Wednesday, April 21, 2010


This Easter, motorists experienced the familiar frustration of being stuck on a motorway in a ‘phantom’ traffic jam that eventually disperses with no road works to blame, or any other apparent cause.

Research at the University of Bristol has investigated this problem and found that although most changes in vehicle speed and road position get absorbed by traffic flow, they sometimes combine in a ‘perfect storm’ to create these phantom jams.

In busy conditions the action of just one driver crossing from one lane to another is enough to cause a ripple which can magnify into a wave of traffic chaos. The resulting queues are like waves which move against the traffic flow, slowing it down to a standstill in places.

Understanding why this happens is being studied in a project led by Dr Eddie Wilson who is developing mathematical models for describing these phantom traffic jams, or stop-and-go waves, in motorway traffic.

Dr Wilson says: “The stop-and-go waves are generated by very small events at the level of individual vehicles. In certain situations a tipping point is reached that magnifies small effects to create large changes that can involve hundreds of vehicles and which may be a couple of miles long. The record phantom jam was about 50 miles long – the entire M6 from Birmingham to the Lake District was stop-go the whole way”.

The research, supported by the Engineering and Physical Sciences Research Council (EPSRC), will lead to better traffic flow forecasting to help prevent congestion.

Dr Wilson has looked at existing traffic models in a new way using ‘string instability’ theory to test how good these computer-based methods are at predicting how traffic flows and queues build up and dissipate.

He has identified patterns in these traffic models that will make working on more complicated scenarios possible and which could lead to more accurate forecasting of traffic flow.

“What is important here”, says Wilson, “is not necessarily shortening journey times, but making the journey time more reliable and consistent so people can more accurately forecast the time it will take to get from A to B”.

The next stage of the project will see the best of Wilson’s traffic models being combined in a way that allows them to learn from experience and observation. This will give a human-like artificial intelligence to these computer-based methods of forecasting traffic.

The project uses data taken from a particularly busy 10-mile stretch of the M42 near Birmingham that has one of the highest concentrations of traffic monitoring equipment in the world. This means the behaviour of millions of individual vehicles can be tracked very accurately to reconstruct their travel paths and understand the effect that individual motorists have on the flow of traffic.

Wilson’s aim is to model driver behaviour more accurately and thereby predict – and ultimately prevent – the initiation and propagation of stop-and-go waves in motorway traffic.

(Photo: Highways Agency)

Bristol University

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