Combining haptic human-machine interaction with predictive path planning for lane-keeping and collision avoidance systems

This paper presents a first approach for a haptic human-machine interface combined with a novel lane-keeping and collision-avoidance assistance system approach, as well as the results of a first exploration study with human test drivers. The assistance system approach is based on a potential field predictive path planning algorithm that incorporates the drivers wishes commanded by the steering wheel angle, the brake pedal or throttle, and the intended maneuver. For the design of the haptic human-machine interface the assistance torque characteristic at the handwheel is shaped and the path planning parameters are held constant. In the exploration, both driving data as well as questionnaires are evaluated. The results show good acceptance for the lane-keeping assistance while the collision avoidance assistance needs to be improved.

I. INTRODUCTION

One of the key issues in bringing advanced driver assistance systems (ADAS) like lane-keeping, lane-changing or collision avoidance systems into the market is the design of an appropriate interaction between driver and driver assistance systems. The driver acceptance depends on a thorough driver and situation based design of the human-machine interface.