A collision model for safety evaluation of autonomous intelligent cruise control.
This paper describes a general framework for safety evaluation of autonomous intelligent cruise control in rear-end collisions. Using data and specifications from prototype devices, two collision models are developed. One model considers a train of four cars, one of which is equipped with autonomous intelligent cruise control. This model considers the car in front and two cars following the equipped car. In the second model, none of the cars is equipped with the device. Each model can predict the possibility of rear-end collision between cars under various conditions by calculating the remaining distance between cars after the front car brakes. Comparing the two collision models allows one to evaluate the effectiveness of autonomous intelligent cruise control in preventing collisions. The models are then subjected to Monte Carlo simulation to calculate the probability of collision. Based on crash probabilities, an expected value is calculated for the number of cars involved in any collision. It is found that given the model assumptions, while equipping a car with autonomous intelligent cruise control can significantly reduce the probability of the collision with the car ahead, it may adversely affect the situation for the following cars.
Touran
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A
Department of Civil and Environmental Engineering, Northeastern University, Boston, MA 02115, USA. atouran@lynx.dac.neu.edu
Brackstone
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MA
McDonald
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M
D000054:Acceleration; D000063:Accidents, Traffic / Q000517:prevention & control*; D001185:Artificial Intelligence; D001336:Automobiles; D003198:Computer Simulation; D006801:Humans; D009010:Monte Carlo Method; D011336:Probability; D018570:Risk Assessment; D012449:Safety