基于车辆视角数据的行人轨迹预测与风险等级评定

The commonly used pedestrian trajectory and risk prediction model based on roadbed-perspective data often cannot avoid complex modeling calculation and manual judgment. For succinctly and effectively predicting pedestrian trajectory and evaluating risk grade, a pedestrian trajectory and risk grade prediction model is created based on vehicle-perspective pedestrian data in this paper. The acquisition of vehicle-perspective pedestrian data, the prediction of pedestrian trajectory based on long-short term memory neural network and the assessment of risk grade based on clustering analysis - support vector machine method are successively conducted. The results of experiments show that the data-driven model built based on vehicle-perspective pedestrian data can capture the movement tendency and interaction characteristics of pedestrian and vehicle and is capable of predicting pedestrian trajectory and assessing risk grade.