Extending adaptive cruise control ( ACC ) towards adaptive driving strategies

We present an adaptive cruise control (ACC) strategy where the acceleration characteristics, i.e., the ’driving style’ automatically adapts to different traffic situations. The three components of the concept are the ACC itself implemented in form of a car-following model, an algorithm for the automatic real-time detection of the traffic situation based on local information, and a ’driving strategy matrix’ to adapt the driving characteristics, i.e., the parameters of the ACC controller to the traffic conditions. Optionally, inter-vehicle and roadside-to-car communication can be used to improve the accuracy for determining the local traffic states. We simulated the complete concept microscopically on a road section with an on-ramp bottleneck using real loop-detector data for an afternoon rush-hour as input for the upstream boundary. Already a small percentage of ’traffic-adaptive’ ACC vehicles, i.e., a relatively modest local change in the maximum free flow improves the traffic stability and performance significantly. While the traffic congestion in the reference case was completely eliminated when simulating a proportion of 25% of ACC vehicles, travel times for the drivers are reduced in a relevant way already for much lower penetration rates. The presented results are largely independent of details of the model, the boundary conditions, or the type of road inhomogeneity. Kesting, Treiber, Schönhof, and Helbing 3