01336801

Component

Severe traffic congestion on urban arterials causes delays and extra travel time when the signal control systems are incapable of responding to high traffic fluctuations. This is especially the case during non-recurrent traffic congestion that is due to unexpected events such as incidents, construction, weather, etc. Pre-timed signal systems and actuated controllers cannot accommodate these types of traffic variation, due to a fixed signal plan. The objective of this research is the development of a responsive signal control strategy, which responds to varying traffic demand that arises from non-recurrent traffic congestion. Case-based reasoning (CBR), a technique in artificial intelligence (AI), was used to formulate a control strategy that the author called RESSICA (RESponsive SIgnal Control for Arterial), which matches the traffic pattern and assigns a corresponding timing plan from its library with minimal re-computation. RESSICA was tested in a corridor network with four signalized intersections under various levels of non-recurrent congestion scenarios. The results showed that RESSICA outperformed the existing pre-timed/actuated signal controller, in terms of reducing travel time, delay, stop delay and intersection delay in the study area.

The DVD lists the title of this paper as: Responsive Signal Control for Nonrecurrent Traffic Congestion on Arterials.

01329018

11-3127

English

17p

2011

Transportation Research Board 90th Annual Meeting

DVD

Figures (6) ; References (10) ; Tables (2)

Arterial highways; Artificial intelligence; Case based reasoning; Nonrecurrent congestion; Signalized intersections; Traffic actuated controllers; Traffic congestion; Traffic delays; Traffic incidents; Traffic signal control systems; Traffic signal timing; Travel time

Highways; Operations and Traffic Management; I73: Traffic Control

Transportation Research Board Annual Meeting 2011 Paper #11-3127

TRIS, TRB

Feb 17 2011 6:24PM