Incorporating Uncertainty and Multiple Objectives in Real-Time Route Selection

Abstract

There is a requirement in real-time, routing information systems to identify the “optimal” route based on the multiple objectives and the individual decision-making rules of the users. While a number of utility theory-based techniques have been developed to accomplish this goal, there are a number of shortcomings regarding implementation. These problems, in particular, are: (1) obtaining a mathematical representation of the driver's utility function for each trip type is difficult in practice; (2) the drivers' utility function is a function of the choice set and is difficult to calibrate prior to the identification of the choice set (i.e., it is context-dependent); and (3) identifying the optimal path using a realistic multiple attribute nonlinear utility function is a nondeterministic polynomial time hard problem. Consequently, a heuristic two-stage strategy that identifies multiple reasonable routes and then selects the “near-optimal” path may be an effective and practical alternative. The second step of this proposed strategy is the focus of this paper. A fuzzy logic-based multiple objective route choice model (or decision support system) is developed in order to evaluate the alternative routes identified in the first step. Fuzzy logic is used to take into account crisp values, fuzzy numbers, and linguistic variables that are common phenomena in a real-time vehicle routing environment. The routes and the route attributes are identified and a posterior utility function is developed by combining the prior utility function with a context-dependent utility function that is derived from an entropy model. The proposed strategy is illustrated using Intelligent Transportation System (ITS) data from Houston, Texas, and tested on a traffic network from Austin, Texas, under various traffic conditions. When multiple attributes were considered, an alternative path to the fastest path was found to be the “optimal” path for a significant number of O-D pairs, and this was likely to occur as the level of congestion and the O-D distance increased.