Optimal design of freeway incident response systems

Raktim Pal, Purdue University

Abstract

Non-recurrent congestion caused by freeway incidents is a major concern for transportation agencies and millions of road users in metropolitan areas in the United States. As a low-cost approach to incident management, freeway service patrol programs have gained wide popularity. Several states have introduced such programs to curb the adverse impacts of incidents. Although there are many such programs in different parts of the country, not much research has taken place in developing systematic design procedures of these programs. An efficient design of a patrol program would ensure appropriate resource allocation. This research seeks to devise a methodology for determining optimally such system parameters as hours of operation, fleet sizes, dispatching policies, areas of operation, and routing schemes so that the efficacy of the program is maximized. Because of the interaction of randomly occurring incidents with time-varying traffic, the problem requires to be solved using dynamic simulation approaches combined with optimization techniques. Simulation approaches are utilized to replicate the operation of response vehicles that move through traffic on freeways. The incident occurrence is simulated from an incident generation model that uses a non-homogeneous Poisson process. Aggregate route diversion models are used, along with queueing models, to capture the non-linear impact of incidents on traffic flow in the network. Total vehicle-hours in the network is used as the performance measure to estimate the effectiveness of the incident response program. Optimization techniques are used to design new programs efficiently and improve existing programs by making intelligent decisions about system parameters. As all the system parameters are not commensurable and there is no analytical expression for system performance measures, traditional optimization techniques cannot be used. A heuristic approach is therefore used based on the nested partitions method where an initial feasible region is systematically partitioned to adapt sampling. Sampling is concentrated in the subset that is considered most promising. The initial promising region is obtained using the idea of sample path optimization. A load balancing technique is used to formulate an initial good design. Subsequently, the nested partitions method and simulation models are used iteratively to select an optimal design so that system parameters are most cost-effective. A generalized framework is developed that can be used to design new freeway patrol programs and improve existing ones. As an example application of the proposed tool, the case of the Hoosier Helper program in northwest Indiana is studied in detail.

Degree

Ph.D.

Advisors

Sinha, Purdue University.

Subject Area

Civil engineering|Operations research

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