基于大数据的城市尾号限行方案设计与评估研究

为提升城市尾号限行方案设计与评估决策水平，制定了统一规范的设计流程，将出行目的分为基家工作、基家上学、基家购物、基家其他、非基家出行等5类，建立了交通方式划分模型；基于层次分析法以路网运行车速、拥堵里程、改善路段数量、节点改善数量、流量均衡、实施难度等6项指标，建立路网运行评价模型，实现了各评价指标的量化分析.依托重庆主城区交通大数据，以重庆为案例进行了实例验证，结果表明：重庆交管部门根据评估最优方案进行了实施，桥梁限行实施后，实际运行车速和拥堵里程分别为23.8 km/h，171 km；模型预测相对误差分别为2.9%，5.2%；预测精度较高，达到了实际应用要求，可为其他城市尾号限行提供一定借鉴.

Design and Evaluation of City Tail Number Limit Scheme Based on Big Data

In order to improve the design and evaluation level of the city car tail number limit plan, a unified and standardized design process is formulated. The travel purposes are divided into five categories, such as home basic work, home basic school, home basic shopping, home basic other and basic family and non-home base trip. The road network operation evaluation model is established by 6 indexes, such as the distance, the improvement of the number of the sections, the quantity of the node improvement, the balance of the flow and the difficulty of implementation. The quantitative analysis of the evaluation indexes is realized. The proposed model is verified based on the large traffic data in Chongqing. The results show that the Chongqing management department has implemented the best plan according to the evaluation. After the implementation of the scheme, the actual running speed and the congestion mileage of the bridge are 23.8 km/h and 171 km. The relative error of the model prediction is 2.9% and 5.2% . The prediction accuracy is high, and the practical application requirements are reached, which can provide a certain reference for other city tail number limit.