魏诚 讲师

• 学院： 电子与控制工程学院
• 性别： 男
• 出生年月： 1995-10-04
• 职称： 讲师
• 学位： 博士
• 学历： 研究生
• 毕业院校： 长安大学
• 联系电话：
• 电子邮箱： chengwei@chd.edu.cn
• 通讯地址： 长安大学渭水校区
• 邮编： 710000
• 传真：
• 办公地址： 长安大学工训中心
• 教育经历：

魏诚，男，讲师，博士毕业于长安大学交通信息工程及控制专业，主要从事交通大数据分析、自动驾驶测试、自动驾驶具身智能等关键问题的研究。目前已在行业领域期刊发表SCI/EI检索论文10余篇，参与国家重点研发计划项目、国家自然科学基金面上项目、陕西省重点研发等项目多项,目前担任IEEE ITS、IEEE TIM、ESWA等多个国际期刊审稿人。

1.自动驾驶仿真测试

2.自动驾驶具身智能

1. 中央高校基本科研业务费，基础培育项目，主持

2. 自动驾驶AGV控制与监控软件研发，企业委托横向项目，主持

1. Wei, C., Hui, F*., Yang, Z., Jia, S., & Khattak, A. J. (2022). Fine-grained highway autonomous vehicle lane-changing trajectory prediction based on a heuristic attention-aided encoder-decoder model. Transportation Research Part C: Emerging Technologies, 140, 103706

2. Wei, C., Hui, F.*, Khattak, A. J., Zhang, Y., & Wang, W. (2023). Controllable probability-limited and learning-based human-like vehicle behavior and trajectory generation for autonomous driving testing in highway scenario. Expert Systems with Applications, 227, 120336.

3. Wei, C., Hui, F., Khattak, A. J., Mu, K., & Liu, X. (2025). A priori-assisted, parallel heuristic attention-aided encoder–decoder: A data-driven model for autonomous vehicle behavior and trajectory predictions in intersections. Information Sciences, 713, 122179.

4. Wei, C., Mu, K., Hui, F., & Khattak, A. J. (2025). Data-driven configurable scenario generation for testing autonomous driving systems in highway environments. Physica A: Statistical Mechanics and its Applications, 130923.

5. Wei, C., Hui, F., Mu, K., Peng, K., & Li, S. (2023, September). A Neural Network-Based Model with Conditional-Deactivation Structure for Autonomous Vehicle Motivation Prediction at Intersections. In Proceedings of the 2023 International Conference on Power, Communication, Computing and Networking Technologies (pp. 1-10).

6. Wei, C., Hui, F., Zhao, X., Li, S., & Wei, J. (2023, August). An Easy-portable Displacement-offset-based Trajectory Prediction Method for Autonomous Vehicles. In 2023 10th International Conference on Dependable Systems and Their Applications (DSA) (pp. 597-605). IEEE.

7. Wei, C., Hui, F., Khattak, A. J., Zhao, X., & Jin, S. (2023). Batch human-like trajectory generation for multi-motion-state NPC-vehicles in autonomous driving virtual simulation testing. Physica A: Statistical Mechanics and its Applications, 616, 128628.

8. Wei, C., Hui, F., Zhao, X., & Fang, S. (2022, December). Real-time Simulation and Testing of a Neural Network-based Autonomous Vehicle Trajectory Prediction Model. In 2022 18th International Conference on Mobility, Sensing and Networking (MSN) (pp. 641-648). IEEE.

9. Hui, F.,Wei, C.*, & SHANGGUAN, W. (2022). Deep encoder-decoder-NN: A deep learning-based autonomous vehicle trajectory prediction and correction model [J]. Physica A: Statistical Mechanics and its Applications, 593, 126869.

10. Wei, C., Hui, F., & Khattak, A. J. (2021). Driver lane‐changing behavior prediction based on deep learning. Journal of advanced transportation, 2021(1), 6676092.

1. 智能网联车载感知与协同控制关键技术及应用，2024年中国交通运输协技术发明二等奖（5/10）

‍2. 面向车路云一体化的车载网联感知与协同控制关键技术及应用，2025年陕西高等学校科学技术研究优秀成果特等奖（8/10）

1. 2024年7月-至今 长安大学 讲师