考虑组合出行行程时间可靠度的多模式交通规划模型与方法

Travel time reliability (TTR), as a key factor affecting travelers’ choice behavior, plays an increasingly important role in transport planning and management. Existing TTR models are mainly a-signle-traffic-mode oriented, which cannot capture the travelers’ distinct risk prefrences and differences in perveived travel time unreliability of different traffic modes with a combined-mode travel. For instance, travelers will overestimate the waiting time at the train station and underestimate the delay by car. Without a proper TTR model for combined-mode trips, the travel choice behavior, especially the mode choice, cannot be modeled correctly. It will lead to significant errors in demand forecasting for multimodal transport system planning. This project aims to quantify travelers’ distinct risk prefrences and differences in their perveived travel time unreliability of different modes, to explore the mechanism of TTR of Combined-mode trips, and to set up new models and improved methodology for multimodal transport planning. The data collection is aimed to capture the distinctions among travelers’ risk prefrences and is designed with a unitility-balanced principle. With the collected data, the risk preference theory is utilized to reveal the mechanism of travel time unreliability of combined-mode trips. The risk assessment technique is applied to integrate the unrelialbity of the associated modes, which leads to the TTR model for a combined-mode trip. The established TTR model of combined-mode trips will be incorporated into the choice behavioral modeling for travelers, based on which a combined-mode choice behavioral model will be developed. Then a multimodal traffic assignment model will be established by considering the TTR of combined-mode trips, with which the impacts of considering TTR of combined modes on mode split could be analyzed. A bi-level formulation will be employed to formulate the plannning problem as an optimization problem, contrained to the lower level of the TTR-based multimodal traffic assignment model. The decision variables could be the location of any tranfering station, etc. Finally, the developed TTR-based approach will be applied for the planning of a real multimpodal transportat system. This research also contributes in extending the research area of travel time reliability by exploring TTR for combined-mode trips.

行程时间可靠度对出行选择行为影响显著。但目前的研究以单一交通方式为主，没有刻画多模式出行链的组合出行可靠度机理，忽略了描述出行者对不同交通方式的可靠度风险偏好和高估公共交通延误等感知差异性，难以揭示组合出行行为规律和本质，导致了组合出行需求预测失准等多模式交通规划问题。本项目旨在量化评估出行者对不同交通方式可靠度的感知差异性和风险偏好，揭示组合出行行程时间可靠度机理，构建多模式交通规划的新模型与新方法。研究以效用平衡为原则、以表征风险偏好为主要目标的数据采集方法，分阶段获取组合出行行为数据；利用风险偏好理论和风险评估等技术，开展组合出行的行程时间可靠度机理解析、行为规律揭示、可靠度模型和行为模型的构建，由此建立考虑组合出行行程时间可靠度的多模式交通分配模型与多模式交通规划方法，开展实证研究和模型验证。预期成果可为科学地规划和配置多模式交通资源提供理论支撑，并将拓展行程时间可靠度理论研究。

行程时间可靠度是影响出行选择行为的重要因素，忽略刻画出行者对不同交通方式可靠度风险偏好，将难以揭示组合出行行为规律和本质，导致交通需求预测失准等问题。本项目针对包含多种交通方式和多影响因素的复杂场景设计问题，创新性提出了D-efficient基于效用平衡理论的行为调查设计方法，保证了各属性水平在所有场景中均以相同概率出现，利用面对面调查方法采集了2316个有效多模式交通场景和6096个有效组合出行交通场景的行为数据，分别采用多项logit模型、巢式logit模型、混合logit模型和非参数估计模型进行了出行行为规律分析，揭示了多模式交通出行和组合出行的行程时间可靠度机理，并对出行者的出行选择风险态度进行了聚类分析，由此探讨了不同风险态度出行者组合出行行为规律。.研究表明：1）无论在多模式交通中，还是在组合出行链中，出行者都对不同交通方式的行程时间可靠度和车内拥挤度存在显著的感知差异性；2）多模式交通出行中，出行者对公交车的车内拥挤度和对地铁的行程时间可靠度出行选择敏感性高；3）停车换乘组合出行中，小汽车的行程时间可靠度价值高于地铁，但地铁的车内拥挤度价值高于小汽车；4）公交换乘地铁组合出行中，出行者更注重公交车的行程时间可靠度和地铁的车内拥挤度；5）不同风险态度下出行者的组合出行行为存在明显差异性，随着风险态度由规避转为偏好，公交车拥挤度价值与地铁的车内拥挤度价值的比值逐渐降低；6）出行者对组合出行与多模式交通出行的行程时间可靠度和车内拥挤度价值存在显著感知差异性。.基于解析的组合出行行为机理建立了考虑组合出行行程时间可靠度的多模式交通规划的新模型与新方法，并基于实际出行行为数据验证了新模型的有效性和可靠性。研究成果拓展了行程时间可靠度理论研究，为科学地规划和配置多模式交通资源提供了有力支撑。