Realization and Evaluation of an Instructor-Like Assistance System for Collision Avoidance

Advanced driver assistance systems should not only make the driving experience safer and more comfortable, it should also have a positive effect on driving behaviors. In this paper, an instructor-like assistance system for collision avoidance is developed and realized on an actual vehicle. The proposed system is activated only if the driver is not operating the vehicle properly when facing a collision risk. The vehicle control is shared by the driver and the assistance system. It is controlled by servomotors. In order to fulfill this requirement, a constraint satisfaction problem (CSP) is proposed and solved based on safe driving constraints and predictive vehicle states. Vehicle motion is predicted by a combination of a dynamics model and a potential field model that reflects the driver's risk feeling to an obstacle. Improved driving behavior is verified and evaluated quantitatively based on driving simulator data. By comparing the driving data before and after using the assistance system, it is found that distance is increased and speed is reduced when passing an obstacle. As a result, driving behavior becomes safer for collision avoidance due to the system's instruction. Furthermore, an experiment with an actual vehicle also demonstrates the practicability of the control system and shows the influence of different safe driving constraints.

Automated summary

This paper introduces an instructor-like assistance system for collision avoidance that only activates when the driver is facing a collision risk due to improper operation. Through a combination of safe driving constraints and predictive vehicle states, the system improves driving behavior, as evidenced by increased distance and reduced speed when passing an obstacle. Experimental data from an actual vehicle also confirms the efficacy of the control system and the impact of different safe driving constraints.