基于延迟函数次梯度启发式道路交通补偿策略

拥挤收费被认为是解决交通拥挤的有效方法，解决道路交通拥堵的主要想法是，对于有些容易造成拥堵的道路进行收费，而对于其他未充分利用的道路进行适当补偿，对此提出一种基于延迟函数的次梯度启发式道路交通补偿策略。首先，给出道路集的收费/补贴的非线性规划模型，主要是基于Beckmann最小化目标函数实现，然后利用库恩-希尔斯条件和拉格朗日乘子建立模型的条件约束；其次，基于启发式算法建立道路交通的定价补偿策略，利用边际成本建立延迟函数分析模型，然后基于次梯度法进行模型的优化；最后，通过在真实道路网络上的仿真实验，显示所提算法在旅行时间、交通流量、收敛性等指标上均具有较好的性能，验证了算法的有效性。

Subgradient heuristic method for road traffic compensation based on delay function

This paper considers the congestion pricing to be the effective way to solve the traffic congestion, the main idea of road traffic congestion is to charge for some easy to cause road congestion, and appropriate compensation for other underutilized roads, and here presents a subgradient heuristic traffic delay compensation strategy based on function. Firstly, here use a nonlinear programming model in the road toll/subsidies, beckmann is the main realization based on minimizing the objective function, and uses the Kuhn hills-Lagrange multiplier model to construct the constraint condition; Secondly, the algorithm uses the pricing compensation strategy to establish the road traffic model based on heuristic algorithm, and also uses the marginal cost model to establish the delay function analysis model. Finally, the simulation experiments on real road networks show that the proposed algorithm has better performance in terms of travel time, traffic flow, convergence and so on, and the effectiveness of the proposed algorithm is verified.