The application discloses a highway traffic
inspection method and
system based on
big data processing, and particularly relates to the technical field of highway inspection. The application accesses floating car Beidou, vehicle detectors, accident platforms, structural sensors, weather and other multi-
source data in real time, and unifies cleaning, constructs congestion, accident, pavement, structure, environment multi-dimensional index, and dynamically divides each kilometer road section into 1-4 risk levels. Then, according to the grading result, the risk change rate, the interval from the last inspection and the three factors of sudden events are introduced, and the dynamic inspection priority of each road section is calculated in real time. Finally, the improved VRPTW-PW
algorithm is used to generate the shortest driving and highest priority inspection path under the constraints of vehicle endurance and real-time road conditions. The
system includes five modules of multi-
source data fusion, dynamic grading, frequency optimization, path planning and closed-loop feedback, which can significantly improve the hidden danger discovery rate, reduce the empty driving rate, and realize the precision and intelligence of highway inspection.