Car-following Characteristics of Adaptive Cruise Control from Empirical Data

Computer-driven vehicles are expected to have profound impacts on transportation modeling, yet many transportation agencies rely on car-following models based on human drivers who have different sensory and control capabilities than computers. Car-following models will need to be updated to reflect automation of the driving task. This paper investigates characteristics of a commercially available adaptive cruise control system driven in real traffic. Four attributes were measured directly: standstill distance, startup time, unimpeded acceleration profile, and maximum desired deceleration. The Intelligent Driver Model was compared to the empirical data, and the test vehicle was found to decelerate less severely than predicted by the model. Finally, guidance for simulating adaptive cruise control in the microscopic simulation software VISSIM was provided through recommended values for ten parameters in the Wiedemann 99 car-following model.

99th Annual Meeting of the Transportation Research Board