Title page for ETD etd-01232006-195437


Type of Document Master's Thesis
Author Joshi, Chetan
Author's Email Address joshchea@vt.edu
URN etd-01232006-195437
Title Development of a Decision Support Tool for Planning Rail Systems: An Implementation in TSAM
Degree Master of Science
Department Civil Engineering
Advisory Committee
Advisor Name Title
Trani, Antoino A. Committee Chair
Baik, Hojong Committee Member
Rakha, Hesham Ahmed Committee Member
Keywords
  • Nodes
  • Graph
  • Arcs
  • Network
  • Amtrak
  • Floyd’s Algorithm
  • Schedule Delay
  • Event Graph
Date of Defense 2005-12-15
Availability unrestricted
Abstract
A Decision Support model for planning Intercity Railways is presented in this research. The main aim of the model is to generate inputs for the logit model existing in the Virginia Tech Transportation Systems Analysis Model (TSAM). The inputs required by the TSAM logit model are travel time, travel cost and schedule delay. Travel times and travel costs for different rail technologies are calculated using a rail network and actual or proposed rail schedules. The concept of relational databases is used in the development of the network topology. Further, an event graph approach is used for analysis of the generated network. Shortest travel times and their corresponding travel costs between origin-destination pairs are found using Floyd’s algorithm. Complete itineraries including transfers (if involved) are intrinsically held in the precedence matrix generated after running the algorithm. A standard mapping technique is used to obtain the actual routes. The algorithms developed, have been implemented in MATLAB. Schedules from the North American Passenger rail system AMTRAK are used to generate the sample network for this study. The model developed allows the user to evaluate what-if scenarios for various route frequencies and rail technologies such as Accelerail, High Speed Rail and Maglev. The user also has the option of modifying route information. Comparison of travel time values for the mentioned technology types in different corridors revealed that frequency of service has a greater impact on the total travel time in shorter distance corridors, whereas technology/line-haul speed has a greater influence on the total travel time in the longer distance corridors. This tool could be useful to make preliminary assessments of future rail systems. The network topology generated by the algorithm can further be used for network flow assignment, especially time-dependent assignment if used with dynamic graph algorithms.
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