Vehicle class–specific route guidance of freeway traffic by model-predictive control

Few active traffic management measures proposed in the past considered the distinction of different vehicle classes. Examples of measures specific to vehicle class are truck lanes and high-occupancy toll lanes. It is proposed that the distinction of different vehicle classes, with different flow characteristics and societal and economic functions, can contribute to the effectiveness of traffic management measures. This study developed a multiclass controller that rerouted the traffic class specifically. Vehicle class–specific properties such as vehicle length and value of time were used in a model-predictive control approach to minimize the total time spent in the network by vehicles and the corresponding economic costs. By means of a simple test case with synthetic data, it was shown that a multiclass controller outperformed a single-class controller and that the multiclass control signals were sensitive to the value of time and the capacity of the network.