Can a unique appearance of e-bikes, coupled with information on their characteristics, influence drivers’ gap acceptance?

Abstract

Objective: Car drivers tend to underestimate the speed of e-bikes and accept smaller gaps for crossing in front of them compared to conventional bicycles. As an explanation, it has been suggested that car drivers rely on their previous experience with conventional bicycles, which tells them that those mostly travel at low speeds. E-bikes, which look just like regular bicycles, do not conform to this expectation, resulting in potentially dangerous interactions. Based on this assumption, researchers have suggested to increase other road users’ awareness of e-bikes’ higher speeds by giving them a distinct appearance. The goal of our experiment was to investigate the effects of such a unique appearance, aided by clear instructions about the higher speeds of e-bikes, on gap acceptance.

Method: In order to investigate the effect of appearance independent of the effect of bicycle type, we used video sequences of conventional bicycles and e-bikes approaching at different levels of speed. The riders (regardless of what type of bike they were actually riding) either wore an orange helmet as an indicator for an e-bike, or a gray helmet indicating a conventional bicycle. Fifty participants were asked to indicate the smallest acceptable gap for a left turn in front of the cyclist or e-bike rider.

Results: The results showed significantly smaller acceptable gaps when confronted with the gray helmet (signal for bicycle) compared to the orange helmet (signal for e-bike), whereas there was no difference between the actual bicycle types.

Conclusions: Overall, the results indicate that informing about e-bikes characteristics in combination with a unique appearance can lead to a more cautious behavior among car drivers.

Keywords:

• Time to collision
• gap acceptance
• electric bicycle
• speed judgements

Acknowledgments

The videos used in this study were produced a project funded by the German Insurers Accident Research. The authors would like to thank Pia Färber for her help while data acquisition.