运输结构调整政策对区域路网重型货车流量的影响评估

Impact assessment of transportation structure adjustment policy on heavy-duty truck traffic flow in regional road network

针对区域路网重型货车流量受运输结构调整政策影响的问题,依托重型货车交通流大数据,以交通需求预测四阶段法为建模思路,引入神经网络模型和遗传算法等数据驱动方法,建立了“2+26”城市区域交通发生吸引量反推模型和交通流分配算法,形成了区域货运交通流时空分布模型.结果表明:运输结构调整政策全面实施后路网流量与基础年流量(2017年)相比,“2+26”城市区域路网重型货车年平均日交通量减少100辆、年平均日行驶量减少751万车·km.实际观测数据显示,“2+26”城市港口、大型工矿企业等关键节点周边道路重型货车流量普遍下降.“公转铁”政策对于区域大气污染防治具有良好潜力,后续应加快完善相关制度,协同推进运输结构调整与柴油货车污染治理工作.

To assess the impact of the transportation structure adjustment policy on the heavy-duty truck traffic flow in regional road network, based on the heavy-duty truck traffic flow big data, a temporal and spatial distribution model of heavy-duty truck traffic flow is established in “2+26” cities. The model is based on the four-stage method of traffic demand forecasting, which innovatively introduced data-driven methods such as neural network model and genetic algorithm to form the backpropagation model for trip attraction and traffic flow allocation algorithms. The results show that after the full implementation of transportation structure adjustment policy, the annual average daily traffic volume of heavy-duty trucks in “2+26” cities drops 100 and the annual average daily driving volume decreases 7.51 million kilometers compared with that in 2017. The observed data indicates that heavy-duty truck traffic flow on the surrounding roads at key nodes such as ports and large industrial and mining enterprises generally decrease in “2+26” cities. Overall, “truck-to-rail” freight modal shifts have good potential for regional air pollution control. Therefore, further efforts should be made to promote the transportation structure adjustment and diesel trucks pollution control.