Autopia Planes, Trains, Automobiles and the Future of Transportation

The trouble with traffic information is that often the wrong people have it. A driver close to the scene of an accident knows there’s going to be a huge traffic snarl on the road behind him, but thousands of unsuspecting riders a mile or two from the scene have no idea what’s in store. A driver pulling into a municipal parking lot knows there are only a few spaces left, but no one approaching the lot has a clue. A commuter at a bus stop knows the bus is fifteen minutes late, but people walking to the bus stop aren’t aware of that.

One solution to the problem is to tap into the power of social media. The same technology that links millions of people through sites like Facebook and Twitter is now being seen as a way to combat traffic congestion. By linking commuters into an intelligent social network, people can send and receive relevant information about traffic conditions.

One traffic-related social network service already up and running is called Roadify. With Roadify, commuters send and receive updates that help them find available parking, catch the next bus or train, or avoid traffic snarls before it’s too late. Currently, the service covers only Brooklyn, but already there is talk of rolling out similar social networking services in other congested areas.

The Roadify service gathers data from New York’s Metropolitan Transportation Authority, the state’s Department of Transportation, and web services such as Google Transit. It mashes that information with intelligence gathered by the people who know traffic conditions best: the commuters already on the road. Travelers can send traffic updates through a mobile device to the Roadify site, and the information is immediately shared with other members of the network. Roadify also maintains a database of parking spots, as well as bus and train schedules that can be accessed and updated by any cell phone.

The next step could be to take that real-time traffic information and project it into the future through the use of computer analytics, which use mathematical models to predict how complex systems are likely to behave in the future. Already, advanced analytic software can predict the speed and volume of cars that are likely to be on various streets around a city 45-60 minutes in the future, based on historic traffic patterns. Improving traffic flow then moves from simply reacting to problems (which is usually too late to benefit many travelers), to anticipating trouble starting to form down the road.

A similar traffic service called Streetline takes aim at one of the scarcest commodities in any city – the empty parking space. Traffic experts estimate that more than 30 percent of traffic congestion in cities is caused by drivers circling the block looking for a parking space. Streetline operates a network of low-power sensors that let drivers quickly locate available parking. At the same time, the network can be used by cities to monitor and better manage their own parking resources.

Expect other applications may be added to the Streetline service, such as detecting cars parked near fire hydrants or in red zones and zeroing in on parking meters that need to have coins emptied or to be repaired. Streetline’s web-based and mobile parking service is already up and running in San Francisco, Sausalito, and Los Angeles, and there are plans to bring it to other parking-challenged cities next year.

In the future, traffic and parking information will be gathered by a host of different sources – wireless sensors, remote cameras, and ordinary commuters. When that information is shared through social networks and mobile devices, drivers will be able to tap into the wisdom of the crowd about traffic conditions in time to make smarter choices.