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A new method was proposed for traffic incident detection based on particle swarm optimizer neural network. At first, the vehicular laser rangefinder and GPS equipment were used as the experimental platform, which collected the traffic parameters including the road vehicle occupancy rate and the vehicle running speed;Secondly,the particle swarm optimizer(PSO) was used to train the random initial data to optimize the connection weights and thresholds of the back-propagation(BP) neural network;Finally The BP neural network after optimization was used to classify traffic incidents automatically. In the detection experiment, PSO neural network, BP neural network and traditional algorithms were compared in the same testing environment. PSO neural network was superior to the other objective algorithm in incident detection rate(DR) and mean time to detection(MTTD).Results showed that particle swarm optimizer neural network brought a promising improvement in the detection capability for traffic incident detection.