In recent years, various mathematical models and experimental measurements of traffic patterns have led to a consensus about the general kinds of traffic flows that can occur. There are three types.
First is free flow in which the density of traffic is low enough to allow vehicles to travel at the maximum speed allowed. Then there is synchronised flow when a higher traffic density forces cars to travel at similar slow speeds but without stop-start motion. Finally, there is the jam in which the speed drops to zero when the traffic density rises above some threshold.
The way the flow transitions from one regime to another is hugely complex but a number of models, in particular those using cellular automaton, have become useful in studying how it occurs.
One interesting question is how best to dissolve jams once they form. Most traffic experts agree that the basic idea is to ensure that cars leave the jam more quickly than they arrive, so that the jam dissolves.
Now Hyun Keun Lee and Beom Jun Kim at the University of Seoul in South Korea have a come up with a simple idea to automate and improve this dissolving process. They define two types of drivers: optimistic and defensive. Defensive drivers leave more room to the vehicle ahead than required by safety. Optimistic drivers leave too little.
They then use a cellular automaton to model traffic flow in a way that reproduces most of the usual driving behaviours such as exceeding the speed limit, overreacting to road conditions by accelerating and braking to hard and so on.
But they also add an extra ingredient. All the vehicles in this model share their speed and position with their neighbours and this information filters downstream. That means downstream vehicles immediately become aware that the traffic ahead has come to a standstill.
When that happens, Lee and Kim’s algorithm immediately switches all the downstream driving behaviour to defensive, so that vehicles exceed the safe distance between them. This slows the rate at which vehicles join the jam.
At the same time, vehicles leaving the jams are made to accelerate away quickly using automated cruise control. This increases the rate at which vehicles leave the jam.
The result is that the jam quickly dissolves.
That’s an interesting and simple approach that could be implemented relatively easily in the next generation of cars. It’s greatest value is that it requires no central control, only an on-board algorithm on most cars. It also requires a little more automated on-board control than cars currently have but not an unrealistic amount.
But it will require a little more modelling to ensure that this kind of group control doesn’t lead to other emergent behaviour that could be detrimental. Neither is it clear what percentage of cars must be fitted with this ability for the effect to work. But it certainly looks worthy of further investigation.
It’s a little premature to say the traffic jams could be banished from the roads of the future but we may bot have to spend as long sitting in them.
Ref: arxiv.org/abs/1109.2191: Dissolution Of Traﬃc Jam Via Additional Local Interactions
How a Russian cyberwar in Ukraine could ripple out globally
Soldiers and tanks may care about national borders. Cyber doesn't.
Meet Altos Labs, Silicon Valley’s latest wild bet on living forever
Funders of a deep-pocketed new "rejuvenation" startup are said to include Jeff Bezos and Yuri Milner.
Meta’s new learning algorithm can teach AI to multi-task
The single technique for teaching neural networks multiple skills is a step towards general-purpose AI.
Going bald? Lab-grown hair cells could be on the way
These biotech companies are reprogramming cells to treat baldness, but it’s still early days.
Get the latest updates from
MIT Technology Review
Discover special offers, top stories, upcoming events, and more.