Braking assistance algorithm considering driver characteristics at signalized intersection

Driving safety and traffic efficiency have always been the research focuses for signalized intersection. This study proposes a braking assistance algorithm, which is developed to help driver brake with a smooth braking process and appropriate stopping distance at signalized intersection as human driver does. The system is required to take human driver's individual differences into consideration. Thus, the braking behavior of different drivers while approaching the intersections is analyzed in terms of braking frequency and stopping distance. Based on driver behavior analyses, the braking assistance algorithm is designed with two modes, one-off braking mode and two-braking mode. The algorithm mode and parameters can be adjusted according to the driver's real world driving behavior data. Finally, the algorithm is verified in the simulation environment. Results show that the algorithm is effective in achieving the desired stopping distance with a stable braking process like the driver. This study provides a practical method of developing the braking assistance algorithm with the ability of adapting to driver characteristics. This study is significant for autonomous vehicle that is expected to provide a comfortable, efficient and safe driving for passengers in the near future.