| 期刊全稱 | Behavior Analysis and Modeling of Traffic Participants | | 影響因子2023 | Xiaolin Song,Haotian Cao | | 視頻video | http://file.papertrans.cn/183/182756/182756.mp4 | | 學(xué)科分類 | Synthesis Lectures on Advances in Automotive Technology | | 圖書封面 |  | | 影響因子 | A road traffic participant is a person who directly participates in road traffic, such as vehicle drivers, passengers, pedestrians, or cyclists, however, traffic accidents cause numerous property losses, bodily injuries, and even deaths to them. To bring down the rate of traffic fatalities, the development of the intelligent vehicle is a much-valued technology nowadays. It is of great significance to the decision making and planning of a vehicle if the pedestrians‘ intentions and future trajectories, as well as those of surrounding vehicles, could be predicted, all in an effort to increase driving safety. Based on the image sequence collected by onboard monocular cameras, we use the Long Short-Term Memory (LSTM) based network with an enhanced attention mechanism to realize the intention and trajectory prediction of pedestrians and surrounding vehicles. However, although the fully automatic driving era still seems far away, human drivers are still a crucial part of the road?driver?vehicle system under current circumstances, even dealing with low levels of automatic driving vehicles. Considering that more than 90 percent of fatal traffic accidents were caused by human errors, thus it | | Pindex | Book 2022 |
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