In this project, we have proposed an integrated in-vehicle decision support system to help driver make better and safer stop/go decisions as a vehicle is approaching a signalized intersection.

  • X. Xie and Z. Wang, “SIV-DSS: Smart in-vehicle decision support system for driving at signalized intersections with V2I communication,” Transportation Research Part C, vol. 90, pp. 181-197, 2018. [PDF] [DOI] [Bibtex]
    @Article{Xie2018SIV,
    Title = {{SIV-DSS}: Smart in-vehicle decision support system for driving at signalized intersections with {V2I} communication},
    Author = {Xiao-Feng Xie and Zun-Jing Wang},
    Journal = {Transportation Research Part C},
    Volume = {90},
    Pages = {181--197},
    PDF={http://www.wiomax.com/team/xie/paper/TRC18Pre.pdf},
    Doi = {10.1016/j.trc.2018.03.008},
    Year = {2018}
    }

Supported by the IoT communications, the system has integrated and harnessed real-time information from both vehicle and infrastructure. Novel decision rules are designed as smart modules utilizing the key physical and behavioral inputs from vehicle motion, vehicle-driver characteristics, intersection geometry and topology, signal phase and timings, and the definition of red-light running (RLR) law. The performance has been evaluated with systematic simulation experiments. The results indicate that the smart system can not only ensure traffic safety by greatly reducing the probability of RLR violations down to zero, but also improve mobility by significantly reducing unnecessary stops at an intersection.

[Case Study] Smart IoT | Intersection Safety