Capacity Allocation in Vertically Integrated Railway Systems: A Rubinstein Sequential Bargaining Game Approach

Author(s):  
Ahmadreza Talebian ◽  
Bo Zou

The present paper proposes, for the first time, a game-theoretic bargaining based approach to allocating rail line capacity in the vertically integrated US rail system. A passenger rail agency (PRA) negotiates with a freight railroad (FRR) to obtain appropriate train paths. This market has specific features: FRR charges PRA a fee for access to the railroad; on the other hand, FRR compensates PRA for delayed services. In addition, by US Public Law 110-432 Amtrak passenger trains have priority over all freight trains. Passenger demand is elastic with respect to the service schedule convenience. With these features explicitly taken into account, a multi-step, game-theoretic bargaining model is put forward. We analytically solve this game and show that a schedule that maximizes the sum of utilities of PRA and FRR is the efficient one. We derive the equation yielding the net internal transfer between the two entities, and show that which player initiating the bargaining game does not change the equilibrium schedule, but alters the net internal transfer.

2014 ◽  
Vol 60 (1) ◽  
pp. 149-158
Author(s):  
Li Xu ◽  
Xinyu Chen ◽  
Jie Li ◽  
Xinyi Huang ◽  
Jianying Zhou

IEEE Access ◽  
2018 ◽  
Vol 6 ◽  
pp. 27777-27789 ◽  
Author(s):  
Songli Fan ◽  
Zhengshuo Li ◽  
Jianhui Wang ◽  
Longjian Piao ◽  
Qian Ai

Author(s):  
Jack E. Heiss

While planners and politicians alike go about kicking the tires of various trains, and traveling abroad on fact-finding missions about HSR, the question remains whether Americans will patronize high-speed rail in sufficient number to justify the investment. A common practice is to identify an existing or abandoned rail line as the candidate route that connects population centers, identify the former stations for rehabilitation, select a technology, and then perform an investment-grade ridership study to determine whether sufficient revenues will be generated. This approach may prove sufficient in the upgrading of an existing conventional service, or re-establishing a previous service in those areas of the country with a long history of passenger rail. When approaching newer developed areas such as the Sunbelt cities, the inter-relationship of development patterns and fixed-guideway passenger services is not established. Those development patterns were influenced by the automobile, not by guideway-based transportation. A different approach is needed when history is not a guide. While the selection of the population centers to be served at the outset is appropriate and makes for a basic identification of the market to be served, it does not reveal the actual destinations that are interest to the travelers. The next step is to more thoroughly investigate travel between those points. That investigation should include surveys to determine trip purpose, identify the main attractors in the markets, the demographics of the travelers and how time is valued by the travelers. Finally, estimates must be made of the absolute numbers of those traveling. Additionally, examination of the current travel patterns through the patronage of existing services can provide clues to the market demand. The acquisition of this market information then allows the planners to design a transportation product that will appeal to the potential customers and make a determination of potential revenue. Even when certain parameters of a system are set because of geography or availability of infrastructure, market information can guide improvements to maximize market capture. This paper will examine those data that are important to a high-speed rail plan and how some system decisions directly affect the ability of the transportation product offered to satisfy the needs of the traveling public. “Build it and they will come” cannot be trusted to repay the massive investment required by high-speed rail.


2012 ◽  
Vol 16 (2) ◽  
pp. 208-211 ◽  
Author(s):  
Guopeng Zhang ◽  
Kun Yang ◽  
Qingsong Hu ◽  
Peng Liu ◽  
Enjie Ding

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