Data collection and processing tools for naturalistic study of powered two-wheelers users' behaviours

Area of Science:

• Road Safety
• Human Factors
• Motorcycle Dynamics

Background:

• Instrumented vehicles are crucial for understanding driver behavior and designing safety countermeasures.
• Instrumentation of Powered Two-Wheelers (PTW) presents unique technical challenges compared to other vehicles.
• Recent European advancements have yielded tools and methodologies for studying PTW rider behavior and dynamics, including crash scenarios.

Purpose of the Study:

• To present methodological tools developed for studying PTW rider behavior in real-world and track conditions, including falls.
• To illustrate the types of results obtainable from studies utilizing these tools.
• To identify the strengths and weaknesses of the methodology for large-scale naturalistic riding studies.
• To highlight how this research fills knowledge gaps regarding PTW rider behavior and risk factors.

Main Methods:

• Development and application of advanced instrumentation for PTWs.
• Integration of multiple data sources: PTW sensors, video retrieval, GPS, and rider verbal data.
• Study of diverse riding situations, from naturalistic riding (filtering, line splitting) to crash events.

Main Results:

• Successful design and tuning of real-time fall detection systems for PTWs.
• Studies on riding training systems and rider behavior in naturalistic riding scenarios.
• Acquisition of in-depth data on rider decision-making processes and motorcycle dynamics.

Conclusions:

• The developed methodology provides a robust framework for studying PTW rider behavior in various conditions.
• This approach offers significant potential for improving PTW safety through evidence-based countermeasures.
• Further research using this methodology will address critical knowledge gaps in PTW rider risk factors.