An efficiency-equity solution to the integrated transportation corridor control design problem.

摘要

This dissertation research proposes the integrated corridor control program based on the bi-criterion of both system efficiency and user equity. For years improving system efficiency, characterized by total travel time or travel delay reduction, has been considered the single most important measure in designing traffic control systems. From the perspective of the traveling public, however, the fairness, or how the improvement benefits is distributed, becomes more important as the transportation corridor systems get ever more congested. Incorporation of user equity in designing new control systems or updating existing ones will become prominent and urgent as the public is more and more involved in implementing these decisions.;The research began with an extensive review of the control practices and recognized three major deficiencies in the literature: (1) unclear and incomplete user equity measures and their fragmental applications in traffic control, (2) ad hoc and inaccurate modeling of the corridor traffic dynamics and subsequent congestion evolution and, (3) sub-optimal solutions of only isolated or sub-systems within the corridor. Aiming to overcome the deficiencies, we first developed a general traffic flow dynamics model based on the kinematic wave model. Various control measures including urban signals, ramp metering and priority-rule controls were adapted and embedded into the flow dynamics model. Within this modeling framework, both the system efficiency measures and the user equity measures at aggregate and disaggregate levels were formulated and defined explicitly. One set of rule-based local synchronization corridor control schemes were then developed, and the schemes were compared with other control strategies of their efficiency and equity performances. We then proceeded to formulate the corridor control program that incorporates both efficiency and equity in the control objective. To solve the problem, one heuristic searching algorithm using simultaneous perturbation stochastic approximation (SPSA) was developed. The SPSA algorithm takes advantage of both heuristic searching algorithms and linear and non-linear programming algorithms to quickly obtain the solution in much less computational burdens, while maintaining the realistic traffic flow model. Extensive numerical experiments with both illustrative and real networks were carried out to demonstrate the effectiveness of the proposed research, and the major findings were summarized in the last chapter.