车速预测模型的发展现状及趋势

doi:10.16638/j.cnki.1671-7988.2025.005.029

摘要/Abstract

摘要： 车速预测可以实现对潜在危险的有效预警，优化交通效率的同时降低油耗，提高驾驶员及乘车人的驾驶体验和安全性。文章以车速预测模型为研究对象，通过文献调研和资料分析相结合的方式，深入对比分析了传统与最新车速预测模型的优劣差异，为后续车速预测模型研究提供参考。结果表明，多信息耦合车速预测模型已成为未来研发趋势，在为自动驾驶和智能交通系统提供更加精准、可靠和实时的速度信息中，发挥愈发重要的作用。

关键词: 车速预测模型；交通效率；驾驶体验；智能交通系统

Abstract: Speed prediction can achieve the effective early warning of the potential hazards, optimizing traffic efficiency while reducing fuel consumption, and enhancing both drivers and passengers experience and safety. This paper takes the vehicle speed prediction model as the research object, and through the combination of literature investigation and data analysis, deeply compares and analyzes the advantages and disadvantages of the traditional and the latest vehicle speed prediction model, so as to provide reference for the subsequent research on vehicle speed prediction model.The results show that the multi-information coupled vehicle speed prediction model has become the trend of future research and development, and plays an increasingly important role in providing more accurate, reliable and real-time speed information for autonomous driving and intelligent transportation systems.

Key words: speed prediction model; traffic efficiency; driving experience; intelligent transportation systems

朱凯家，王浩然. 车速预测模型的发展现状及趋势[J]. 汽车实用技术, 2025, 50(5): 153-157,162.

ZHU Kaijia, WANG Haoran. The Development Status and Trend of Vehicle Speed Prediction Model[J]. Automobile Applied Technology, 2025, 50(5): 153-157,162.

参考文献

[ 1 ] 陈丹霞,陈国波.新形势下智慧交通管理信息化建设的路径及实践[J].中国管理信息化,2022,25(12):208- 210. [ 2 ] 王笑.基于模型预测的智能车换道轨迹规划与跟踪控制研究[D].青岛:青岛理工大学,2023. [ 3 ] LIN C C,WANG M S.Vehicle Speeding Early Warning Model Using Frame Feature Detection and HMM[C]// 2011 IEEE 15th International Symposium on Consumer Electronics.Piscataway:IEEE,2011:241-244. [ 4 ] GUO J,HUANG W,WILLIAMS B M.Adaptive Kalman Filter Approach for Stochastic Short-term Traffic Flow Rate Prediction and Uncertainty Quantification[J]. Transportation Research Part C:Emerging Technologies,2014,43(2):50-64. [ 5 ] 袁鲁山.基于 NAR 神经网络的车速预测及应用[D]. 大连:大连理工大学,2016. [ 6 ] 徐韬.基于浮动车数据的道路运行车速动态预测研究[D].重庆:重庆交通大学,2017. [ 7 ] 谢浩.基于 BP 神经网络及其优化算法的汽车车速预测[D].重庆:重庆大学,2014. [ 8 ] LI Q,CHENG R,GE H.Short-term Vehicle Speed Prediction Based on Bilstm-GRU Model Considering Driver Heterogeneity[J].Physica A:Statistical Mechanics and Its Applications,2023,610:128410. [ 9 ] CHENG Z,CHOW M Y,JUNG D,et al.A Big Data Based Deep Learning Approach for Vehicle Speed Prediction[C]//2017 IEEE 26th International Symposium on Industrial Electronics.Piscataway:IEEE,2017: 389-394. [10] XIE H,HU D,SONG K.An Iterative Optimization Algorithm for Vehicle Speed Prediction Considering Driving Style and Historical Data Effects[C]//2021 40th Chinese Control Conference.Piscataway:IEEE, 2021:6094-6100. [11] 郭兴,马彬,杨朝红,等.考虑驾驶行为预判的改进 ARIMA 车速短期预测方法[J].重庆理工大学学报 (自然科学),2022,36(1):51-59. [12] 朱杰.基于行车监测数据的驾驶员风格辨识及车速预测研究[D].重庆:重庆交通大学,2020. [13] 张英杰.基于驾驶工况预测的安全辅助策略研究[D]. 北京:北京交通大学,2020. [14] 刘文祥.基于交通状态预测的车辆经济车速优化方法[D].大连:大连理工大学,2019. [15] 聂浩.考虑交通信息的插电式混合动力汽车智能能量管理策略研究[D].济南:山东大学,2021. [16] XIANG C L,DING F,WANG W D,et al.MPC-based Energy Management with Adaptive Markov-Chain Prediction for a Dual-mode Hybrid Electric Vehicle[J]. Science China Technological Sciences,2017,60(5): 737-748. [17] 刘吉超,陈阳舟.基于 GA-PSO 混合优化的 BPNN 车速预测方法[J].交通运输系统工程与信息,2017,17 (6):40-47. [18] ZHANG Z Y,SHEN J H,YAO D W,et al.Research on Self-adaptive Online Vehicle Velocity Prediction Strategy Considering Traffic Information Fusion[J].Preprint arXiv,2022(1):03402. [19] LAI W K,KUO T H,CHEN C H.Vehicle Speed Estimation and Forecasting Methods Based on Cellular Floating Vehicle Data[J].Applied Sciences,2016,6(2): 47-65. [20] PARK J,LI D,MURPHEY Y L,et al.Real Time Vehicle Speed Prediction Using a Neural Network Traffic Model[C]//The 2011 International Joint Conference on Neural Networks.Piscataway:IEEE,2011:2991-2996. [21] JIANG B,FEI Y.Vehicle Speed Prediction by TwoLevel Data Driven Models in Vehicular Networks[J]. IEEE Transactions on Intelligent Transportation Systems,2016,18(7):1793-1801. [22] 楼挺.基于深度学习的道路车速预测模型研究[D].杭州:浙江工业大学,2019. [23] 潘龙帅,高建平,宋哲,等.多源信息融合的车速预测方法及整车能量管理[J].河南科技大学学报(自然科学版),2020,41(6):23-31. [24] 李婷婷.基于深度学习的纯电动车预测性节能控制研究[D].太原:中北大学,2022. [25] LI Y F,CHEN M N,LU X D,et al.Research on Optimized GA-SVM Vehicle Speed Prediction Model Based on Driver-vehicle-road-traffic System[J].Science China Technological Sciences,2018,61(5):782-790. [26] XIONG Z,LI H,XIAO S.Urban Road Speed Prediction Based on Multisource Feature Bidirectional Long Short-term Memory[J].Advances in Transportation Studies,2021,55:265-282. [27] YANG J Y,CHOU L D,TUNG C F,et al.Average-speed Forecast and Adjustment via VANETs[J].IEEE Transactions on Vehicular Technology,2013,62(9):4318- 4327. [28] YE M,CHEN J,LI X,et al.Energy Management Strategy of a Hybrid Power System Based on V2X Vehicle Speed Prediction[J].Sensors,2021,21(16):5370.