Browsing by Author "Torabi, Behnam"
Now showing 1 - 3 of 3
- Results Per Page
- Sort Options
Item A Self-Adaptive Collaborative Multi-Agent Based Traffic Signal Timing System(Institute of Electrical and Electronics Engineers Inc.) Torabi, Behnam; Zalila-Wenkstern, Rym; Saylor, R.; 0000-0002-2062-6794 (Zalila-Wenkstern, R); 2863148574264724430006 (Zalila-Wenkstern, R); Torabi, Behnam; Zalila-Wenkstern, RymIn this paper, we present DALI, a self-Adaptive, collaborative multi-Agent Traffic Signal Timing system (TST). Intersection controller agents collaborate with one another and adapt their timing plans based on the traffic conditions. Reinforcement learning is used to optimize values for the various thresholds necessary to dynamically determine the scope of collaboration between the agents. DALI was implement in MATISSE 3.0, a large-scale agent-based micro-simulator. Experimental results show an improvement over traditional and reinforcement learning TSTs. © 2018 IEEE.Item DALI: A Collaborative, Agent-Based Traffic Signal Timing System(2019-04-29) Torabi, Behnam; Zalila-Wenkstern, RymIn this dissertation, we present DALI (Distributed, Agent-based traffic LIghts), a smart collaborative traffic signal timing system. With DALI, intersection controller agents communicate with each other through direct links and do not have a supervising unit to oversee coordination. By default, they execute a timing strategy that improves traffic flow. At the same time, they observe and analyze their respective intersections. If, at any given time, an agent determines that its intersection is congested, it deliberates and defines a new timing plan. It also determines which direct intersections may be affected by the new timing plan and communicates with the concerned intersection agents. They in turn communicate with those agents that may be affected, and the process continues until all affected intersections are notified. The agents then negotiate and collaborate with one another to ensure that the traffic flow will be optimized throughout the intersections. DALI was validated by traffic engineers as well as through extensive simulation of the City of Richardson’s traffic network. In addition, hybrid simulations (i.e., integration of controllers in the field with the simulator) were run to verify compliance with the strict traffic regulations. DALI was deployed in a Richardson, Texas, corridor that includes three major intersections. The data collected for a period of three weeks shows that in average, DALI reduced delay by 40.12 percent (43.56 percent during weekday peak hours).Item Matisse 3.0: A Large-Scale Multi-Agent Simulation System for Intelligent Transportation Systems(Springer Verlag) Torabi, Behnam; Al-Zinati, M.; Zalila-Wenkstern, Rym; 0000-0002-2062-6794 (Zalila-Wenkstern, R); 2863148574264724430006 (Zalila-Wenkstern, R); Torabi, Behnam; Zalila-Wenkstern, RymIn this demo we present MATISSE 3.0, a microscopic simulator for agent-based Intelligent Transportation Systems (ITS). MATISSE provides abstract classes for the definition of vehicle and intersection-controller agents as well as components for the concurrent 2D and 3D visualizations of the simulation. The control GUI allows the user to change various agent properties at run time. The OSM converter imports entire traffic networks from Open Street Map. We illustrate the use of MATISSE through the development of a simulation for the City of Richardson, Texas.