A campus bus network design and evaluation, taking Tsinghua University as an example, is investigated in this paper. To minimize the total cost for both passengers and operator, the campus bus system planning in a seq...A campus bus network design and evaluation, taking Tsinghua University as an example, is investigated in this paper. To minimize the total cost for both passengers and operator, the campus bus system planning in a sequential approach is discussed, including the route network design, headway （i.e., the inverse of service frequency） optimization, and system evaluation. The improved genetic algorithm is proposed to optimize the route network based on the route property, and the impacts of the fluctuation of passenger demand and average traveling time are analyzed. The identity proportion in the headway optimization is then introduced with full consideration of its impacts. Based on the actual variety of passenger demand, a non-fixed schedule demonstrates its efficiency. VISSIM is finally adopted to simulate the campus bus system and a comprehensive evaluation system for the campus bus is developed. Compared with the current bus network and the one without considering the route property, the evaluation of the proposed approach shows an improvement of 18.7% and 10.1%, respectively. Moreover, the sequential approach shows an efficiency significance for the development of public transit systems passengers and operator. mprovement over the alternative method. It is of great n large industrial parks to decrease the total cost for both展开更多
The public transit system in Sanandaj has been under review and modification for the last several years. The goal is to reduce the traffic congestion and the share of private car usage in the city and increase the ver...The public transit system in Sanandaj has been under review and modification for the last several years. The goal is to reduce the traffic congestion and the share of private car usage in the city and increase the very low share of the public transit. The bus routes in Sanandaj are not connected. There is no connected transit network with the ability to transfer between the routes in locations outside of the downtown terminal. The routes mostly connect the downtown core directly to the peripheries without providing travel options for passengers between peripheries. Although there has been some improvement in the transit system, lack of service in many populated districts of Sanandaj and town nearby makes the transit system unpopular and unreliable. This research is an attempt to provide solutions for the transit network design (TND) problem in Sanandaj using the capabilities of GIS and artificial intelligence methods. GIS offers several tools that enable the decision-makers to investigate the spatial correlations between different features. One of the contributions of this research is developing a transit network design with utilizing a spectrum of GIS software modeling functionalities. The visual ability of GIS is used to generate TNDs. Many studies focus on artificial intelligence as the main method to generate the TNDs, but the focus of this research is to combine GIS and artificial intelligence capabilities in order to generate a multi-objective GIS-based procedure to construct different bus network designs and explore and evaluate them to find the suitable transit network alternative.展开更多
基金supported by the National Natural Science Foundation of China (No.61673233)Beijing Municipal Science and Technology Program (No.D15110900280000)
文摘A campus bus network design and evaluation, taking Tsinghua University as an example, is investigated in this paper. To minimize the total cost for both passengers and operator, the campus bus system planning in a sequential approach is discussed, including the route network design, headway （i.e., the inverse of service frequency） optimization, and system evaluation. The improved genetic algorithm is proposed to optimize the route network based on the route property, and the impacts of the fluctuation of passenger demand and average traveling time are analyzed. The identity proportion in the headway optimization is then introduced with full consideration of its impacts. Based on the actual variety of passenger demand, a non-fixed schedule demonstrates its efficiency. VISSIM is finally adopted to simulate the campus bus system and a comprehensive evaluation system for the campus bus is developed. Compared with the current bus network and the one without considering the route property, the evaluation of the proposed approach shows an improvement of 18.7% and 10.1%, respectively. Moreover, the sequential approach shows an efficiency significance for the development of public transit systems passengers and operator. mprovement over the alternative method. It is of great n large industrial parks to decrease the total cost for both
文摘The public transit system in Sanandaj has been under review and modification for the last several years. The goal is to reduce the traffic congestion and the share of private car usage in the city and increase the very low share of the public transit. The bus routes in Sanandaj are not connected. There is no connected transit network with the ability to transfer between the routes in locations outside of the downtown terminal. The routes mostly connect the downtown core directly to the peripheries without providing travel options for passengers between peripheries. Although there has been some improvement in the transit system, lack of service in many populated districts of Sanandaj and town nearby makes the transit system unpopular and unreliable. This research is an attempt to provide solutions for the transit network design (TND) problem in Sanandaj using the capabilities of GIS and artificial intelligence methods. GIS offers several tools that enable the decision-makers to investigate the spatial correlations between different features. One of the contributions of this research is developing a transit network design with utilizing a spectrum of GIS software modeling functionalities. The visual ability of GIS is used to generate TNDs. Many studies focus on artificial intelligence as the main method to generate the TNDs, but the focus of this research is to combine GIS and artificial intelligence capabilities in order to generate a multi-objective GIS-based procedure to construct different bus network designs and explore and evaluate them to find the suitable transit network alternative.
