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Forward Collision Alarms (FCA) intend to signal hazardous traffic situations and the need for an immediate corrective driver response. However, data of naturalistic driving studies revealed that approximately the half of all alarms activated by conventional FCA systems represented unnecessary alarms. In these situations, the alarm activation was correct according to the implemented algorithm, whereas the alarms led to no or only minimal driver responses. Psychological research can make an important contribution to understand drivers’ needs when interacting with driver assistance systems.
The overarching objective of this thesis was to gain a systematic understanding of psychological factors and processes that influence drivers’ perceived need for assistance in potential collision situations. To elucidate under which conditions drivers perceive alarms as unnecessary, a theoretical framework of drivers’ subjective alarm evaluation was developed. A further goal was to investigate the impact of unnecessary alarms on drivers’ responses and acceptance. Four driving simulator studies were carried out to examine the outlined research questions.
In line with the hypotheses derived from the theoretical framework, the results suggest that drivers’ perceived need for assistance is determined by their retrospective subjective hazard perception. While predictions of conventional FCA systems are exclusively based on physical measurements resulting in a time to collision, human drivers additionally consider their own manoeuvre intentions and those attributed to other road users to anticipate the further course of a potentially critical situation. When drivers anticipate a dissolving outcome of a potential conflict, they perceive the situation as less hazardous than the system. Based on this discrepancy, the system would activate an alarm, while drivers’ perceived need for assistance is low. To sum up, the described factors and processes cause drivers to perceive certain alarms as unnecessary. Although drivers accept unnecessary alarms less than useful alarms, unnecessary alarms do not reduce their overall system acceptance. While unnecessary alarms cause moderate driver responses in the short term, the intensity of responses decrease with multiple exposures to unnecessary alarms. However, overall, effects of unnecessary alarms on drivers’ alarm responses and acceptance seem to be rather uncritical.
This thesis provides insights into human factors that explain when FCAs are perceived as unnecessary. These factors might contribute to design FCA systems tailored to drivers’ needs.
The increasing importance of environmental friendly and efficient transportation guides the interest of researchers and car manufacturers towards the development of technologies that support an efficient driving style.
This thesis presents the development of a traffic light assistance system with the focus on human factors. The system aims on supporting drivers in approaching traffic light intersections efficiently. In three driving simulator studies, the content related research covered the investigation of the unassisted driving task, the influence of the system on the driver’s perception of the interaction with other road users and the information strategy of the human machine interface. When the traffic light phase changes or when visibility is limited, drivers prepare driving behaviour that is not appropriate for the traffic light phase at arrival at the intersection. These situations offer the greatest potential for the assistance system. The traffic light assistant is able to change driving behaviour. However, the expectation of other road user’s emotional reactions influences driver compliance. In situations in which drivers expected to bother others with their driving behaviour, compliance to the traffic light assistant was low. Further, the deviations of driver behaviour from the target strategy of the traffic light assistant are lowest when the HMI includes the two information units target speed and action recommendations. Traffic light phase information in the HMI is a subjectively important information for drivers. The results point towards the presentation of all three information units.
The method related research covered the development of a method for measuring drivers’ information demand for dynamic stimuli. While driving, specific stimuli are action relevant for drivers, i.e. they need to be processed in order to decide on the appropriate driving behaviour. Eye tracking has been the standard method for measuring information demand while driving. The novel MARS (Masking Action Relevant Stimuli) method measures information demand by masking the dynamic action relevant stimulus in the driving environment or in the vehicle. To unmask the stimulus for a fixed interval, drivers press a button at the steering wheel. In the present thesis, two driving simulator studies evaluated the MARS method. They included measuring information demand for the traffic light phasing and the in-vehicle display of the traffic light assistant. The analyses demonstrate that variations in the experimental conditions influence the information demand measured with the MARS method qualitatively similar to the influences on fixations measured by eye tracking. Due to its simple application, the MARS method represents a promising tool for transportation research.