|M.Sc Student||Hamdan Salah-Eldeen|
|Subject||Control of Signalized Intersections to Reduce Energy|
|Department||Department of Civil and Environmental Engineering||Supervisor||Professor Tomer Toledo|
|Full Thesis text|
At an intersection, many vehicles experience deceleration, idling, and acceleration. Therefore, in these facilities, vehicles tend to consume energy much more than while cruising, especially during the acceleration operation.
Traffic signal control is the main tool for operators and managers of transportation systems to allocate capacities and affect the state of the system and its performance. The efficient design of intersection traffic signal control has been recognized as one of the most cost-effective methods to improve accessibility and mobility in urban networks. They may also be operated as to reduce fuel consumption and emissions.
This work presents the detailed structure of a simulation-based optimization system of complex actuated traffic signal plans combined with an energy consumption model. This system includes a mesoscopic simulation model for modeling the movement of road users at intersections area and sections that connect them and build a speed profile for each vehicle during its travel in the intersection system. The energy consumption model that estimates the energy consumption that vehicles consume based on the speed profile of each vehicle. In addition, a genetic algorithm (GA) will help determine the optimal parameter values of the traffic signal plan for each intersection on the network.
With this integrated optimization system, complex actuated traffic signal plans were optimized for three adjacent intersections in Haifa. The results showed that the intersections performance can be improved compared to the initial design. The energy consumption optimization decreases average energy consumption in the system by 11%. The delay optimization decreases the average delay of travelers in the system by 55%. Pareto front was created with various weights of energy consumption and delay in the objective function.
In this work, the three intersections were optimized in 27 scenarios of changes in demand and their distribution, as well as changes in weights of energy consumption and delay in the objective function. In the optimization of equal weights in the objective function for energy consumption and delay, the intersections system performs better both in terms of average energy consumption and delay and in terms of queue lengths in the approaches to the intersections.