The Research On Intelligent Optimization Of Bus Timetable Based On Passenger Flow Data

With the development of the economy and the intensification of urbanization,urban public transportation is facing serious traffic congestion,frequent traffic accidents,severe air pollution and many other problems.How to establish an efficient and reasonable operation and dispatching management system for public transport enterprises is the core issue for improving the level of public transport services.The establishment of bus schedules is an indispensable element in the operation and dispatch management system of bus companies.The core of making the timetable is to determine the departure interval of the bus.The main determinant of the departure interval is the size and spatial distribution of bus passenger flow.In order to achieve a win-win situation for both enterprises and passengers,it is important to establish a bus interval optimization model that meets the needs of passenger flow changes and satisfies the optimal passenger and enterprise benefits.Regarding the problem of timetable optimization,the typical approach is to divide the whole day into several time periods,and solve an equal time interval within each time period.In most papers,the length of the time period is too long,and it is difficult to ensure that the passenger flow is stable in the time period.This article takes one hour as the length of the time period,and solves the optimal departure interval in each time period.Theoretical analysis shows that the time periods are independent of each other,and the time interval within the time period can be solved by exhaustive method.In addition,an improved binary particle swarm optimization algorithm is used to solve the problem,and the experimental results are consistent with the analysis results.Although the timetable optimization problem with equal time intervals can be obtained by the exhaustive method,the premise is that the method needs to divide the time periods to ensure that the passenger flow is stable in each time period.The time division method is the difficulty of this problem.Therefore,this paper proposes a timetable optimization problem for unequal time intervals throughout the day,avoids the division of time periods,and directly solves the timetable that meets the changes in passenger flow.Optimizing bus timetables with unequal intervals is much more complex than the optimization of timetables with equal time intervals.In this paper,we propose a bus timetable optimization approach based on a memetic algorithm(BTOA-MA)to optimize a bus timetable with unequal time intervals.The validity of the algorithm is verified with real public transit data from two cities.The results show that the optimized timetable can reduce the operating costs of enterprises and improve the service quality of buses.