Campus Bus Network Design and Evaluation Based on the Route Property

: A campus bus network design and evaluation, taking Tsinghua University as an example, is investigated in this paper. To minimize the total cost for both passengers and operator, the campus bus system planning in a sequential approach is discussed, including the route network design, headway (i.e., the inverse of service frequency) optimization, and system evaluation. The improved genetic algorithm is proposed to optimize the route network based on the route property, and the impacts of the fluctuation of passenger demand and average traveling time are analyzed. The identity proportion in the headway optimization is then introduced with full consideration of its impacts. Based on the actual variety of passenger demand, a non-fixed schedule demonstrates its efficiency. VISSIM is finally adopted to simulate the campus bus system and a comprehensive evaluation system for the campus bus is developed. Compared with the current bus network and the one without considering the route property, the evaluation of the proposed approach shows an improvement of 18.7% and 10.1%, respectively. Moreover, the sequential approach shows an efficiency improvement over the alternative method. It is of great significance for the development of public transit systems in large industrial parks to decrease the total cost for both passengers and operator.

[1]  Hai Wan,et al.  Probabilistic modeling and optimization of Real-Time Protocol for Multifunction Vehicle Bus , 2016 .

[2]  Renato Oliveira Arbex,et al.  Efficient transit network design and frequencies setting multi-objective optimization by alternating objective genetic algorithm , 2015 .

[3]  Héctor Cancela,et al.  Mathematical programming formulations for transit network design , 2015 .

[4]  Ziyou Gao,et al.  A bi-level programming for bus lane network design , 2015 .

[5]  Steven I-Jy Chien,et al.  Investigating the impact of stochastic vehicle arrivals to optimal stop spacing and headway for a feeder bus route , 2015 .

[6]  Avishai Ceder,et al.  Optimal Modification of Urban Bus Network Routes Using a Genetic Algorithm , 2015 .

[7]  Avishai Ceder,et al.  Designing large-scale bus network with seasonal variations of demand , 2014 .

[8]  Ping Hu,et al.  Transit network design based on travel time reliability , 2014 .

[9]  Jen-Jia Lin,et al.  Optimization of a feeder-bus route design by using a multiobjective programming approach , 2014 .

[10]  Hong Kong,et al.  A Simultaneous Bus Route Design and Frequency Setting Problem for Tin Shui Wai , Hong Kong , 2011 .

[11]  Matthew G. Karlaftis,et al.  Transit Route Network Design Problem: Review , 2009 .

[12]  Fang Zhao,et al.  Optimization of transit route network, vehicle headways and timetables for large-scale transit networks , 2008, Eur. J. Oper. Res..

[13]  Wei Guan,et al.  Study on Bus Route Evaluation System in Beijing Based on AHP , 2007, 2007 IEEE Intelligent Transportation Systems Conference.

[14]  Dušan Teodorović,et al.  Performance evaluation of bus routes: A provider and passenger perspective , 2007 .

[15]  Randy B Machemehl,et al.  Optimal Transit Route Network Design Problem with Variable Transit Demand: Genetic Algorithm Approach , 2006 .

[16]  Partha Chakroborty,et al.  Genetic Algorithms for Optimal Urban Transit Network Design , 2003 .

[17]  Steven I-Jy Chien,et al.  GENETIC ALGORITHM APPROACH FOR TRANSIT ROUTE PLANNING AND DESIGN , 2001 .