近些年，共享出行正在冲击和改变传统的交通出行方式。共享出行既不需要新建交通基础设施，还可减少交通网络中的汽车使用数量，对缓解交通拥堵产生积极作用。本项目综合运用交通科学、微观经济学、行为科学、优化方法和博弈论等多学科知识，构建考虑用户出行时间价值异质性和共享出行偏好异质性的新型交通均衡分配模型，设计有效的模型求解算法，并开展不同共享出行政策下的路径选择行为实验，利用“滴滴出行”提供的盖亚数据挖掘司机和乘客的出行特征和规律。本研究拓展传统的交通均衡分配模型，为共享出行平台建设提供理论和技术支持，为城市交通需求管理提供政策建议，为缓解城市交通拥堵、提高车辆和道路使用率做出积极贡献。

Ridesharing, which can significantly reduce the number of vehicles on road networks and thus relieve the urban traffic congestion without new network infrastructures, has been changing the traditional transport modes over the past few years. Combined with cross-disciplinary knowledge from transportation science, microeconomics, behavioral science, optimization methods, and game theory, this project proposes several new ridesharing user equilibrium models with heterogeneous travelers (including different value of times and different ridesharing preferences), develops efficient solution algorithms for these proposed models, conducts laboratory experiments for route choice under different ridesharing transport policies, and excavates travel behavior characteristics and regularity of ridesharing drivers and passengers with the data provided freely by “Didi Chuxing”. This research will enrich the existing traffic equilibrium assignment models, provide theoretical and technical support for ridesharing platform construction, make policy suggestions for urban traffic demand management, and contribute to reducing urban traffic congestion and increasing the use efficiency of existing vehicles and urban road networks.