Mitigating network traffic congestion via link- and path-based incentives
研究了在预算约束下，基于链路和路径的激励措施如何缓解城市交通网络拥堵，发现路径激励比链路激励更能将用户均衡流转向系统最优，并提出了高效的列生成迭代求解算法。
This study investigates the potential of link- and path-based incentives to mitigate congestion in urban transportation networks under a budget constraint. Both incentive schemes are formulated as non-linear optimisation problems with complementarity constraints. Mathematically, it is demonstrated that the feasible region of the link-based model is a subset of the feasible region of the path-based model under the same budget constraint. Consequently, path-based incentives exhibit greater potential to shift the user equilibrium flow pattern toward the system optimum compared to link incentives. A column generation-based iterative solution technique, which generates new paths at each iteration, is devised to efficiently solve both optimisation problems. Numerical experiments conducted for various transport networks also highlight the efficiency and scalability of the proposed algorithm, and the superiority of path-based incentives in reducing total travel time in urban transportation networks.