Optimization Method for Conventional Bus Stop Placement and the Bus Line Network Based on the Voronoi Diagram

With the rapid development of the economy, the existing conventional bus transit system finds it difficult to meet people's increasing travel needs. In addition, with the emergence and rapid development of urban rail transit, it is also necessary to integrate the existing conventional bus transit system with the rail transit system to realize the optimization of the whole public transport system. This study introduces the concept of the Voronoi diagram and uses it to divide the service area of bus stops. Taking the average walking time of regional passengers to the station as the main index, the convenience of passengers in the service area was evaluated, and a set of candidate station sites is established. Against the background of urban rail transit, a complete optimization model for a conventional bus station layout and line network was proposed. Finally, taking Wuhan East Lake High-tech Development Zone as an example, two optimization schemes for the public transport system were obtained. Compared with the status quo, the optimized scheme had obvious improvement effects on the repetition coefficient of bus lines, per capita transfer time, bus line network coverage and station service rate. This has been recognized by the local authorities, which proves the practicality and scientificity of the optimization method of this study.

Automated summary

With the rapid economic development and the rise of urban rail transit, the traditional bus transit system needs to be integrated with the rail transit system to optimize the entire public transport system. By using the concept of the Voronoi diagram, this study divides the service area of bus stops and proposes an optimization model for layout and line network. The optimized schemes for a public transport system in Wuhan East Lake High-tech Development Zone showed significant improvements compared to the current situation, proving the practicality and scientific nature of the study's optimization method.