Skip to main content

TTI launches Smart Intersection initiative

The Texas A&M Transportation Institute (TTI), Texas A&M University and the City of College Station are joining forces with seven key private sector companies to help design, develop and test safer, smarter intersections, where vehicles alert drivers to stalled traffic miles before the queues begin – and suggest alternate routes. They say the ability to detect traffic flow and volume, analyse complex traffic data in real time, calculate multiple route alternatives and send the resulting recommendations to
June 8, 2016 Read time: 2 mins
The Texas A&M Transportation Institute (TTI), Texas A&M University and the City of College Station are joining forces with seven key private sector companies to help design, develop and test safer, smarter intersections, where vehicles alert drivers to stalled traffic miles before the queues begin – and suggest alternate routes.

They say the ability to detect traffic flow and volume, analyse complex traffic data in real time, calculate multiple route alternatives and send the resulting recommendations to vehicles approaching a congested intersection will change the congestion equation. Rather than dealing with traffic choke points on an intersection-by-intersection basis, such technologies promise to address the problem systemically – to dynamically shift traffic patterns on the fly. The convergence of intelligent vehicle systems, traffic monitoring technologies, and active roadway infrastructure will shift mobility management from a reactive strategy to a dynamic, real-time system.

The Smart Intersections Initiative is the first of several promising developments coming out of the Transportation Technology Conference sponsored by TTI and held last month at the Bush School’s Annenberg Conference Center in College Station, Texas.

Several key players in transportation-related automation, among them 6692 Econolite Group, EDI, 73 Iteris, 772 McCain, MoboTrex, Savari and 189 Siemens, have indicated preliminary interest in the initiative. Talks are underway with others.

The project will be based at The Texas A&M University System’s new RELLIS campus.

The research will be conducted in three distinct environments: laboratory; a controlled environment featuring several intersections constructed at the RELLIS campus; and ultimately at live intersections in the City of College Station.

Work will centre on practical application of evolving automated and connected vehicle and infrastructure technologies. The goal is to streamline signal operations, enhance safety and improve overall mobility.
UTC

Related Content

  • January 25, 2012
    US congestion costs continue to rise
    The 2010 Urban Mobility Report, published by the Texas Transportation Institute at Texas A&M University, concludes that after two years of slight declines in overall traffic congestion - attributable to the economic downturn and high fuel prices - leading indicators suggest that as the economy rebounds, traffic problems are doing the same. While 2008 was the best year for commuters in at least a decade, the problem again began to grow in 2009.
  • March 19, 2014
    Asking drivers what information they need: radical but effective
    When Texas A&M Transportation Institute was asked to devise a temporary traveller information system for work zones, it started by asking drivers what they need. Robert Brydia explains the thinking, implementation and results. US Interstate 35 (I-35) runs roughly north–south originating in Laredo, Texas and ends 1,500 miles away in Duluth, Minnesota having passed through Oklahoma, Kansas, Missouri and Iowa. Within Texas the I-35 splits into I-35E and I-35W passing through Dallas and Fort Worth respectiv
  • June 28, 2018
    Same old mistakes? Try something new
    There’s nothing for it: we need to talk about Mobility as a Service (MaaS). The late Stephen Hawking’s publisher once told him that his readership would be cut in half for every equation he put in a book. Well, here goes nothing… One of the most famous equations in physics is Isaac Newton’s Second Law of Motion: Force = mass x acceleration. With a little tweaking, I think we
  • November 23, 2018
    Cubic: predictive analytics is putting fortune tellers out of business
    The rise of machine learning and artificial intelligence means that fortune tellers will soon be out of business. Ed Chavis takes a behind the scenes look at the world of predictive analytics ver since organisations started taking advantage of insights derived from Big Data, data scientists concentrated their efforts on the ability to make correct assumptions about the future. A few years later, with the help of automation, developments in machine learning (ML) and advancements in the application of a