Customized Bus Line Design Model Based on Multi-Source Data

Customized bus (CB) system is a new type of public transport service that offers a personalized and flexible travel pattern. The CB system aims to enable private car users to select public transportation to alleviate heavy traffic conditions in large- and medium-sized cities. The design of a bus line, as part of the CB system, is an important procedure because this design is the basis of other planning and operation processes, such as timetable planning, vehicle scheduling, and crew scheduling. Currently, most of the existing CB line design models are established based on a single source of data, such as survey or taxi trajectories data. However, data from a single source may inaccurately estimate the real travel demands for the CB systems. In this paper, a data-driven CB line design model is proposed based on multi-source data, that is, transit smart card, GPS, and mobile sensor data, to maximize demands coverage and minimize travel cost of all passengers. A genetic algorithm is designed to solve the model that can obtain the alternative CB lines. Hangzhou City in China is selected as the case study. Results show that the existing CB system of Hangzhou can be improved through the proposed method. This work can be a practical guide to enhancing the quality of public transportation services.