Title

Adaptive traffic control for large scale dynamic traffic assignment applications

Document Type

Article

Abstract

Dynamic Traffic Assignment (DTA) applications require traffic signal control data which is typically difficult to obtain and cumbersome to code in the required format. In addition, the evaluation of future scenarios requires future traffic signal settings consistent with the forecasted demand. These future signal settings are not known a priori and are costly to estimate. Intuitively, the future signal timings need to be reasonably optimized so as to represent what the traffic management agency will do. In literature, integration between traffic control and DTA models has been formulated as a bi-level or single-level optimization problem with system or user optimal constraints. Most existing solution procedures require certain “nested” structure with an inner loop algorithm solving the user equilibrium or system optimal assignment problem and the outer loop algorithm searching for the optimal signal timing setting. Most of these solution approaches remain only research tools without practical use due to computational intractability. This research proposes an efficient solution algorithm to the problem. An adaptive traffic signal control model is embedded in a simulation-based DTA model. For each inbound approach at an intersection of interest, the adaptive model uses upstream information and a dynamic rolling horizon approach to project traffic flow conditions for a dynamic but short period of time (projection period). The adaptive model provides the signal settings during the entire traffic flow simulation process and for every iteration of the solution algorithm. Thus, during the entire solution process, the experienced travel times and the resulting traffic assignment flows are based on the adaptive (demand responsive) signal settings. Thereby, the DTA flows and the adaptive signal settings are generated simultaneously in a single-loop algorithmic structure. Simulation experiments illustrate the capabilities of the proposed approach.

Disciplines

Civil Engineering | Other Civil and Environmental Engineering | Other Engineering | Transportation

Permissions

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