The Effect of Variable Demand in Bus Rapid Transit Routing

The implementation of a Bus Rapid Transit (BRT) line is one option for improving publictransportation. This paper describes a method for optimising an integrated transit network route that incorporates a scalable BRT line. When optimising transit networks, the following factors should be considered: the reduction of transit line transfers and user costs, the maximisation of service areas, the fluctuating customer demand for the BRT system, the size of the transit fleet, and the street network of the transit service area. Planning an integrated transit network requires an estimate of the potential reduction in total travel time and an estimate of the increased BRT demand. This paper describes the optimisation of a route structure and transit vehicle headway using Simulated Annealing and Fast Descent optimisation problem. To estimate the increased demand from a BRT line, a heuristic algorithm was used to perform a flexibility analysis. In this research, the average user travel time is considered to be an operative parameter that consists of both travel time and total demand. These results can be evaluated based on the demand variation analysis. In all cases of study, the average user travel time increases “with demand changing without route changing,” causing occasional problems. This travel time increase may indicate that after the demand changes, the BRT route cannot remain optimised. After solving the demand variation problem and choosing a new route “with demand and route changing,” the total user travel time is reduced and provides less value than the previous result. These values are more than “without demand and route changing.” The average user travel time for “with demand and route changing” is reduced significantly. Between 3 analysed cases, the average user travel time in “with demand and route changing” has the lowest value. “With demand and route changing “reduced by 2.016%, 2.921%, and 3.021% average user travel time from without demand and route changing in variable BRT fleet size. The changes for a fixed BRT fleet size are1.041%, 1.112%, and 2.209%, demonstrating that demand variation changing works efficiently.