Skip to main content

Derq predicts violations and saves lives

Derq has teamed up with FLIR and the Michigan Department of Transportation (MDoT) to pilot new V2X applications at a busy intersection in Detroit, using artificial intelligence (AI) to predict and prevent vehicle-and pedestrian related-accidents. Located at Jefferson Avenue and Randolph Street near downtown, the pilot uses technology that can predict red light violations and vulnerable pedestrians and bicyclists that are approaching the intersection. Derq AI algorithms analyse video feeds from two FLIR came
June 7, 2018 Read time: 2 mins
© F11photo | Dreamstime.com

8805 Derq has teamed up with FLIR and the Michigan Department of Transportation (MDoT) to pilot new V2X applications at a busy intersection in Detroit, using artificial intelligence (AI) to predict and prevent vehicle-and pedestrian related-accidents.

Located at Jefferson Avenue and Randolph Street near downtown, the pilot uses technology that can predict red light violations and vulnerable pedestrians and bicyclists that are approaching the intersection. Derq AI algorithms analyse video feeds from two FLIR cameras—one thermal sensor and one visual sensor—and identify intent up to two seconds before a violation takes place. The system then alerts approaching drivers via V2X connectivity, giving them plenty of time to take action and avoid collisions. The result is less accidents, fewer injuries and better traffic flow.

The pilot was made possible by a PlanetM Startup Grant. According to CEO George Aoude, Derq and FLIR demonstrated their joint solution in Dubai in 2017 and are exploring other pilot opportunities around the US.

“Connected vehicle pilots are growing around the country and right here in Michigan, and there’s a great opportunity for us to get our technology out there to help save lives,” Aoude said.

Booth 300   

For more information on companies in this article

Related Content

  • University of Michigan wins Transportation Technology Tournament
    July 25, 2019
    A team from the University of Michigan has won the Transportation Technology Tournament for designing a solution to reduce congestion on two interstate highways in the Detroit area. The team presented their solution, Corridor Management in the I-75/I-696 Influence Area, to a panel of judges during a tournament which took place during the Institute of Transportation Engineers annual meeting in Austin, Texas. It focused on mitigating heavy, peak hour traffic volume on I-75 between Detroit and Troy, as
  • Machine vision offers new solutions to old problems
    October 28, 2014
    The transportation sector is set to benefit from a far wider range of machine vision technology. While machine vision techniques have been applied to traffic management applications for some years, in some areas there can still be a shortage of knowledge about what the technology can offer transportation professionals. The image processing and interpretation functions of machine vision enables control room staff to be immediately alerted to occurrences requiring attention which, in turn, enables each person
  • Cost benefit: Wichita eases workzone congestion
    July 8, 2019
    Achieving higher diversion rates has helped one Kansas city to make traffic flow more efficient around workzones. David Crawford examines what’s behind a 10:1 benefit-to-cost ratio in Wichita Around 10% of highway congestion in the US results from delays in workzones, leading to an estimated annual loss of $700 million in fuel costs alone. The lack of accessible real-time traffic information to help motorists minimise their inconvenience – particularly at peak times - is a major contributor. One solut
  • Miovision Scout Plus – the future of traffic data collection
    April 17, 2024
    Miovision is here to introduce the future of traffic data collection. The company say its Scout Plus is a genuine gamechanger. This innovative device seamlessly blends the familiar, user-friendly Scout form factor with cutting-edge features, marking a significant leap forward in its product line.