This dissertation proposes a Dynamic Message Signs (DMS) diversion control system based on principles of existing Advanced Traveler Information Systems and Advanced Traffic Management Systems (ATMS). The objective of the proposed system is to alleviate total corridor traffic delay by choosing optimized diversion rate and alternative road signal-timing plan. The DMS displays adaptive messages at predefined time interval for guiding certain number of drivers to alternative roads. Messages to be displayed on the DMS are chosen by an on-line optimization model that minimizes corridor traffic delay. The expected diversion rate is assumed following a distribution. An optimization model that considers three traffic delay components: mainline travel delay, alternative road signal control delay, and the travel time difference between the mainline and alternative roads is constructed. Signal timing parameters of alternative road intersections and DMS message level are the decision variables; speeds, flow rates, and other corridor traffic data from detectors serve as inputs of the model. Traffic simulation software, CORSIM, served as a developmental environment and test bed for evaluating the proposed system. MATLAB optimization toolboxes have been applied to solve the proposed model. A CORSIM Run-Time-Extension (RTE) has been developed to exchange data between CORSIM and the adopted MATLAB optimization algorithms (Genetic Algorithm, Pattern Search in direct search toolbox, and Sequential Quadratic Programming). Among the three candidate algorithms, the Sequential Quadratic Programming showed the fastest execution speed and yielded the smallest total delays for numerical examples. TRANSYT-7F, the most credible traffic signal optimization software has been used as a benchmark to verify the proposed model. The total corridor delays obtained from CORSIM with the SQP solutions show average reductions of 8.97%, 14.09%, and 13.09% for heavy, moderate and light traffic congestion levels respectively when compared with TRANSYT-7F optimization results. The maximum model execution time at each MATLAB call is fewer than two minutes, which implies that the system is capable of real world implementation with a DMS message and signal update interval of two minutes.

This study presents an analysis of detour operations as a concept of congestion management. Since a large portion of traffic delay emanates from traffic incidents, the goal of the study was to alleviate incident-induced impacts on freeways by diverting congested traffic on to adjacent roadway facilities. To balance the demand between freeway and arterial systems, optimization was required through Integrated Corridor Management (ICM). This thesis examines the justification and optimization of dynamic traffic routing strategies. Previous studies have justified detour operations based solely on traffic simulation results. This study quantifies the impacts from freeway incidents on a parallel arterial roadway using a data-driven signal processing technique, with operating speeds adopted as a performance measure. Results show that rerouting traffic to an adjacent arterial road, due to a freeway incident, can mitigate the mobility of the corridor with a probability of up to 88% depending on the type of incident and occurrence time. Results also indicate that diverting traffic during off-peak hours, especially for minor incidents, provides minimal mobility benefits. A secondary focus of this study explored the optimum dynamic traffic diversion, to an adjacent arterial roadway, from incident-induced freeway congestion to better utilize the freeway’s available corridor capacity. VISSIM, a microsimulation tool, was employed to simulate a freeway incident and measure the performance of detour operations. A 23 full factorial central composite design was used to establish a relationship between the performance of the detour operation and three control factors: incident duration, diversion rate, and demand level. The resulting regression equation predicts the corridor delay with over 83% accuracy. The findings of this study can potentially serve as a building block in the understanding and development of future ICM systems and incident management plans.