摘要
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.
投稿的翻译标题 | Pedestrian Trajectory Prediction and Risk Grade Assessment Based on Vehicle-Perspective Pedestrian Data |
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源语言 | 繁体中文 |
页(从-至) | 675-683 |
页数 | 9 |
期刊 | Qiche Gongcheng/Automotive Engineering |
卷 | 44 |
期 | 5 |
DOI | |
出版状态 | 已出版 - 25 5月 2022 |
已对外发布 | 是 |
关键词
- Clustering analysis
- Long short term memory neural network
- Pedestrian risk grade assessment
- Pedestrian trajectory prediction
- Support vector machine
- Vehicle-perspective pedestrian data