A Semi-Cooperative Social Routing System to Reduce Traffic Congestion

One of the ways to reduce city congestion is to balance the traffic flow on the road network and maximally utilize all road capacities. There are examples showing that, if the drivers are not competitive but cooperative, the road network usage efficiency and the traffic conditions can be improved. This motivates the idea of designing a cooperative routing algorithm to benefit most vehicles on the road. This paper presents a semi-cooperative social routing algorithm for large transportation network with predictive traffic density information. The goal is to integrate a cooperative scheme into the individual routing and achieve short traveling time not only for the traveler itself, but also for all vehicles in the road network. The most important concept of this algorithm is that the route is generated with the awareness of the total travel time added to all other vehicles on the road due to the increased congestion. Based on the macroscopic fundamental diagrams of different road segments in the road network, this impact can be quantified as the marginal social time cost. This cost can be considered as a measure of individual vehicle’s contribution to congestion, and used as part of the cost in the shortest-path algorithm. A trade-off is made between being extremely selfish and extremely cooperative.