2020-LI-68904: Addressing the problems of running a red light at traffic intersections


Each year over 2 million crashes occur at signalized intersections, with hundreds of thousands and injuries and over 3,000 fatalities. In addition, heavy vehicles lead to a fatality rate in crashes that is five times higher than that of passenger vehicles. Traditional technologies typically extend a green light signal to enable passenger cars to save time; however, this requires expensive infrastructure.


Purdue researchers have developed a new system to help manage signalized intersections and mitigate risk associated with running red lights. It features a wireless communication network with devices located at the traffic signals and in vehicles. Vehicles are identified by the traffic signal as they arrive at an intersection. The system calculates the trajectory of a vehicle reaching the signal and, via embedded intelligence, the system can change either extend green or indicate yellow early to ensure the vehicle has ample time to stop.


Purdue University News Release


Howell Li, principal research analyst, Lyles School of Civil Engineering, College of Engineering


Addressing the problems of running a red light at traffic intersections: 2020-LI-68904


Phone: (765) 588-3475
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Email: otcip@prf.org


Email: sgmartin@prf.org


Using Connected Vehicle Data to Reassess Dilemma Zone Performance of Heavy Vehicles


The rate of fatalities at signalized intersections involving heavy vehicles is nearly five times higher than for passenger vehicles in the US. Previous studies in the US have found that heavy vehicles are twice as likely to violate a red light compared with passenger vehicles. Current technologies leverage setback detection to extend green time for a particular phase and are based upon typical deceleration rates for passenger cars. Furthermore, dilemma zone detectors are not effective when the max out time expires and forces the onset of yellow. This study proposes the use of connected vehicle (CV) technology to trigger force gap out (FGO) before a vehicle is expected to arrive within the dilemma zone limit at max out time. The method leverages position data from basic safety messages (BSMs) to map-match virtual waypoints located up to 1,050 ft in advance of the stop bar. For a 55 mph approach, field tests determined that using a 6 ft waypoint radius at 50 ft spacings would be sufficient to match 95% of BSM data within a 5% lag threshold of 0.59 s. The study estimates that FGOs reduce dilemma zone incursions by 34% for one approach and had no impact for the other. For both approaches, the total dilemma zone incursions decreased from 310 to 225. Although virtual waypoints were used for evaluating FGO, the study concludes by recommending that trajectory-based processing logic be incorporated into controllers for more robust support of dilemma zone and other emerging CV applications.