Human Factor Considered Risk Assessment of Automated Vehicle Using Vehicle to Vehicle Wireless Communication

Abstract

This paper describes a human factor considered risk assessment of automated vehicle using vehicle to vehicle wireless communication (V2V communication). A human-reaction time is incorporated into the probabilistic threat assessment algorithm for the human-centered risk assessment. The V2V communication have been fused with a radar sensor to achieve more enhanced tracking performance of automated vehicle. Information fusion of two tracks, V2V communication and radar sensor, is performed using Global Nearest Neighborhood (GNN) approach. A prediction of vehicle's motion follows the basic idea of the particle filtering. Based on the predicted behavior of vehicles, a collision risk is computed numerically and 321 driver data based human reaction time are incorporated to determine an active safety control intervention moment. The humancentered risk assessment algorithm has been applied to a collision avoidance scenario to monitor threat vehicles ahead and to find the best intervention point. Effects of the vehicular communication on a target vehicle state estimation and a vehicle safety control performance are investigated. The performance of the proposed algorithm has been investigated via computer simulation studies. It has been shown from both simulations and vehicle tests that the proposed human-centered risk assessment algorithm with the V2V communication can be beneficial to active safety systems in decision of controller intervention moment and in control of automated drive for the guaranteed safety.

Autonomous vessels: state of the art and potential opportunities in logistics

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