Application of Traffic Weighted Multi-Maps Based on Disjoint Routing Areas for Static Traffic Assignment

Abstract

Urban traffic congestion is a pressing issue, demanding effective and cost-efficient solutions. This paper develops the Traffic Weighted Multi-Maps (TWM) method to solve the Traffic Assignment Problem in Intelligent Transportation Systems (ITS). TWM offers drivers diverse views of the network, promoting path diversity and adaptability. Providing an optimal TWM configuration to the traffic demand in terms of structure and allocation policy is a challenging issue as it usually depends on the size of the network and its complexity. The paper explores TWM generation and assignment by applying routing areas based on semi-disjointed k-shortest paths and allocating them using a per-sub flow optimized assignment policy. This approach allows obtaining a pseudo-optimal solution for static traffic assignment with similar results in terms of total travel time compared to the direct solution of calculating optimal map weights and the theoretical system optimum. It offers a cost-effective solution valid for wide urban areas, as the TWM calculation depends on the variety of the traffic flows and the number of semi-disjoint routing areas considered instead of the network complexity and size. Urban network experiments with synthetic traffic demands are studied under different TWM adoption rates, comparing results with existing traffic assignment policies and estimation methods. It highlights its potential for enhancing urban traffic management. Overall, TWM presents a promising approach to addressing urban traffic congestion efficiently.

Keywords

• traffic assignment
• traffic control
• vehicle routing
• intelligent transportation systems
• traffic big data
• decision making