A linear acceleration car-following algorithm for Autonomous Intelligent Cruise Control Systems (AICCS)

This paper introduces a new car-following model for Autonomous Intelligent Cruise Control Systems (AICCS). In AICCS, a controller in the vehicle performs the car-following by controlling the throttle and the brake according to a car-following logic, while the driver conducts the steering. A more detailed car-following logic than the existing models was needed for the AICCS controller because, these models use a constant and step-wise acceleration model that could cause unrealistic and abrupt vehicle behavior when used in AICCS. Therefore, a linear acceleration car-following model is developed. The linear acceleration model provides continuous acceleration profiles which results in a smooth and real-like vehicle behavior in car-following. Another desirable property to have in AICCS is that the car-following behavior of AICCS must resemble the driver car-following so that the AICC vehicles can be mixed with the ordinary vehicles in the traffic. Furthermore, AICCS relies on the sensors placed in the vehicle to obtain speed, acceleration and headway information from the leader(s) at certain time intervals and determines the appropriate action. Thus, the information obtained from the sensors of the vehicle must be adequate for the car-following without any help from roadside intelligence sources. Therefore, a linear acceleration car-following model has been developed with the above desirable properties for AICCS and real time simulation applications. The model is validated with the field data and the results show that the new model can simulate the driver car-following behavior and perform the car-following for the drivers on a freeway. Moreover, it is observed that the linear acceleration car-following model can process the vehicles reliably and realistically even in the stop-and go conditions.