Microscopic simulation of multi-lane traffic under dynamic tolling and information feedback

To investigate drivers' lane-changing behavior under different information feedback strategies, a microscopic traffic Simulation based on the Cellular automaton model was made on the typical freeway with a regular lane and a high-occupancy one. A new dynamic tolling scheme in terms of the real-time traffic condition oil the high-occupancy lane was further designed to enhance the whole freeway's flow throughput. The results show that the mean velocity feedback strategy is generally more efficient than the travel time feedback strategy in correctly guiding drivers' lane choice behavior. Specifically, the toll level, lane-changing rate and freeway's throughput and congestion coefficient induced by the travel time feedback strategy oscillate with larger amplitude and longer period. In addition, the dynamic tolling scheme can make the high-occupancy lane less congested and maximize the freeway's throughput when the regular-lane inflow rate is larger than 0.45.