基于出行者活动的多模式城市公交网络复杂交通行为研究

In many large cities in China such as Beijing and Shanghai, with dense land uses and congested multi-modal transit systems, a large proportion of trips are made by various transit modes for different activities. For instance, the activity behaviors include the decision of whether to perform the non-work activity or not, whether to perform it during the commuting trip or, alternatively, to pursue it making a separate trip chain from home; while the travel behaviors are related to the departure/arrival time choices, location choices of the non-work activity, the mode and route choices. However, little attention has been given to the effects of various activities on travel demands particularly in congested urban areas with mixed land uses. In order to capture the impacts of various activities on travel demand, this project proposes to develop dynamic activity-based network equilibrium models and solution algorithms for estimation of travel demands by modes in multi-modal transit system. The proposed models will explicitly take into account travelers' behaviors regarding choice of activity and duration, choice of departure time, choice of destination, choice of mode and routes under generalized utility structures. The first part of the project will make use of the available historical data to calibrate the activity and travel choice patterns. The second part will develop activity-based time-dependent network equilibrium models to solve the travelers' activity and travel choice problems with taking account the congestion effects in multi-modal transit network. Three types of models will be proposed, i.e. models for single-person activity-travel pattern, models for joint activity-travel pattern, and models under adverse weather. The third part will be the integration of the first and second partsof the project for estimation of travel demands by modes and parameter estimation of the activity/travel choice model with and without updated multi-modal transit network travel time data. The proposed project has the potential to help the transport planners and traffic engineers understand travelers' behaviors on activity and travel choices and their responses to congestion in the multi-modal transit systems. These issues are particularly important in most Asian cities with dense and mixed land-use development where various activity and travel choices are inter-related. The application of the proposed models also holds great promise for establishing the potential of using updated traffic data to develop/calibrate travel demand forecasting models with minimum recurrent effort and maximum coverage in the whole urban area of a large city in China.

在人口密集的城市地区，多模式公交系统为人们提供了便捷高效的出行方式， 有效缓解了日益增长的交通需求给城市可持续发展带来的压力。基于出行者活动的方法可 明确地考虑出行动机，将出行与活动相结合，有效地模拟多模式公交网络中出行者的复杂交通行为。本项目拟综合运用交通运筹理论、系统科学、行为科学等知识，利用基于出行者活动的方法，构造多模式时空活动超级网络，提出适用于多模式公交网络的交通模型及算法（包括针对个人出行活动的模型、针对家庭出行活动的模型，以及考虑气候因素的模型），并利用观测数据和统计调查数据对模型进行校准和验证，从而从出行者活动和出行的相关性方面准确地模拟和探究多模式公交网络中出行者的复杂行为（包括出行行为及活动行为）。本研究为城市多模式公交网络的规划和管理提供理论指导和科学依据，研究成果还具有重要的战略和政策意义，可为多模式公交系统的社会、环境和经济的可持续性评估提供先进的模型和工具。

在人口密集的城市地区，多模式公交系统为人们提供了便捷高效的出行方式，有效缓解了日益增长的交通需求给城市可持续发展带来的压力。基于出行者活动的方法可明确地考虑出行动机，将出行与活动相结合，有效地模拟多模式公交网络中出行者的复杂交通行为。本项目综合运用交通运筹理论、系统科学、行为科学等知识，利用基于出行者活动的方法，构造多模式时空活动超级网络，提出适用于多模式公交网络的交通模型及算法，并利用观测数据和统计调查数据对模型进行校准和验证，从而从出行者活动和出行的相关性方面准确地模拟和探究多模式公交网络中出行者的复杂行为（包括出行行为及活动行为）。.本项目具体研究成果如下：.（1）提出了考虑出行者不同出行活动链选择行为对土地利用和交通网络影响的双层数学规划模型，提出了求解该双层规划模型的启发式算法。.（2） 构建了“多模式时空活动超级网络”，并优化了该多模式时空活动超级网络的拓扑结构，将时空网络、多模式公交网络、出行者的活动行为、出行者的出行行为连为一体。.（3）建立了多交通方式的城市系统均衡模型，考虑出行时间不确定性对通勤者出行方式选择和家庭住宅选址的影响，分析了出行时间不确定性水平对城市系统性能的影响，及其对最优拥挤收费定价策略（包括收费水平和位置）的影响。.（4）提出了新的城市系统均衡模型来设计一种可交易的电子票税收政策，以此平衡城市系统内的交通拥挤外部性和环境外部性。.