Powered two-wheelers dynamics: determination of thresholds for the detection of emergency situations
Résumé
During naturalistic driving studies on Powered Two-Wheelers (PTW), a lot of data is acquired and difficulties appear to analyze all of it. So it seems interesting to focus on incident detection to shorten the driving sequences to study. Furthermore, a lot of studies were conducted concerning accidents, hence the decision to focus on near-crashes. This work deals with the determination of the most adequate PTW's dynamics parameters and their thresholds level allowing incidents detection. More than 60 experimental tests were performed on track (braking, slaloms, avoidance manoeuvres...) and on road with an instrumented motorcycle. Data recorded were speed, accelerations, rotation speeds, steering angle, steering torque, lean angle, brake pressure and trajectory. The method consists to observe these parameters in parallel with the feeling of the rider when performing manoeuvres. For example, the rider was not considering engaging strongly the motorcycle capacities for the slalom at 30km/h, while the avoidance manoeuvre at the same speed was considered as an emergency manoeuver. Then, criteria and thresholds have been determined to highlight the suddenness of a manoeuvre and the urgency of a situation. For the longitudinal dynamics, the retained conditions are: Longitudinal Speed greater than 10 km/h and Longitudinal Acceleration, under braking only, less than -6m/s². Concerning lateral dynamics, two possible criteria were retained: norm of Rotation Speed vector (Roll+Yaw+Pitch) greater than 80°/s or norm of Rotation Acceleration vector (Roll+Yaw+Pitch) greater than 300°/s². These criteria were afterwards validated on road travels were the rider ensures not to be confronted to any emergency situation. This study allows determining the PTW dynamics parameters that make possible the incident or near-crashes detection. About 30 vehicles were then instrumented to collect a large amount of data on the use of dynamics capacities. In the future these data collection will permit to refine these thresholds values.