Same as novel coronavirus has spread from person to person throughout the world, so too has traffic spread through highways and urban centers such as infectious diseases. From one collision, traffic jams swept across the city, and now scientists have a model to prove it. Researchers in Australia, Iran, and the US have modified the general model to map the spread of the disease to show that it also serves to describe the spread of traffic jams – only in this case the cars infect each other with congestion instead of mutual people infect each other. another with a virus.
Strangely, they found that in six different cities – Chicago, London, Melbourne, Montreal, Paris and Sydney – traffic spread very closely. “We can calculate how quickly congestion spreads in the network, and that actually doesn’t depend on the geography and topography of the city,” said New South Wales University engineer Meead Saberi, lead author on new paper in Natural Communication describe the work. “It can be anywhere in the world, and the dynamics of its spread are very similar.”
More about how that happened – but first, let’s talk about those models. One way to characterize the spread of diseases such as Covid-19 is known as a susceptible model infected-recovered. Susceptible means a group of people who have never been sick before and now can get sick; infected means those who are sick now; and recover means those who have defeated the disease. Because recovering is now invulnerable, pandemics tend to decrease over time, because viruses have fewer and fewer potential hosts that can infect.
Adapting this model to characterize traffic, the researchers looked at “links” and not people, which means a physical road between two intersections. (Four-way stops are technically two roads together, but each direction is counted as one link.) And instead of studying biological symptoms such as coughing or fever, they study traffic jams, aka traffic jams where cars slow down and retreat as solid mass. “We have three types of links in the network,” Saberi said. “Links that are prone to traffic, links that are stuck, and links that have been stuck and are now being restored.” So the analogy is the same, he said, but “from a traffic perspective.”
The dynamics of this traffic are well understood. Say you are on the freeway. There was an accident in front, and everyone was unconscious as they passed. When one person slows down, the cars behind them slow down in a predictable way. They all have to be slow in the end, don’t let every car hit the one in front of it. But because traffic increased again after the accident, the acceleration was less predictable. Drivers accelerate according to their wishes – some slamming gas, while others accelerate more slowly. That is, nothing coercion: Drivers do not need to behave in a certain way, because there are no more rubber drivers in front of them.
As a result of this stop-and-go phenomenon, congestion spreads like transmission between a car and recovering when an accident is cleared from the road. “We have shown that, yes, the transmission model at the macroscopic level can describe the spread of traffic congestion,” Saberi added. “And we use some empirical data from six different cities around the world to show that it’s actually universal.”
But how can traffic spread in the same way in a labyrinth city like London as it does along a more organized grid like the one in Chicago? It turns out that this is not about the layout of the road itself, but rather how the roads intersect – that is, how many links connect the average of each intersection.
In Chicago’s relatively organized layout, there are many intersections where two roads – or four links – meet. In Paris, sometimes five or six links can meet per intersection. “But when we look at all these different cities – even though they have very, very different urban forms – the average number is almost the same,” Saberi said. “So it is somewhere between two and three – every intersection, there is somewhere between two and three united roads. And that’s why, even though the topography is different, the results will be the same, because the average number of vertices is almost the same for them. “
Models like this can help city officials better manage their traffic, treat “illnesses” before they can spread. To add an economic touch to the metaphor, “if you travel on the freeway, and are very congested, there are costs for you in lost time, in wasted fuel,” said Bob Pishue, a transportation analyst at the traffic data company Inrix, who are not involved in this new work. “So the people in that case – if the costs are very high – they will turn to the side of the road, where they think the costs are cheaper. That’s kind of the way you see outgoing traffic. “The costs are piled up when the spread of traffic spreads, until the city squares are sick and unproductive.
But the disease model does have some limitations. One is that while roads can be infected by traffic, they then do not develop immunity to traffic – their congestion can return as severely the next day. At present, this model can only describe what happens during one particular traffic peak, for example at night rush hour. In addition, the researchers developed a macroscopic model, so that they cannot tell you precisely that congested roads, how quickly the congestion spreads in certain cities. “So you know that, for example, during this period, half of the links on the network, or 10 percent of links on the network, became congested,” Saberi said.
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