Development of a Computational System to Determine the Optimal Bus-stop Spacing in order to Minimize the Travel Time of All Passengers

2011 ◽  
pp. 15-25
Author(s):  
Homero F. Oliveira ◽  
Mirian B. Gonçalves ◽  
Eduardo S. Cursi ◽  
Antonio G. Novaes
Mathematics ◽  
2019 ◽  
Vol 7 (7) ◽  
pp. 625
Author(s):  
Cheng ◽  
Zhao ◽  
Zhang

The purpose of this study is to create a bi-level programming model for the optimal bus stop spacing of a bus rapid transit (BRT) system, to ensure simultaneous coordination and consider the interests of bus companies and passengers. The top-level model attempts to optimize and determine optimal bus stop spacing to minimize the equivalent costs, including wait, in-vehicle, walk, and operator costs, while the bottom-level model reveals the relation between the locations of stops and spatial service coverage to attract an increasing number of passengers. A case study of Chengdu, by making use of a genetic algorithm, is presented to highlight the validity and practicability of the proposed model and analyze the sensitivity of the coverage coefficient, headway, and speed with different spacing between bus stops.


2017 ◽  
Vol 98 (1-2) ◽  
pp. 15-23 ◽  
Author(s):  
Amita Johar ◽  
S. S. Jain ◽  
P. k. Garg

Author(s):  
Peter G. Furth ◽  
Adam B. Rahbee

A discrete approach was used to model the impacts of changing bus-stop spacing on a bus route. Among the impacts were delays to through riders, increased operating cost because of stopping delays, and shorter walking times perpendicular to the route. Every intersection along the route was treated as a candidate stop location. A simple geographic model was used to distribute the demand observed at existing stops to cross-streets and parallel streets in the route service area, resulting in a demand distribution that included concentrated and distributed demands. An efficient, dynamic programming algorithm was used to determine the optimal bus-stop locations. The model was compared with the continuum approach used in previous studies. A bus route in Boston was modeled, in which the optimal solution was an average stop spacing of 400 m (4 stops/mi), in sharp contrast to the existing average spacing of 200 m (8 stops/mi). The model may also be used to evaluate the impacts of adding, removing, or relocating selected stops.


Author(s):  
Ángel Ibeas ◽  
Luigi dell’Olio ◽  
Borja Alonso ◽  
Olivia Sainz

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