Abstract
With the advantages of congestion alleviation, environmental friendliness, as well as a better travel experience, the customized bus (CB) system to reduce individual motorized travel is highly popular in increasing numbers of cities in China. The line planning problem is a key aspect of the CB system. This paper presents a detailed flow chart of a CB network planning methodology, including individual reservation travel demand data processing, CB line origin–destination (OD) area division considering quantity constraints of demand in areas and distance constraints based on agglomerative hierarchical clustering (AHC), an initial set of CB lines generating quantity constraints of the demand on each line and line length constraints, and line selection model building, striking a balance between operator interests, social benefits, and passengers’ interests. Finally, the impacts of the CB vehicle type, the fixed operation cost of online car-hailing (OCH), and the weights of each itemized cost are discussed. Serval operating schemes for the Beijing CB network were created. The results show that the combination of CB vehicles with 49 seats and 18 seats is the most cost-effective and that CBs with low capacity are more cost-effective than those with larger capacity. People receive the best service when decision-makers pay more attention to environmental pollution and congestion issues. The CB network’s service acceptance rate and the spatial coverage increase with the fixed operating cost per OCH vehicle per day c0C. The CB vehicle use decreases as c0C ccincreases. The results of this study can provide technical support for CB operators who design CB networks.
Highlights
The public transport service is facing problems with overcrowding, low punctuality, and the amount of time taken to travel in peak periods, which greatly affect the satisfaction of passengers with the public transport service and reduces the attraction of public transport
Our contributions are as follows: (1) based on hierarchical clustering, the customized bus (CB) network is planned using online car-hailing (OCH) data; (2) in the four steps of CB network planning, line length and minimum demand constraints are proposed to reduce computational redundancy; and (3) based on the line selection model proposed by Ma et al [11], the cost factors are improved, and a model considering multiple CB vehicles types is constructed
We made the following assumptions in this study: (1) passengers travel by either CBs or OCH; (2) each bus only runs one route and starts from the origin area and ends in the destination area; (3) passengers can only board in the origin areas and alight in the destination areas; and (4) the CB line length is represented by the average travel distance of all the travel demands on this line
Summary
The public transport service is facing problems with overcrowding, low punctuality, and the amount of time taken to travel in peak periods, which greatly affect the satisfaction of passengers with the public transport service and reduces the attraction of public transport. Our contributions are as follows: (1) based on hierarchical clustering, the CB network is planned using OCH data; (2) in the four steps of CB network planning, line length and minimum demand constraints are proposed to reduce computational redundancy; and (3) based on the line selection model proposed by Ma et al [11], the cost factors are improved, and a model considering multiple CB vehicles types is constructed. We made the following assumptions in this study: (1) passengers travel by either CBs or OCH; (2) each bus only runs one route and starts from the origin area and ends in the destination area; (3) passengers can only board in the origin areas and alight in the destination areas; and (4) the CB line length is represented by the average travel distance of all the travel demands on this line. The sets, indices, and parameters used in this study are listed in the Appendix A
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