BSafe-360: An All-in-One Naturalistic Cycling Data Collection Tool

Area of Science:

• Transportation engineering
• Road safety research
• Wearable sensor technology

Background:

• Increasing bicycle use necessitates better safety measures.
• Current data limitations hinder accurate assessment of cyclist risks.
• Understanding cyclist behavior and road interactions is crucial for safety improvements.

Purpose of the Study:

• To develop and evaluate the BSafe-360, a novel multi-sensor data acquisition system (DAS).
• To collect high-granularity naturalistic cycling data for urban safety analysis.
• To identify factors contributing to bicycle collisions and severity.

Main Methods:

• The BSafe-360 integrates a Raspberry Pi, GPS, ultrasonic sensors, IMU, and RTC in a bicycle phone case.
• Dual Python scripts manage data processing and storage in local and online databases.
• A proof-of-concept experiment collected seven hours of data, supplemented by CCTV and weather information.

Main Results:

• The BSafe-360 successfully collected granular data on bicycle trajectory, lateral passing distance (LPD), and cyclist behavior.
• The integrated sensor approach provides comprehensive information for safety event verification.
• The device demonstrated its capability in a real-world data collection scenario.

Conclusions:

• The BSafe-360 is a promising tool for naturalistic cycling data collection.
• Enhanced data facilitates a deeper understanding of bicycle safety dynamics.
• The system has the potential to significantly improve urban cyclist safety and reduce incidents.