A Mean-Variance Model for Route Guidance in Advanced Traveler Information Systems

Suvrajeet Sen (), Rekha Pillai, Shirish Joshi and Ajay K. Rathi
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Suvrajeet Sen: SIE Dept., University of Arizona, Tucson, Arizona 85721
Rekha Pillai: ITS Group, Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831-6206
Shirish Joshi: I2 Technologies, Irving, Texas 75063
Ajay K. Rathi: ITS Group, Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831-6206

Transportation Science, 2001, vol. 35, issue 1, 37-49

Abstract: Traditional models of route generation are based on choosing routes that minimize expected travel-time between origin and destination. Such approaches do not account for the fact that travelers often incorporate travel-time variability within their decision making. Thus, a route with lower travel-time variability is preferred by some travelers, even if such a route is not one with the lowest mean travel-time. Such traveler behavior is best captured by a multiobjective model in which the choice of a route is based on the mean as well as the variance of the path travel-time. Our route-planning model is intended to help travelers make choices that reflect their decision-making process better. We formulate a network flow multiobjective model in which one of the objectives (expectation) is linear, whereas, the other (variance) is quadratic. In order to present the user with a series of options, we solve a series of parametric 0-1 quadratic integer programs. By utilizing the network structure of the problem, we devise an effective algorithm in which the 0-1 quadratic program is solved by using a continuous relaxation together with an enumeration of some selected paths. Finally, we note that the data requirements for the model can be easily satisfied in practice.

Date: 2001
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