A multi-agent approach to real-time traffic signal optimisation

The objective of our study is to demonstrate the feasibility of applying agent algorithms to develop a decentralised adaptive traffic control system. The controllers will be equipped with an optimisation model that is generally used to design pre-timed traffic signal timings. Interestingly, the origins of this signal optimisation model are found in the work by Webster in the early 1960s. However, the model was initially developed for operation in under-saturated conditions. A number of researchers introduced several changes to the model over the years and a variant of the model (described below) is currently implemented in the well-known aaSIDRA software. In this paper, we demonstrate the applicability of our model using a microscopic traffic simulator (AIMSUN NG). The simulation approach provides an environment where different scenarios can be introduced and evaluated in a controlled setting without disrupting traffic conditions in the real world. (a) For the covering entry of this conference, please see ITRD abstract no. E214666.

• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/isbn/1877040568
• Authors:
  • NIGARNJAGOOL, S
  • DIA, H
• Publication Date: 2006-9

Language

• English

Media Info

• Pagination: 16P
• Monograph Title: Exploring the impacts of fuel price increases on public transport
• Serial:
  • AUSTRALASIAN TRANSPORT RESEARCH FORUM (ATRF), 29TH, 2006, GOLD COAST, QUEENSLAND, AUSTRALIA, VOL 29
  • Publisher: QUEENSLAND TRANSPORT

Subject/Index Terms

• TRT Terms: Conferences; Intelligent transportation systems; Mathematical models; Traffic flow; Traffic signal cycle; Traffic signals
• ITRD Terms: 8525: Conference; 576: Cycle (traffic signals); 8735: Intelligent transport system; 6473: Mathematical model; 671: Traffic flow; 565: Traffic signal
• Subject Areas: Operations and Traffic Management; I73: Traffic Control;

Filing Info

• Accession Number: 01050531
• Record Type: Publication
• Source Agency: ARRB
• ISBN: 1877040568
• Files: ITRD, ATRI
• Created Date: Jun 4 2007 11:35PM