A line haul transit technology selection model

A decision analytic model for the selection of mass transit technology is suggested. The model considers a transit corridor with known right of way category and rules of operation. The system with technology under evaluation satisfies the users’, operators’ and community requirements roughly equally and has identical level of comfort, convenience and other nonquantifiable attributes of performance measures. Cost attributes comprise of access/egress cost, riding time cost, waiting time cost in users’ side, transit operating cost, station cost, line cost and fleet cost in the operators’ side, and the measurable cost of air pollution on the community's cost side. Given the subjective probabilities of the chance event influencing the decision and possible outcomes of the event, technology, which offers the maximum expected utility, is established. This utility indicator together with other unmodellable factors can form the basis for decision making on technology selection. The problem is extended to include multiple chance events and outcomes of more definitive experiments with updated probabilities. It is shown that transit technology similar to Light Rail Transit could be considered viable in developing countries only when the value of travel time is considerably higher than what it is now.

[1]  Eric R. Zieyel.  Operations research : applications and algorithms , 1988 .

[2]  Alan Armstrong-Wright.  Urban transit systems : guidelines for examining options , 1986 .

[3]  S. C. Wirasinghe,et al.  Rail Line Length in an Urban Transportation Corridor , 1986, Transp. Sci..

[4]  Howard Raiffa,et al.  Decision analysis: introductory lectures on choices under uncertainty. 1968. , 1969, M.D.Computing.

[5]  Frederick S. Hillier,et al.  Introduction of Operations Research , 1967 .

[6]  G. F. Newell.  Scheduling, Location, Transportation, and Continuum Mechanics: Some Simple Approximations to Optimization Problems , 1973 .

[7]  Richard de Neufville,et al.  Systems analysis for engineers and managers , 1971 .

[8]  Sang M. Lee,et al.  Goal programming for decision analysis , 1972 .

[9]  Vukan R Vuchic,et al.  Urban Public Transportation: Systems and Technology , 1981 .

[10]  Partha Mani Parajuli.  Analysis of line haul transit systems with low cost feeder modes , 1996 .

[11]  Godfred Jere Quain.  Optimal parameters for urban rail planning , 1994 .

[12]  Roger J Allport,et al.  THE PERFORMANCE AND IMPACT OF RAIL MASS TRANSIT IN DEVELOPING COUNTRIES , 1990 .

[13]  S. C. Wirasinghe.  RE-EXAMINATION OF NEWELL'S DISPATCHING POLICY AND EXTENSION TO A PUBLIC BUS ROUTE WITH MANY TO MANY TIME-VARYING DEMAND , 1990 .

[14]  David E. Goldberg,et al.  Genetic Algorithms in Search Optimization and Machine Learning , 1988 .

[15]  Kenneth A. Small,et al.  On the Costs of Air Pollution from Motor Vehicles , 2018, Controlling Automobile Air Pollution.

[16]  E L Tennyson,et al.  ECONOMICS OF ELECTRIC TROLLEY COACH OPERATION , 1995 .