2026-07-02 チャルマース工科大学
＜関連情報＞
- https://news.cision.com/chalmers/r/drunk-riding–behind-almost-half-of-fatal-electric-scooter-crashes-in-sweden,c4367711
- https://www.sciencedirect.com/science/article/pii/S0022437526000769
3つのモード、3つのプロファイル：スウェーデンにおける電動スクーター、電動自転車、および従来型自転車の死亡事故の特徴付け Three modes, three profiles: Characterizing fatal crashes on e-scooters, e-bikes, and conventional bicycles in Sweden
Rahul Rajendra Pai, Rikard Fredriksson, Marco Dozza
Journal Of Safety Research Available online: 7 May 2026
DOI:https://doi.org/10.1016/j.jsr.2026.05.001
Highlights
- Compared e-scooterist, e-cyclist & conventional bicyclist fatalities across Sweden.
- Three micromobility modes exhibit fundamentally distinct fatal crash profiles.
- Most fatal e-scooter crashes involve severe intoxication and own vehicles.
- Critically low helmet use across all modes exacerbates fatal head injury risks.
- Distinct crash profiles suggest vehicle-agnostic safety policies are insufficient.
Abstract
Introduction: The electrification of personal transport has transformed urban mobility, but the rapid adoption of e-bikes and e-scooters has introduced distinct fatal crash risks. Existing research on micromobility safety is often limited to non-fatal injuries and relies on standard crash databases that often lack the granular detail needed, for instance, to distinguish between vehicle types, ownership (private vs. rental), or to quantify the severity of alcohol intoxication. Method: We conducted a retrospective analysis of all fatal crashes involving conventional bicyclists (n = 152), e-cyclists (n = 34), and e-scooterists (n = 18) recorded in Sweden’s unique in-depth fatal crash database (2016–2024). This national-level data, compiled by multidisciplinary teams, allowed for an unprecedented comparative analysis of crash typologies, vehicle characteristics, and rider profiles. Results: The three micromobility modes showed different fatal crash profiles. Conventional bicyclists were old (median age 71.0) involved in multi-road-user crashes during weekdays. In contrast, e-scooterist fatalities involved middle-aged riders (median age 47.5) in single-rider crashes, occurred on weekends and at night, and showed a high prevalence of alcohol intoxication (44.4%). Interestingly, the majority of e-scooterist crashes (66.7%), particularly those involving alcohol, occurred on privately-owned vehicles. E-cyclists occupied an intermediate crash and rider profile, sharing characteristics with both modes. Across all modes, head injuries were the dominant cause of death, while helmet use was critically low or absent. Conclusions: The unique crash profiles suggest that a vehicle-agnostic regulatory approach may be a missed opportunity to develop appropriate safety interventions. The findings highlight that safety interventions must extend beyond shared fleets to ensure private e-scooterists are not overlooked. The high prevalence of severe alcohol intoxication and lack of helmet use indicate clear areas for intervention. Practical applications: This study provides a detailed, evidence-based resource for policymakers to develop targeted regulations, safer infrastructure, and create awareness campaigns that address the risks unique to different micromobility modes.
