The Simultaneous Vehicle Scheduling and Passenger Service Problem

Abstract

Passengers using public transport systems often experience waiting times when transferring between two scheduled services. In this paper we propose a planning approach that seeks to obtain a favourable trade-off between the two contrasting objectives, passenger service and operating cost, by modifying the timetable. The planning approach is referred to as the simultaneous vehicle scheduling and passenger service problem (SVSPSP). The SVSPSP is modelled as an integer programming problem and solved using a large neighborhood search metaheuristic. The proposed framework is tested on data inspired by the express-bus network in the Greater Copenhagen area. The results are encouraging and indicate a potential decrease of passenger transfer waiting times in the network of up to 20%, with the vehicle scheduling costs remaining mostly unaffected.

Planning, operation, and control of bus transport systems: A literature review

“…The later approach is a combination of previously defined tools (Ceder, 2007) to compute timetables with even loads, timetables with even headways, and vehicle schedules with minimum operational costs. Petersen et al (2013) formulate a partial integration of TNT and MDVSP minimizing the weighted sum of the costs of vehicles usage and passenger transfers. The authors consider metatrips which are a sets of trips that contains an original trip of the initial timetable and also contains the ''same trip'' but with different departure times.…”

A stochastic optimization model for transit network timetable design to mitigate the randomness of traveling time by adding slack time

“…During the transfer, passengers spend a lot of time waiting for connecting bus that serves on the line without well-designed timetable. Petersen et al (2013) reported that the waiting time for one transfer is an average of about 9.75 min on each weekday in the Greater Copenhagen area. Therefore, a well-designed timetable, with good coordination between buses so that passengers can enjoy smooth transfers with minimal delay, is quite important for an attractive bus transit service.…”

Bus service time estimation model for a curbside bus stop

“…Service time estimation could help in the estimation and prediction of bus travel time (Furth and Muller, 2007), and arrival and departure time forecasts of intelligent transportation systems could become more precise if service time at bus stops is modeled (Shalaby and Farhan, 2004;Yu et al, 2011). Service time estimation are vital to daily operations, such as bus scheduling (Petersen et al, 2012;Ceder, 2011) and headway control (Sun and Hickman, 2008;Delgado et al, 2012). Moreover, bus service time estimation plays an vital role in transit network design (Cipriani et al, 2011;Bagloee and Ceder, 2011;Yu et al, 2012;Wu et al, 2015;Zhang et al, 2014;Yao et al, 2014;Amiripour et al, 2014;Nayeem et al, 2014) and transit assignment analysis (Szeto et al, 2011;Hamdouch et al, 2011;Leurent et al, 2014).…”