Survey-Based Accident Analysis for Human-Powered Three-Wheeled Vehicles

Authors Abstract
The causes of accidents involving nonconventional bicycle types have hardly been investigated in the literature to date. However, these vehicles could play an important role in reducing the CO2 emissions generated by traffic. As a basis for improving the driving safety of these environmentally friendly vehicles, this article presents the results of a survey on accidents and near-accidents of multitrack bicycle vehicles. More than 120 critical or accident situations of 86 drivers were analyzed. The situations are investigated with respect to the circumstances, the causes, and the consequences of the accidents using manual analysis and multiple correspondence analysis. A distinction is made between single accidents and accidents with another party. The aim of the survey is not to make statistically accurate statements on the frequency and probability of accidents, but rather to analyze the accident or near-accident circumstances. It is shown that the causes of single accidents are usually too high cornering velocities in combination with other factors such as road conditions. In the case of accidents with external involvement, the person who caused the accident is usually the other party involved. The accident opponent is in most cases a passenger car. Here the overlooking of the vehicles is the most frequent cause of accidents. Finally, possibilities to reduce the probability of accidents are briefly discussed for the different situations. As the research shows, most of the situations described occur on the road. This indicates that there are deficits in the bicycle infrastructure for the vehicles considered here. The results also indicate that there are deficits with regard to the perceptibility of the vehicles by other road users.
Meta TagsDetails
Wilhelm, T., Dorsch, V., and Gauterin, F., "Survey-Based Accident Analysis for Human-Powered Three-Wheeled Vehicles," Transportation Safety 10(1):3-22, 2022,
Additional Details
Oct 12, 2021
Product Code
Content Type
Journal Article