Sustainable management of traffic flows at signalized intersections is an important issue in terms of traffic engineering. The minimization of lost time, emission, fuel consumption, etc., can be achieved by optimization-based intersection management. In this study, a new traffic signal control model is developed for the management of three-leg signalized intersections. In the proposed model, signal timing and signal phasing are optimized simultaneously using Differential Evolution (DE) algorithm which is one of the population-based metaheuristic algorithms. The effectiveness of the model is tested on sample traffic scenarios with VISSIM simulation software considering average vehicle delay performance criteria. Results show that the proposed approach may reduce the average vehicle delay between the rates of 28%–42% and 3%–38% comparing to the optimum fixed-time signal control and vehicle-actuated signal control for tested scenarios, respectively.
In transportation planning, design of intersections is required some concrete decisions. It is mostly related to capacity, safety and economy. In many applications, capacity is considered as the main factor for design purpose and type of intersection is determined regarding the capacity. But it is known that safety and economy are as important as the capacity. In order to handle this problem, a multi-criteria decision making approach (AHP) is used. Four intersection types are used. Fuel consumption, emission rates, delay, cost of intersection type and safety parameters are taken into account in the decision process. These intersection types are tested by SIDRA Intersection software using the parameters listed above. The data obtained by SIDRA software is used in the AHP model. Weights of the factors used in the AHP model are varied considering the views of capacity and economy. And results and applicability of the model are discussed.
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