Can Information About an Approaching Bicycle’s Characteristics Influence Drivers’ Gap Acceptance and TTA Estimates?

E-bikes, which have the potential to reach higher speed levels than conventional bicycles, but look basically the same, are suspected to be at a higher crash risk than such conventional bicycles. Other road users might misjudge the time remaining before the approaching bicycle arrives (time to arrival, TTA) and accept unsafe gaps (e.g. for turning manoeuvres) as a result of this combination of higher speed and well-known looks. Researchers have therefore suggested to make drivers aware of the higher speed of e-bikes, and give e-bikes a distinct appearance. Goal of this experiment was to investigate the effects of such a unique appearance, coupled with clear instructions about the capabilities of ebikes, on gap acceptance and TTA estimates. Participants were presented with video sequences of approaching cyclists clearly identifiable as either riding a conventional bicycle or e-bike, and were required to either indicate the smallest acceptable gap for a left turn in front of the cyclist, or to estimate TTA in two different experimental blocks. The results showed no difference in accepted gap size between the two appearances of the cyclist, whereas there was a minor effect on TTA estimates. Overall, the results imply that simply informing other road users about e-bikes (in conjunction with a re-design that gives them a unique appearance), might not be sufficient to elicit a more conservative behavior

Gender Effects on Lane Change Test (LCT) Performance

There are various easy-to-implement, low-cost methodologies for evaluating driver performance under distraction caused by in-vehicle tasks. One of them is the Lane Change Test (LCT), which is currently under consideration for becoming an ISO-standardized procedure. This paper investigates the effect of gender on LCT performance. Although a common procedure in psychological research, balancing for gender is not a requirement made by the ISO draft. However, using data from three LCT experiments, we found gender differences in LCT as well as secondary task performance. We conclude that subject samples balanced for gender are necessary to assure comparability of LCT results

Time to Arrival Estimates, (Pedestrian) Gap Acceptance and the Size Arrival Effect

Various studies have found that road users’ acceptance of gaps to cross in front of another vehicle is dependent on the approaching vehicle’s size, with smaller accepted gaps in front of smaller vehicles. At the same time, the so called size arrival effect is well known from research on time to collision / time to arrival estimates, where larger objects / vehicles tend to be judged as arriving earlier than smaller objects / vehicles. However, so far there has been no attempt to connect these two approaches in a single experiment to investigate whether the size arrival effect that is prevalent in time to arrival estimates can explain the variations in gap acceptance. In this experiment, twenty-seven participants observed video clips of approaching virtual vehicles of varying size (truck, bus, van, two different cars and a motorcycle) from a pedestrian’s perspective, and were either required to indicate a crossing decision, or to estimate time to arrival. While, overall, the effect of vehicle size was clearly visible for both crossing decision and time to arrival estimates, there was also a clear exception in form of the motorcycle, which went with larger accepted gaps than some of the larger vehicles. This exception might be explained by the participants’ subjective rating of perceived threat, which was rather high for the motorcycle. As (with the exception of the motorcycle), vehicle size and perceived threat correlated substantially, it is unclear at this stage to what degree these two factors contribute to perceived time to arrival and crossing decisions

The Development of a Cognitive Skills Training to Support Driver Education: Experimental Validation of Theoretical Underpinnings

Crash numbers of novice drivers are, despite best efforts of all involved institutions, alarmingly high. One central explanation refers to deficits in cognitive skills such as hazard perception, which have a tremendous influence on accident involvement of younger drivers. Conventional forms of driver training have largely failed to build up skills that go beyond a rather descriptive knowledge of how to drive. Computer based trainings (CBTs) are assumed to provide new ways of tackling this problem. There are already CBTs available that address relevant issues and are presumed to be effective. However, their evaluations lack evidence for the superiority of the specific features of multimedia based interventions over other forms of training. This shortcoming, in addition to the fact that all available relevant CBTs have been developed within contexts that differs significantly from European conditions in terms of the “average” driving environment as well as the respective educational schemes, has prompted us to develop a new CBT that is intended to complement the existing driver training program by addressing critical cognitive skills. In a first step, we tested the CBTs theoretical validity by comparing the performance in the training itself between learner drivers and experienced drivers. The results show that experienced drivers achieve higher scores in the CBT. We conclude that our application does indeed address relevant cognitive skills that are associated with driving experience

The Development of a Cognitive Skills Training to Support Driver Education – Comparing Performance of Experienced and Trained Learner Drivers

Deficits in cognitive skills such as hazard perception are considered one of the major factors explaining the high numbers of crashes for novice drivers. Computer based trainings (CBTs) have been identified as a potential measure to improve such skills. Several CBTs have been developed since. Some of them have been evaluated, however, only by comparing a treatment group and a control group. While results show that the evaluated CBTs are somewhat effective, it is unclear how an experienced driver would have performed in the test scenarios. We developed our own CBT, and in a first step, evaluated it following the same known strategy (treatment and control group, adding a “paper based training group). Results provided evidence for the assumption that the CBT had a positive effect on learner drivers’ glance behaviour in simulated driving (Petzoldt et al., 2013). However, after we confirmed the effectiveness, we tested a group of experienced drivers on exactly the same simulator scenarios. The comparison between treatment, control and experienced driver group is presented in this paper. Results show comparable patterns of glance behaviour for the treatment group and the experienced drivers, superior to that of the control group. Driving performance rated by experts was mostly appropriate for all groups, with notable exceptions for some scenarios

Contributions to the 10th International Cycling Safety Conference 2022 (ICSC2022)

This publication contains all contributions (extended abstracts) to the 10th International Cycling Safety Conference, which was held in Dresden, Germany, Nov. 08-10, 2022

Curve Negotiation: Identifying Driver Behavior Around Curves with the Driver Performance Database

Approximately one quarter of all accidents outside city limits occur while driving around curves, where assistance systems could prevent the driver from negotiating curves with excessive speed. This study argues that the parameterizing of a Driving Assistant System could be realized with data from realistic, noncritical driving behavior offered by Naturalistic Driving Studies. The Driver Performance Database presented in this study provides a tool for observing normal, noncritical driving behavior. The Database contains results from road tests with an instrumented vehicle that were carried out on public road traffic on a predetermined route, which was precisely measured in advance. In addition to vehicle state parameters, we also collected data concerning the driving environment and physiological information. With the Driver Performance Database it is possible to generate different facets of human driving behavior in a descriptive and normative way, which is illustrated by driver behavior in curve negotiation

Curve Negotiation: Identifying Driver Behavior Around Curves with the Driver Performance Database

Approximately one quarter of all accidents outside city limits occur while driving around curves, where assistance systems could prevent the driver from negotiating curves with excessive speed. This study argues that the parameterizing of a Driving Assistant System could be realized with data from realistic, noncritical driving behavior offered by Naturalistic Driving Studies. The Driver Performance Database presented in this study provides a tool for observing normal, noncritical driving behavior. The Database contains results from road tests with an instrumented vehicle that were carried out on public road traffic on a predetermined route, which was precisely measured in advance. In addition to vehicle state parameters, we also collected data concerning the driving environment and physiological information. With the Driver Performance Database it is possible to generate different facets of human driving behavior in a descriptive and normative way, which is illustrated by driver behavior in curve negotiation

Trying to validate subjective reports with a naturalistic driving data - a case against questionnaires and surveys to quantify driver distraction

The effects of different forms of driver distraction on driving distracting activities, however, is less clear. Available are comparatively well understood. How often drivers actually engage in different methods are either not able to provide a complete picture, or are extremely expensive. Post-drive questionnaires and surveys might provide a cheap solution to the problem. As part of a naturalistic driving pilot survey/questionnaire that is intended to capture the occurrence and duration of different secondary tasks. However, for a variety of reasons, this attempt was unsuccessful. It became clear that there was a huge discrepancy between the drivers’ naïve understandings of secondary tasks (what is it, what is part of it, how long is it, etc.) and scientific definitions of the same concepts. Further problems arose from the fact that even though questioned directly after the trip, many accounts appeared to have been reconstructions, rather than recollections of secondary task engagement. We conclude that subjective accounts of secondary task engagement are largely inappropriate to quantify driver distraction