Tackling Traffic Through the Internet of Things
As millennials flood urban areas, cities, long plagued by automotive traffic, are growing more congested. According to the Atlantic, the American commuter spends an average of 38 hours a year stuck in traffic. Not only is this state of affairs economically inefficient, it decreases the quality of life and safety --for drivers, but also, increasingly, pedestrians. While fatalities from automotive accidents have declined somewhat over the last decade, among them, pedestrian fatalities have grown. Consequently, there is growing demand for infrastructural fixes and better and more public transit.
But smart technologies -- not more highways and train tracks – could solve these problems for tomorrow’s cities. Presentations at the recent SmartAmerica Expo in Washington, D.C. offered glimpses of what the 21st century city will look like.
Much of the congestion in present-day cities is due to “stupid” problems. A surprisingly high of percentage of automotive traffic, for example, is attributable to drivers just searching for parking – 30% according to some estimates. All urban dwellers know the frustration of trying to find parking. What if you could know where to find it?
Qualcomm and Audi have developed Vehicle-to-Cloud services that use NRIX data streams to provide real-time updates on available metered street, lot, and garage parking. Soon more smart automobile services will be available, including dynamic interaction with traffic signals.
Other surprisingly significant causes of automotive traffic include small or large inefficiencies (stopped vehicles, blocked lanes, rubbernecking) whose effects ripple out – akin to putting small kinks in a large hose. Everyone is familiar with the experience of “phantom traffic jams,” where traffic backups linger long after the original obstruction has been removed.
Researchers at Vanderbilt and UC Berkeley are working on smart roads technologies, which connect and coordinate the varieties of technologies currently used to monitor traffic flow, from ramp meters and traffic signals to changeable message signs. This, along with traffic signal-vehicle interaction, offers hope for a radically more efficient driving ecosystem.
As for safety: the imminence of so-called V2V or Vehicle-to-Vehicle communications has become well-known. In partnership with Qualcomm, Honda is bringing the potential safety benefits of V2V technologies to pedestrians. A new vehicle-to-pedestrian communication technology, which coordinates with Qualcomm enabled smartphones, will help prevent accidents between cars and people by warning both drivers and pedestrians of “near crash collision scenarios.”
But all of this is mere prelude to the coming era of the autonomous vehicle. The above technologies are helping to create a smart automotive ecosystem, which will one day soon be populated with driverless vehicles.
In addition to Google, the U.S. military is helping to bring this sci-fi fantasy into reality. The U.S. Army’s Tank Automotive Research Development and Engineering Center (TARDEC) has created, with private and academic partnerships (including Stanford), the Applied Robotics for Installations and Base Operations (ARIBO) program. ARIBO aims to study robotic vehicles in real-world settings by gathering and analyzing data pertaining to the use and infrastructure of autonomous electric vehicles personnel shuttles. The pilot program is already underway at Fort Bragg and is coming soon to West Point.
As driverless vehicles go mainstream, the nature and efficiency of traffic flows will be dramatically changed. Whatever the cultural and psychological challenges, cost and energy savings, personal safety, and overall efficiency will win the day. Driving in the future may feel a lot more like taking public transit than the stop-and-go commute known and reviled by all.
All of this is possible, of course, thanks to smart sensor technologies, sophisticated data analytics and the declining cost of computing—the data-driven economy. Look to data, not centuries old infrastructural tools, for solutions to the urban traffic challenge.