Harnessing the Power of Microscopic Simulation to Evaluate Freeway Service Patrols

Evaluating the impact of Road Rangers in preventing secondary crashes

Many transportation agencies utilize freeway service patrols (FSPs) to quickly identify and respond to incidents. The objectives of FSP are to minimize the incident duration and increase safety at the incident scene. The current research explored the safety benefits of Florida's FSP program known as Road Rangers - harnessed from lowering the likelihood of secondary crashes (SCs) - compared to other responding agencies. The analysis was done on 6088 incidents that occurred on freeways in Jacksonville, Florida, from 2015 through 2017. Since SCs were not explicitly identified in the SunGuide® incident database, the study adopted a data-driven technique that used BlueToad® speed data to identify them. Once SCs were identified, a model was developed to identify factors influencing their occurrence. Factors such as an increase in equivalent hourly traffic volume, incident impact duration, and the percent of lanes closed significantly increased the likelihood of a SC. Besides, moderate/severe incidents, crash events, weekdays, peak hours, shoulder blockage, and incidents involving towing showed a high likelihood of resulting in a SC. Of practical importance, the model results revealed that a minute increase in incident impact duration increased the SC probability by 1.2 percent, with other factors held constant. Based on a 16-minutes decrease in incident impact duration, the Road Rangers program could lessen the probability of SCs by 21 percent, compared to other agencies. These findings could be beneficial to incident managers, responders, and researchers in evaluating the program's performance.

Genetic Algorithm for Optimizing Routing Design and Fleet Allocation of Freeway Service Overlapping Patrol

The freeway service patrol problem involves patrol routing design and fleet allocation on freeways that would help transportation agency decision-makers when developing a freeway service patrols program and/or altering existing route coverage and fleet allocation. Based on the actual patrol process, our model presents an overlapping patrol model and addresses patrol routing design and fleet allocation in a single integrated model. The objective is to minimize the overall average incident response time. Two strategies—overlapping patrol and non-overlapping patrol—are compared in our paper. Matrix encoding is applied in the genetic algorithm (GA), and to maintain population diversity and avoid premature convergence, a niche strategy is incorporated into the traditional genetic algorithm. Meanwhile, an elitist strategy is employed to speed up the convergence. Using numerical experiments conducted based on data from the Sioux Falls network, we clearly show that: overlapping patrol strategy is superior to non-overlapping patrol strategy; the GA outperforms the simulated annealing (SA) algorithm; and the computational efficiency can be improved when LINGO software is used to solve the problem of fleet allocation.