Cycling, as one of the oldest forms of mobility, is currently experiencing a renaissance. It supports active mobility and can have a positive influence on public health, the environment, climate and the traffic situation. Pedelecs (bicycles with an electric motor supporting the user up to a speed of 25 kmph) represent a new form of active mobility and are currently enjoying great popularity as they have the same benefits compared to conventional bicycles and, in addition, make cycling accessible to new user groups. With the growing number of pedelecs, however, potential for conflict also increases. Unfortunately, the majority of accidents cannot yet be analysed accordingly, as pedelec-specifiic characteristics are missing from the accident data. This fact in itself has already been proven as a barrier. Most accident studies focusing on pedelecs are based on police data from standardised accident forms [e.g. 1, 2, 3, 4]. Their findings can be summarised in the following key statements: Accidents with pedelecs are less frequent but more severe than those with conventional bicycles. For both, accidents on urban roads dominate, but pedelec accidents occur significantly more often on rural roads than conventional bicycle accidents. And: injured pedelec users, especially those fatally injured, are on average significantly older than injured users of conventional bicycles. But, standardised accident forms were initially designed for accidents with double-track motor vehicles, in particular passenger cars. Accidents with bicycles (especially pedelecs), are difficult to categorise with this systematic as important information is missing. For example, 'falling on ground' is not an accident category as cars normally won't do so, but for pedelec accidents, this information is fundamental. This acts as a barrier as bicycle-specific causes of accidents cannot be analysed. However, accident statistics are the most important basis for evidence-based measures in road safety work. The aim of this paper is therefore to identify and categorise pedelec-specific accident characteristics and to evaluate pedelec accidents on the basis of these characteristics to identify frequent and severe accident constellations. [From: Introduction]
| Identifer | oai:union.ndltd.org:DRESDEN/oai:qucosa:de:qucosa:82453 |
| Date | 19 December 2022 |
| Creators | Panwinkler, Tobias |
| Publisher | Technische Universität Dresden |
| Source Sets | Hochschulschriftenserver (HSSS) der SLUB Dresden |
| Language | English |
| Detected Language | English |
| Type | doc-type:conferenceObject, info:eu-repo/semantics/conferenceObject, doc-type:Text |
| Rights | info:eu-repo/semantics/openAccess |
| Relation | urn:nbn:de:bsz:14-qucosa2-813602, qucosa:81360 |
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