a virtual simulator make it possible to evaluate driver reaction and potential acceptance by the future users of those systems. Within PROSPECT the new functions are investigated under various aspects in several simulator studies and test track studies.This deliverable D7.3 gives detailed information of conduction and results of the each study. Three studies focus exclusively on the for Vulnerable Road Users (VRUs) specifically dangerous urban intersection scenarios. The first of those studies examines the driver behaviour in a turning situation when a byciclist might be crossing. The second study, which provides an initial step in this line of research, analyzed the acceptance of issued forward collision warning times. In the third study acceptance of an intersection assist autonomous emergency braking systems was tested regarding the acceptance of potential buyers.Two studies focused on longitudinal scenarios. Both studies followed the same design, but one was conducted on a test track and the other one in a simulator. The main objective was to investigate drivers reactions to FCW warnings and Active Steering interventions in critical VRU scenarios in case of a distraction of the driver.
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| 4. |
- Åkerberg Boda, Christian-Nils, 1989, et al.
(författare)
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Modelling discomfort: How do drivers feel when cyclists cross their path?
- 2020
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Ingår i: Accident Analysis and Prevention. - : Elsevier BV. - 0001-4575. ; 146
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Tidskriftsartikel (refereegranskat)abstract
- Introduction: Even as worldwide interest in bicycling continues to grow, cyclists constitute a large part of road fatalities. A major part of the fatalities occurs when cyclists cross a vehicle path. Active safety systems and automated driving systems may already account for these interactions in their control algorithms. However, the driver behaviour models that these systems use may not be optimal in terms of driver acceptance. If the systems could estimate driver discomfort, their acceptance might be improved. Method: This study investigated the degree of discomfort experienced by drivers when cyclists crossed their travel path. Participants were instructed to drive through an intersection in a fixed-base simulator or on a test track, following the same experimental protocol. The effects of demographic variables (age, gender, driving frequency, and yearly mileage), controlled variables (car speed, bicycle speed, and bicycle-car configuration), and a visual cue (car’s time-to-arrival at the intersection when the bicycle appears; TTAvis) on self-reported discomfort were analysed using cumulative link mixed models (CLMM). Results: Results showed that demographic variables had a significant effect on the discomfort felt by drivers—and could explain the variability observed between drivers. Across both experimental environments, the controlled variables were shown to significantly influence discomfort. TTAvis was shown to have a significant effect on discomfort as well; the closer to zero TTAvis was (i.e., the more critical the situation), the more likely the driver red great discomfort. The prediction accuracies of the CLMM with controlled variables and the CLMM with the visual cue were similar, with an average accuracy between 40 and 50%. Surprise trials in the simulator experiment, in which the bicycle appeared unexpectedly, improved the prediction accuracy of the models, more notably the CLMM including TTAvis. Conclusions: The results suggest that the discomfort was mainly driven by the visual cue rather than the deceleration cues. Thus, it is suggested that an algorithm that estimates driver discomfort be included in active safety systems and autonomous driving systems. The CLMM including TTAvis was presented as a potential candidate to serve this purpose.
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