Navigation Content
University of Wisconsin Madison College of Engineering
You are here:
  1. Home > 
  2. News > 
  3. News archive > 
  4. 1996 > 

Intelligent Highway Systems to Ease Gridlock

In a big city, it always seems as though there are more cars than could possibly fit on the freeway. "The infrastructure is always lagging behind, so you will always have more cars on the road than you can handle," Civil and Environmental Engineering Assistant Professor Bin Ran says. That's because the public won't fund new highways until the old ones are hopelessly overcrowded, he says.

But there may be another way to ease congestion, Ran says. If the highway system were to be fully automated, many more vehicles could be squeezed into existing roads. "Instead of investing in concrete and pavement, we are investing in computers and communications equipment and control devices. It is a change of concept for conservation," he says. Moving traffic more efficiently also reduces pollution and saves fuel.

Professor in Traffic

Even at the peak of rush hour, traffic in Madison runs smoothly compared to that of major cities. If Bin Ran has his way, Intelligent Vehicle-Highway Systems will someday control the country's major highways, saving fuel, reducing pollution and sparing Madison big-city gridlock. (large image)

In Ran's ultimate transportation system, or Intelligent Vehicle-Highway System, motor vehicles would be guided by on-board computers that receive information from navigational satellites and transmit information to a centralized computer. These command centers would coordinate the routing, speed, arrival and departure times of cars, trucks, trains, airplanes and watercraft.

Rudimentary computerized traffic routing systems are already in place in California and Illinois. And satellite-aided systems are guiding fleets of rental cars in such oft-visited areas as Tampa, Florida and Chicago, Illinois. Ran's specialty is finding the best way for these systems' components to interact. He creates mathematical models of the networks of computers and vehicles in an intelligent highway. By using real-time or close to real-time data, Ran's models attempt to find the best possible routes for all vehicles on the road. If an accident blocks one expressway, for example, you can't just send everyone on the next shortest route, creating another jam somewhere else.

The trickiest part, however, may be accounting for individuals' personalities. To model how people react to alternatives the system suggests, Ran stratifies people into groups according to such variables as age, willingness to follow instructions and stubbornness. "About 80 percent of the people are very stubborn," he says. "They don't want to change their routes." That's one reason that it is important for the system provide reliable instructions. Once "burned," these people won't trust an alternative again.

Archive