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In a mixed traffic ecosystem, accurately predicting the trajectories of surrounding vehicles is crucial for the safety of autonomous vehicles. However, existing technologies still face issues of accuracy and computational complexity in longterm prediction. A spatiotemporal interactive sparse attention model combined with intention probability is proposed in this paper, which predicts trajectories through an efficient encoderdecoder structure. The position mask matrix is first constructed to extract positional information from historical trajectories, and key features are selected using the sparse attention mechanism. The intention behavior analysis module is utilized to improve the accuracy of intention recognition. Finally, spatiotemporal features, positional features, and intention features are fused and input into the decoder, and the model is trained using a multitask learning approach. The experimental results show that, compared to the optimal algorithm on the HighD and NGSIM datasets, the proposed model achieves a notable reduction in root mean square error (RMSE) in longterm prediction of 3 to 5 seconds, significantly enhancing prediction accuracy. In addition, the model's performance in realworld scenarios is validated through road tests, further demonstrating its application potential in complex traffic environment.
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| 科 Family | 属数 Number of genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) | 属 Genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) |
|---|---|---|---|---|---|---|
| 鹅膏菌科Amanitaceae | 2 | 11 | 5.26 | 鹅膏菌属 Amanita | 10 | 4.78 |
| 小菇科 Mycenaceae | 2 | 12 | 5.74 | 丝盖伞属 Inocybe | 5 | 2.39 |
| 多孔菌科 Polyporaceae | 8 | 14 | 6.70 | 蜡蘑属 Laccaria | 5 | 2.39 |
| 红菇科 Russulaceae | 3 | 23 | 11.00 | 小皮伞属 Marasmius | 6 | 2.87 |
| 小菇属 Mycena | 11 | 5.26 | ||||
| 光柄菇属 Pluteus | 5 | 2.39 | ||||
| 红菇属 Russula | 17 | 8.13 | ||||
| 栓菌属 Trametes | 5 | 2.39 |
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