Trial-and-error operation schemes for bimodal transport systems

Abstract We concern the modal choice of commuters in a transport system comprising a highway, which is only used by autos, in parallel to a transit line, which is only used by buses. In the transport system, the in-vehicle congestion of passengers in bus carriages is treated as a negative externality cost of affecting the modal choice of commuters and commuters choose their travel modes according to the perceived travel costs of transport modes. We propose two trial-and-error operation schemes for the transport system without resorting to both the function of in-vehicle congestion costs and the distribution of perceived travel cost errors. In the first operation scheme, the manager (or the government) determines the transit fare charged from (or financial subsidy to) bus users from period to period so as to minimize the system time cost of the transport system. The second operation scheme is established from the viewpoint of a private firm that operates the public transit line. The operator determines the transit fare and bus run frequency from period to period in order to maximize its operating profit. Moreover, we demonstrate the effectiveness of the two operation schemes for optimizing the system time cost and the operating profit by both theoretical analyses and numerical examples.

[1]  A. Palma,et al.  The economics of crowding in rail transit , 2017 .

[2]  Renaud Foucart,et al.  Modal choice and optimal congestion , 2014 .

[3]  Bingsheng He,et al.  Road pricing for congestion control with unknown demand and cost functions , 2010 .

[4]  Hai-Jun Huang,et al.  Fares and tolls in a competitive system with transit and highway: the case with two groups of commuters , 2000 .

[5]  Hai Yang,et al.  The Downs–Thomson Paradox with responsive transit service , 2014 .

[6]  Hai Yang,et al.  Dynamics of modal choice of heterogeneous travelers with responsive transit services , 2016 .

[7]  Hai Yang,et al.  A trial-and-error congestion pricing scheme for networks with elastic demand and link capacity constraints , 2015 .

[8]  Yosef Sheffi,et al.  Urban Transportation Networks: Equilibrium Analysis With Mathematical Programming Methods , 1985 .

[9]  W. F. Trench,et al.  Introduction to Real Analysis: An Educational Approach , 2009 .

[10]  Hai Yang,et al.  TRIAL-AND-ERROR IMPLEMENTATION OF MARGINAL-COST PRICING ON NETWORKS IN THE ABSENCE OF DEMAND FUNCTIONS , 2004 .

[11]  Hai Yang,et al.  Interactive travel choices and traffic forecast in a doubly dynamical system with user inertia and information provision , 2017 .

[12]  Hai-Jun Huang.  Pricing and logit-based mode choice models of a transit and highway system with elastic demand , 2002, Eur. J. Oper. Res..

[13]  Marvin Kraus,et al.  A new look at the two-mode problem , 2003 .

[14]  E. Pels,et al.  Infrastructure Pricing and Competition between Modes in Urban Transport , 2007 .

[15]  William H. K. Lam,et al.  Modeling intermodal equilibrium for bimodal transportation system design problems in a linear monocentric city , 2012 .

[16]  Wei Liu,et al.  Managing morning commute with parking space constraints in the case of a bi-modal many-to-one network , 2016 .

[17]  W. Y. Szeto,et al.  Day-to-day modal choice with a Pareto improvement or zero-sum revenue scheme , 2018 .

[18]  Nikolas Geroliminis,et al.  Doubly dynamics for multi-modal networks with park-and-ride and adaptive pricing , 2017 .

[19]  M. Wardman,et al.  Twenty Years of Rail Crowding Valuation Studies: Evidence and Lessons from British Experience , 2011 .

[20]  Adam J. Pel,et al.  Including passengers’ response to crowding in the Dutch national train passenger assignment model , 2014 .

[21]  Giulio Erberto Cantarella,et al.  Day-to-day Dynamics & Equilibrium Stability in A Two-Mode Transport System with Responsive bus Operator Strategies , 2015 .

[22]  Hai-Jun Huang,et al.  Equilibrium and Modal Split in a Competitive Highway/Transit System Under Different Road-use Pricing Strategies , 2014 .

[23]  K. Small,et al.  Should Urban Transit Subsidies Be Reduced? , 2007 .

[24]  D. Hensher,et al.  Crowding and public transport: A review of willingness to pay evidence and its relevance in project appraisal , 2011 .

[25]  Hai Yang,et al.  Bisection-based trial-and-error implementation of marginal cost pricing and tradable credit scheme , 2012 .

[26]  Carlos F. Daganzo,et al.  Morning Commute with Competing Modes and Distributed Demand: User Equilibrium, System Optimum, and Pricing , 2012 .

[27]  M. Koning,et al.  The distribution of crowding costs in public transport: New evidence from Paris , 2015 .

[28]  Michael Z. F. Li,et al.  The role of speed–flow relationship in congestion pricing implementation with an application to Singapore , 2002 .

[29]  Ki-jung Ahn,et al.  Road Pricing and Bus Service Policies , 2009 .

[30]  R. Arnott,et al.  The Two‐Mode Problem: Second‐Best Pricing and Capacity , 2000 .

[31]  Xiaobo Qu,et al.  Trial-and-error train fare design scheme for addressing boarding/alighting congestion at CBD stations , 2018 .

[32]  E. Verhoef,et al.  Congestion pricing in a road and rail network with heterogeneous values of time and schedule delay , 2014 .

[33]  Ziyou Gao,et al.  Modal Split and Commuting Pattern on a Bottleneck-Constrained Highway , 2007 .

[34]  Eric J. Gonzales.  Coordinated pricing for cars and transit in cities with hypercongestion , 2015 .

[35]  Erik T. Verhoef,et al.  Competition in Multi-Modal Transport Networks: A Dynamic Approach , 2012 .

[36]  Hai Yang,et al.  Congestion pricing in the absence of demand functions , 2009 .

[37]  D. Hensher,et al.  Multimodal Transport Pricing: First Best, Second Best and Extensions to Non-motorized Transport , 2012 .