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Is the automated vehicle “aware” of the pedestrian? Examining driving behavior adaptation as a cue to inform the passenger of a potential hazard

GND
1250354005
ORCID
0000-0002-3081-3163
Affiliation/Institute
Institut für Psychologie
Stange, Vanessa;
GND
1250359422
ORCID
0000-0001-8913-6980
Affiliation/Institute
Institut für Regelungstechnik
Steimle, Markus;
GND
1072250632
ORCID
0000-0002-5357-9701
Affiliation/Institute
Institut für Regelungstechnik
Maurer, Markus;
GND
172523982
ORCID
0000-0001-8508-8934
Affiliation/Institute
Institut für Psychologie
Vollrath, Mark

In urban areas, drivers often have difficulty detecting pedestrians who want to cross the street but are obstructed by parked vehicles. Highly automated vehicles (HAVs, SAE Level 4) will have to solve this issue automatically and at least as safely as human drivers. We conducted two studies to investigate whether passengers’ trust in automation can be supported by adapting HAV driving behavior to demonstrate that the vehicle is “aware” of a potential hazard. We examined the passengers’ perception of risk, their trust in the automated driving system, and their preferences for HAV behavioral adaptations as a response to potential hazard in a driving situation in two experimental studies, 1) a driving simulator study and 2) a human&vehicle-in-the-loop study. We varied the lateral offset from the road center and deceleration (driving simulator only) when passing a parked vehicle. In the driving simulator study, we varied the HAV’s speed and the presence of a pedestrian in the parking bay and an oncoming vehicle. In the human&vehicle-in-the-loop study, the HAV passing the obscured pedestrian at 50 km/h. Results support the idea that it is beneficial for human passengers to be informed about the HAVs “awareness” of a potentially hazardous situation. However, introducing a lateral offset had no positive effect on passengers’ perceptions. Deceleration enhanced passengers’ trust but was only examined in the driving simulator study. Future research should compare the effects of behavioral adaptations to other in-vehicle human–machine interface approaches providing information about the “awareness” about potential hazards visually.

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