基于时变二源数据的城市公交调度协调模型与算法
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摘要
现代化社会经济的发展客观上要求各种公共交通方式实现有效衔接,从而最大限度地提高公共交通的吸引力。城市公交动态调度协调相对于静态调度协调,能够考虑乘客需求的时变性和公交运行的不确定性,因此,成为公共交通研究领域的热点问题。然而,由于调度问题的复杂性,目前公交动态调度协调多是针对突发事件的行车控制策略研究,并且作为动态调度协调的关键技术,动态客流OD估算和公交车辆行程时间预测多是独立研究。缺乏面向实际应用、综合考虑公交多源时变数据的调度协调模型。
在此背景下,本文提出了基于时变二源数据的城市公交调度协调模型和算法。首先,从公交静、动态调度模型,公交动态调度相关问题,对国内外现有的研究进行了全面综述。在综述的基础上,开展了如下的研究工作。
第一,针对公交二源数据,开展了数据质量控制研究。提出了公交IC卡数据质量控制方法、基于乘车站距分布的公交线路OD扩样模型和面向调度应用的公交GPS数据质量控制模型。
第二,针对公交调度协调的关键问题,本文提出了一票制线路上、下车站点判别方法,开发了基于状态空间模型的公交客流短时预测方法,根据公交车辆行程时间状态判别,建立了不同行程时间状态下的公交车辆行程时间预测模型。
第三,在以上研究的基础上,本文建立了基于时变二源数据的公交调度协调模型,并提出了基于NSGA-Π算法的模型求解流程。在模型建立中,考虑了运营商成本、拥挤里程比例和换乘乘客平均候车时间三个目标函数。对于拥挤里程比例,考虑了线路整体拥挤里程比例和个体出行者所能忍受的拥挤出行站数。对于轨道交通换乘常规公交平均候车时间,通过分析直接换乘乘客和非直接换乘乘客的到站时间分布,建立了基于对数正态和伽马分布的轨道交通换乘常规公交平均候车时间模型。
第四,本文应用所建立的公交调度协调模型和算法,选择北京城铁立水桥站进行了实例分析,并将模型求解结果与传统方法求解结果进行了比较,结果表明：与传统计算法方法相比,本文建立的基于时变二源数据的公交调度协调模型平均运营成本增加了10.50%；但是,平均拥挤里程比例和换乘平均候车时间均有较大幅度改善,平均拥挤里程比例降低幅度为75.63%,换乘平均候车时间减少幅度为20.05%。并且,在用传统方法计算各线路时刻表时,没有考虑出行个体的满意度。比较结果表明,本文提出的方法,在提高公交出行服务水平方面,更具优势。
最后,对于动态客流OD时间粒度问题、公交调度协调模型的软件开发和工程应用问题等方面提出了进一步的研究展望和建议。
The modern socio-economic development requires an effective coordination between all public transit modes to maximize the enhancement of its attractiveness. In comparison with the static dispatching coordination of the urban public transit system, the dynamic dispatching coordination can incorporate the consideration of the time-varying nature of the passenger demand as well as the uncertainty of public transit operations. As such, it has become a hot research issue in the field of the public transit. However, due to the complexity of the dispatching, the existing dynamic dispatching coordination of the public transit has mostly focused on the study of vehicle control strategies at the emergency. Moreover, in spite of being the key techniques for the dynamic dispatching coordination, the dynamic passenger origin-destination (OD) demand estimation and bus travel time prediction have been studied independently. Thus, there is a lack of effective application-oriented dispatching coordination models incorporating time-varying multiple sources of data.
In this context, the research in this dissertation develops dispatching coordination models and algorithms for urban public transit based on the time-varying dual sources of data. First, the dissertation synthesizes state-of-the-art on both static and dynamic bus dispatching models, and the relevant problems. Then, it conducts the following research work:
First, it conducts the study on the data quality control for the public transit dual sources of data. It develops public transit IC card data quality control models, the bus route OD sampling expansion models based on the distribution of riding distance, and the public transit GPS data quality control models towards the application to the dispatching.
Second, with respect to the key techniques of the public transit dispatching coordination, it develops the method for identifying boarding and alighting stations for flat fare lines, as well as a short-term transit ridership forecasting model based on the state-spacial model. It further develops the bus travel time prediction models based on an identification of the state of the bus travel time.
Third, it develops the public transit dispatching coordination model based on time-varying dual sources of data, as well as the model solution procedure based on the NSGA-Πalgorithm. The model is developed by incorporating the consideration of three objective functions, the supplier cost, the proportion of congested mileage, and the average waiting time for transferring passengers. In the modeling of the average waiting time for passengers to transfer from rail transit to buses, the arrival rate distributions of direct transfer passengers and non-direct transfer passengers are first analyzed. Then, an average waiting time model for transferring passengers is developed based on the lognormal and gamma distributions.
Fourth, the proposed models and algorithms are applied to the case study of the dispatching coordination of Lishuiqiao station in Beijing. The results calculated using the proposed models are compared with the results obtained from the traditional method. It is demonstrated that, comparing with the results calculated from the traditional method, the average supplier-cost based on the proposed models increases by 10.50% while the the proportion of congested mileage decreases by 75.63%, and the average waiting time decreases by 20.05%. Therefore, the proposed model in this dissertation performs better in improving the overall quality of the transit service.
Finally, it provides recommendations on the time intervals of the public transit dynamic OD, and the development of software and engineering applications of the proposed dispatching coordination models.
在此背景下,本文提出了基于时变二源数据的城市公交调度协调模型和算法。首先,从公交静、动态调度模型,公交动态调度相关问题,对国内外现有的研究进行了全面综述。在综述的基础上,开展了如下的研究工作。
第一,针对公交二源数据,开展了数据质量控制研究。提出了公交IC卡数据质量控制方法、基于乘车站距分布的公交线路OD扩样模型和面向调度应用的公交GPS数据质量控制模型。
第二,针对公交调度协调的关键问题,本文提出了一票制线路上、下车站点判别方法,开发了基于状态空间模型的公交客流短时预测方法,根据公交车辆行程时间状态判别,建立了不同行程时间状态下的公交车辆行程时间预测模型。
第三,在以上研究的基础上,本文建立了基于时变二源数据的公交调度协调模型,并提出了基于NSGA-Π算法的模型求解流程。在模型建立中,考虑了运营商成本、拥挤里程比例和换乘乘客平均候车时间三个目标函数。对于拥挤里程比例,考虑了线路整体拥挤里程比例和个体出行者所能忍受的拥挤出行站数。对于轨道交通换乘常规公交平均候车时间,通过分析直接换乘乘客和非直接换乘乘客的到站时间分布,建立了基于对数正态和伽马分布的轨道交通换乘常规公交平均候车时间模型。
第四,本文应用所建立的公交调度协调模型和算法,选择北京城铁立水桥站进行了实例分析,并将模型求解结果与传统方法求解结果进行了比较,结果表明：与传统计算法方法相比,本文建立的基于时变二源数据的公交调度协调模型平均运营成本增加了10.50%；但是,平均拥挤里程比例和换乘平均候车时间均有较大幅度改善,平均拥挤里程比例降低幅度为75.63%,换乘平均候车时间减少幅度为20.05%。并且,在用传统方法计算各线路时刻表时,没有考虑出行个体的满意度。比较结果表明,本文提出的方法,在提高公交出行服务水平方面,更具优势。
最后,对于动态客流OD时间粒度问题、公交调度协调模型的软件开发和工程应用问题等方面提出了进一步的研究展望和建议。
The modern socio-economic development requires an effective coordination between all public transit modes to maximize the enhancement of its attractiveness. In comparison with the static dispatching coordination of the urban public transit system, the dynamic dispatching coordination can incorporate the consideration of the time-varying nature of the passenger demand as well as the uncertainty of public transit operations. As such, it has become a hot research issue in the field of the public transit. However, due to the complexity of the dispatching, the existing dynamic dispatching coordination of the public transit has mostly focused on the study of vehicle control strategies at the emergency. Moreover, in spite of being the key techniques for the dynamic dispatching coordination, the dynamic passenger origin-destination (OD) demand estimation and bus travel time prediction have been studied independently. Thus, there is a lack of effective application-oriented dispatching coordination models incorporating time-varying multiple sources of data.
In this context, the research in this dissertation develops dispatching coordination models and algorithms for urban public transit based on the time-varying dual sources of data. First, the dissertation synthesizes state-of-the-art on both static and dynamic bus dispatching models, and the relevant problems. Then, it conducts the following research work:
First, it conducts the study on the data quality control for the public transit dual sources of data. It develops public transit IC card data quality control models, the bus route OD sampling expansion models based on the distribution of riding distance, and the public transit GPS data quality control models towards the application to the dispatching.
Second, with respect to the key techniques of the public transit dispatching coordination, it develops the method for identifying boarding and alighting stations for flat fare lines, as well as a short-term transit ridership forecasting model based on the state-spacial model. It further develops the bus travel time prediction models based on an identification of the state of the bus travel time.
Third, it develops the public transit dispatching coordination model based on time-varying dual sources of data, as well as the model solution procedure based on the NSGA-Πalgorithm. The model is developed by incorporating the consideration of three objective functions, the supplier cost, the proportion of congested mileage, and the average waiting time for transferring passengers. In the modeling of the average waiting time for passengers to transfer from rail transit to buses, the arrival rate distributions of direct transfer passengers and non-direct transfer passengers are first analyzed. Then, an average waiting time model for transferring passengers is developed based on the lognormal and gamma distributions.
Fourth, the proposed models and algorithms are applied to the case study of the dispatching coordination of Lishuiqiao station in Beijing. The results calculated using the proposed models are compared with the results obtained from the traditional method. It is demonstrated that, comparing with the results calculated from the traditional method, the average supplier-cost based on the proposed models increases by 10.50% while the the proportion of congested mileage decreases by 75.63%, and the average waiting time decreases by 20.05%. Therefore, the proposed model in this dissertation performs better in improving the overall quality of the transit service.
Finally, it provides recommendations on the time intervals of the public transit dynamic OD, and the development of software and engineering applications of the proposed dispatching coordination models.
引文
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