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Mizzou Engineering researcher aims for a smoother ride

Computer Science Professor Yi Shang hopes to harness the potential of a new wireless sensor to reduce traffic congestion and fuel consumption.

A Mizzou Engineering researcher is proposing to use wireless sensor technology to provide some relief to automobile drivers frustrated by traffic congestion and slowdowns.

Computer Science Professor Yi Shang aims to use a new type of battery-powered sensor to create a traffic control system that would be more efficient and significantly less expensive than current systems. Shang is working to develop software that would allow the traffic system’s components to communicate with each other and select the best plan for handling traffic as it occurs, without the need to wire the sensors to a central computer.

“Computational intelligence is distributed throughout the system,” Shang said. “It would be a much cheaper, much more flexible system.”

Transportation experts estimate that improving traffic signal operations would save the United States as much as $45 billion each year. Traffic signal improvements also would cut traffic delays by up to 40 percent, and reduce fuel consumption by as much 10 percent or an estimated 17 billion gallons annually, according to the National Transportation Operations Coalition’s (NTOC) 2007 National Traffic Signal Report Card.

Shang believes a new sensor developed by Sensys Networks potentially offers those improvements. Unlike traditional traffic monitoring sensors that require bulky hardware and underground cables to connect them to a central computer, the California-based company’s small wireless sensors can be embedded in a roadway in 20 minutes and run for 10 years on a battery set.

In hopes of fulfilling the promise these new sensors hold, Shang is developing software that control them intelligently as well as link them to a transportation management network supporting various applications. Shang’s research seeks to connect the sensors to controlling computers housed within nearby traffic lights and the controlling computers to each other.

Part of that software program also would determine the best times to activate, turn off and coordinate the sensors. Traffic sensors help most during rush hours, but can be deactivated during slow times to extend their lifetime—a conservation effort that can be improved with better traffic information, Shang said.

Other software Shang is working on would give the traffic light controlling computers “brains” capable of establishing the best timing plan for managing traffic. The traffic light computers would adapt those plans to real-time information provided by the sensors, incorporating traffic pattern estimates to develop a cohesive management strategy among groups of traffic controllers, Shang said.

Combined, the softwares would provide the intelligent control that more traditional systems obtain from costly central computers running for an extended time, he said.

“With this new technology, we can start to do more,” Shang said. “We can make the system more efficient, flexible, responsive and robust.”

And more adaptable. Shang proposes to use the sensor system to help devise the best routes for public transit, based on travel time and traffic. The system also could provide up-to-date traffic information that would help public transportation operators maneuver around stoppages, he said.

The sensors also could work as a navigation system, providing a service akin to that offered by the global positioning system’s (GPS) navigation network, Shang said. While GPS signals may be muffled by tall buildings in densely populated cities, traffic sensors embedded in the road would act as beacons regardless of the environment, he said.

“Intelligent traffic monitoring and control using wireless sensors in transportation infrastructure creates a paradigm shift that has the potential to revolutionize the transportation system,” Shang said.