Adaptive Signal Control Gradually Emerging As a New Way to Decrease Costs Associated With Delays, Stops and Fuel Consumption

Define traffic efficiency and safety criteria for Utah’s first ASCS. Define Measures of Effectiveness (MOE’s) to assess these criteria. Project Manager: Lindsey, Rukhsana Phone: (801) 965-4196 Fax: (801) 965-4564 Email: [email protected] Investigator: Martin, Peter Development and Evaluation of a Multi-Agent Based Neuro-Fuzzy Arterial Traffic Signal Control System Start date: 2006/9/1 End date: 2007/8/31 http://rip.trb.org/browse/dproject.asp?n=12249 ABSTRACT: Arterial traffic signal control is a very important aspect of traffic management system. Efficient arterial traffic signal control can reduce delay, stops, congestion, and pollution and save travel time. Commonly used pre-timed or traffic actuated signal controls does not have the capability to fully respond to real-time traffic demand and pattern changes. Although some of the well-known adaptive control systems have shown advantageous over the traditional per-timed and actuated control strategies, their centralized architecture makes the maintenance, expansion, and upgrade difficult and costly. Distributed artificial technologies such as multi-agent system is well suited for arterial signal control, and it has the ability to decompose complicated control problems and accomplish them by cooperatively simple agents such that flexibility, efficiency, robustness, and cost effectiveness can be achieved. The objective of this research is to conduct an in-depth investigation of applying multi-agent technology in arterial signal control. A multi-agent arterial signal control system will be developed and evaluated using simulation tools and real world traffic data. The goal of this project is to develop a new distributed adaptive control framework and control logic for arterial traffic signal control. Arterial traffic signal control is a very important aspect of traffic management system. Efficient arterial traffic signal control can reduce delay, stops, congestion, and pollution and save travel time. Commonly used pre-timed or traffic actuated signal controls does not have the capability to fully respond to real-time traffic demand and pattern changes. Although some of the well-known adaptive control systems have shown advantageous over the traditional per-timed and actuated control strategies, their centralized architecture makes the maintenance, expansion, and upgrade difficult and costly. Distributed artificial technologies such as multi-agent system is well suited for arterial signal control, and it has the ability to decompose complicated control problems and accomplish them by cooperatively simple agents such that flexibility, efficiency, robustness, and cost effectiveness can be achieved. The objective of this research is to conduct an in-depth investigation of applying multi-agent technology in arterial signal control. A multi-agent arterial signal control system will be developed and evaluated using simulation tools and real world traffic data. The goal of this project is to develop a new distributed adaptive control framework and control logic for arterial traffic signal control. Project Manager: Kline, Robin Phone: (202) 366-2732 Email: [email protected] Principal Investigator: Zhang, Yunlong Phone: (979) 845-9902 Real-time Adaptive Ramp Metering: Phase 1 Simulation & Proof of Concept Start date: 2004/12/29 End date: 2007/2/28 http://rip.trb.org/browse/dproject.asp?n=11414 ABSTRACT: The Arizona’s Department of transportation (ADOT) Freeway Management System is designed to apply “smart” ramp metering, taking into account the impacts on mainline freeway traffic flow. However, since its inception, smart real-time traffic-adaptive ramp metering has never been implemented. Planned FMS controller upgrades, and The Arizona’s Department of transportation (ADOT) Freeway Management System is designed to apply “smart” ramp metering, taking into account the impacts on mainline freeway traffic flow. However, since its inception, smart real-time traffic-adaptive ramp metering has never been implemented. Planned FMS controller upgrades, and