Short-term vehicle trajectory prediction using attention mechanism integrated GRU network

Tian Xie; Zhifa Chen; Peng Chen

doi:10.1117/12.2684176

14 June 2023 Short-term vehicle trajectory prediction using attention mechanism integrated GRU network

Tian Xie, Zhifa Chen, Peng Chen

Proceedings Volume 12708, 3rd International Conference on Internet of Things and Smart City (IoTSC 2023）; 1270836 (2023) https://doi.org/10.1117/12.2684176
Event: 3rd International Conference on Internet of Things and Smart City (IoTSC 2023）, 2023, Chongqing, China

Abstract

Predicting the motion and behavior of surrounding vehicles is an essential task for motion planning and decision-making of autonomous vehicles in complex traffic conditions. In this paper, we propose a short-term vehicle trajectory prediction framework using attention mechanism integrated GRU network. We use an encoder-decoder model as the main architecture. A gate recurrent unit (GRU) coupled with temporal attention and graph attention is used to extract and fuse more important information which could be used for trajectory prediction. The temporal attention could extract temporal information and graph attention could consider interactions between surrounding vehicles within sensing range. The extracted information is fed into fully connected layers to obtain predicted trajectory. The publicly next generation simulation (NGSIM) I-80 and US-101 datasets are used to evaluate proposed model. Compared to other prediction models, our model shows improvement on final displacement error (FDE) and average displacement error (ADE). The results show that model with attention mechanism improves prediction accuracy by 1% ~5% in 5 second prediction horizon.

Citation Download Citation

Tian Xie, Zhifa Chen, and Peng Chen "Short-term vehicle trajectory prediction using attention mechanism integrated GRU network", Proc. SPIE 12708, 3rd International Conference on Internet of Things and Smart City (IoTSC 2023）, 1270836 (14 June 2023); https://doi.org/10.1117/12.2684176

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KEYWORDS

Feature extraction

Data modeling

Autonomous vehicles

Motion models

Roads

Data processing

Network architectures

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