# Applying Topological Information for Routing Commercial Vehicles Around Traffic Congestion
## 2 Materials and Methods
Their study proposed several future areas of research, such as incorporating signal-timing plans into the process of diverting traffic to alternative routes, comparing different alternate routes for trucks, and assessing the impact of the behavior of truck drivers on the diversion decision. A study in [17] reviewed recent advances in DTA models and investigated their environmental impact. They also assessed traffic signal control for emission pricing and investigated the integration of DTA models with emission estimation models. Moreover, they highlighted several areas for future research on environmentally sustainable transportation. Presented in [18] was a state-of-the-art study that compares 17 simulation software tools and evaluates their adaptability and versatility in real-time simulations in a heterogeneous road network. They concluded that there is a shortage of online traffic simulation software applications specifically designed for use with multiple road transportation networks. The authors recommended that future research should focus on improving traffic simulation systems to increase their capabilities and enable them to provide real-time traffic information. When congestion is detected, vehicle navigation systems and services such as Google Maps and Bing can provide alternative paths for affected vehicles. However, they offer the same routes for all vehicles, which could lead to an imbalance in global traffic behavior. By contrast, DTA can assign each vehicle a route based on either system equilibrium or user optimization. However, the calculation is not carried out quickly enough to notify drivers of the availability of new routes and assist them in avoiding congestion. The Alternate Route Handbook of the Highway Administration and Federal Highway Administration (2006) provided thorough guidelines for traffic diversion strategies. Additionally, the Alternative Route Handbook presented the process of development and deployment of diversion strategies. Moreover, the handbook noted the criteria that are currently used in various states to make reliable diversion decisions according to predefined alternate route plans. Most of the transportation agencies considered incident duration and lane blockage as the principal factors in making a diversion decision. In [19], a diversion decision framework was presented to assess the benefits of implementing a detour strategy for managing nonrecurrent congestion on urban freeways. The author noted that the literature contains minimal information and few tools that can assist policymakers and traffic managers in making a firm decision on traffic diversion during significant incidents. They also generated simulation scenarios using a combination of critical parameters, such as incident duration, flow rate on a main-line detour route, and number of lanes and number of signals on the detour route, to define whether and when a detour decision should be made. The results revealed that the proposed logistic decision model could be used in the real-time management of nonrecurrent congestion. The authors in [20] introduced a systematic framework based on traffic assignment models and analyzed the value of traffic information in performing route diversion strategies for online traffic management objectives under the impact of traffic incidents. The author confirmed the importance of real-time traffic information in alleviating nonrecurrent congestion. The results of their simulation analysis indicated that the proposed framework was able to assess the cost-effectiveness of information provision strategies. A study in [21] proposed a GIS-based approach to assessing the vulnerability of road-way segments to disruptions. The study presented a vulnerability index to determine network connectivity and evaluate roadway segments as diversion routes in the event of road disruptions. The model provided transportation planners with a tool to enhance network continuity and identify high-risk areas.