The invention discloses a traffic road jam prediction method based on a
particle swarm algorithm; the method comprises the following steps: S1, using a
sensor system on the terminal side and a trafficmonitoring
system in a road intersection to gather traffic data, and uploading the data to a
cloud server; S2, enabling the
cloud server to receive the traffic data and process the data via the improved
particle swarm algorithm, thus obtaining prediction data; S3, enabling the
cloud server to send the prediction data to equipment on the terminal side; S4, enabling the equipment on the terminal side to receive data returned by the cloud
server, and storing the data in a local storage device; S5, enabling the cloud
server to obtain the traffic data gathered by the terminal and the traffic
monitoring system in real time, taking the traffic data as new input variables, continuously learning according to the improved
particle swarm algorithm, and continuously optimizing the prediction data. The method can obviously improve the prediction precision, can effectively adjust the
traffic flow, can reduce the traffic loads, can reduce transportation
delay and parking rate, thus improving the road network passing ability, and improving the city
traffic conditions.