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How automated vehicles should operate to avoid fatal crashes with cyclists?
Roni Utriainen1, Markus Pöllänen1
1Transport Research Centre Verne, Tampere University, P.O. Box 600, FI-33014 Tampere, Finland.
Accident; Analysis and Prevention
|March 29, 2021
Summary
Highly automated vehicles (HAVs) need five key features to safely interact with cyclists and prevent fatal crashes. Implementing these features presents significant programming and design challenges for complex traffic scenarios.
Area of Science:
- Road safety
- Human-computer interaction
- Autonomous systems
Background:
- Fatal crashes between cyclists and passenger cars remain a critical road safety issue.
- Highly automated vehicles (HAVs) present a potential solution but require specific capabilities for safe interaction with vulnerable road users like cyclists.
Purpose of the Study:
- To identify essential features for HAVs to ensure safe operation during encounters with cyclists.
- To analyze fatal crash data to determine how HAVs could have prevented these incidents.
Main Methods:
- Qualitative evaluation of five pre-defined HAV capabilities.
- Analysis of fatal car-cyclist crash data from Finland.
- Hypothetical scenario testing of HAVs replacing human-driven vehicles.
Main Results:
- Five crucial HAV features for cyclist crash avoidance were identified: cyclist recognition, awareness of traffic rules, intention signaling, safe driving pattern maintenance, and cyclist intention assessment.
- Implementing these features is complex due to varied and challenging traffic environments.
Conclusions:
- HAVs require sophisticated features to navigate complex interactions with cyclists safely.
- Further research and development are needed for real-world implementation of these safety features.
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