Research Progress and Prospects of Vehicle Driving Behavior Prediction
Abstract
:1. Introduction
2. Research on Individual Intelligent Vehicle Driving Behavior Prediction
2.1. Individual Intelligent Vehicle Motion-Planning Model
2.2. Prediction of Individual Intelligent Vehicle Behavior Recognition
2.2.1. Prediction of Individual Intelligent Vehicle Driving Behavior on Roads
2.2.2. Prediction of Individual Intelligent Vehicle Driving Behavior at Intersections
2.3. Research Comments
- 1.
- Individual intelligent vehicle motion-planning model
- 2.
- Prediction of individual intelligent vehicle driving behavior on roads
- 3.
- Prediction of individual intelligent vehicle driving behavior at intersections
3. Research on IoV Driving Behavior Prediction
3.1. IoV Model Optimization
3.2. Prediction of IoV Driving Behavior
3.2.1. Prediction of IoV Driving Behavior on Roads
3.2.2. Prediction of IoV Driving Behavior at Intersections
3.3. Research Comments
- 1.
- IoV model optimization
- 2.
- Prediction of IoV driving behavior on roads
- 3.
- Prediction of IoV driving behavior at intersections
4. Research on Predictive Problems in Mixed Traffic Driving Environments
4.1. Research on Automatic–Manual Mixed Traffic Flow
4.2. Research Comments
5. Conclusions
5.1. Shortcomings
5.2. Prospects
- 1.
- Recognition of driving status based on vehicle files
- 2.
- Realization of fully autonomous driving based on all-element traffic information perception
- 3.
- Virtual simulation experiments
- 4.
- Prediction of driving behavior in mixed traffic flows
- 5.
- Autonomous “agents”
Author Contributions
Funding
Conflicts of Interest
References
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Research Objective | Author | Year | Opinion or Model |
---|---|---|---|
Review | Thomas [1] | 1994 | Emphasized the importance of driving behavior analysis |
Kumar et al. [2] | 2015 | Driver behavior models significantly differ for different vehicle drivers | |
Chen et al. [4] | 2016 | Believed that functional models are superior to descriptive models | |
Xiong et al. [3] | 2018 | Based on the potential of the learning algorithm model | |
Intent recognition | Berndt [5] | 2008 | Used HMM to recognize driving intention |
Zhu et al. [6] | 2017 | Recognition method of driving behavior based on SVM | |
Liu et al. [8] | 2018 | HMM and SVM | |
Zong et al. [9] | 2009 | Proposed HMM and ANN driver behavior prediction models | |
Zhang et al. [10] | 2019 | MV-CNN has better generalization ability than ANN | |
Zhang et al. [7] | 2021 | SVM optimization | |
Trajectory prediction | Ye et al. [11] | 2016 | Established dynamic model to predict vehicle trajectory |
Hu et al. [12] | 2018 | AV path planning method based on discrete optimization | |
Ji et al. [13] | 2019 | Vehicle trajectory prediction model based on LSTM |
Research Objective | Author | Year | Opinion or Model |
---|---|---|---|
Straight | Luo et al. [16] | 2009 | Improve driving comfort and fuel economy |
Zhu et al. [14] | 2017 | ACC strategy based on response time | |
Zhu et al. [15] | 2019 | ACC car-following control optimization | |
Lane-changing | Schreier et al. [19] Toru et al. [20] | 2014 | Lane-changing probability of dynamic Bayesian network |
Schlechtriemen et al. [21] | 2015 | Prediction of lane-changing based on random forest method | |
Chen et al. [17] | 2017 | Combining rough set urban environment lane-changing rules | |
Jiang et al. [18] | 2019 | Autonomous driving emergency lane-changing rules | |
Intersections | Song et al. [22] | 2016 | Intention perception of driver at intersection |
Cheng et al. [23] | 2019 | Intersection driving game model | |
Yang et al. [24] | 2019 | USI multiple impact variables |
Chapter | Research Objective | Summary | Author/Year | |
---|---|---|---|---|
Individual intelligent vehicle motion-planning model | Review | Reviewed and analyzed driving behavior models from different perspectives | Thomas/1994 [1] Kumar et al./2015 [2] Chen et al./2016 [4] Xiong et al./2018 [3] | |
Intent recognition | The introduction of machine learning and other technologies to intelligent vehicle control | Berndt/2008 [5] Zhu et al./2017 [6] Liu et al./2018 [8] Zong et al./2009 [9] Zhang et al./2019 [10] Zhang et al./2021 [7] | ||
Trajectory prediction | Ye et al./2016 [11] Hu et al./2018 [12] Ji et al./2019 [13] | |||
Prediction of individual intelligent vehicle behavior recognition | On-road | Straight | Development and optimization of ACC | Luo et al./2009 [16] Zhu et al./2017 [14] Zhu et al./2019 [15] |
Lane-changing | Safe and reliable lane-changing control systems are needed | Schreier et al./2014 [19] Toru et al./2014 [20] Schlechtriemen et al./2015 [21] Chen et al./2017 [17] Jiang et al./2019 [18] | ||
At intersections | Its efficiency and safety are yet to be investigated | Song et al./2016 [22] Cheng et al./2019 [23] Yang et al./2019 [24] |
Research Objective | Author | Year | Opinion or Model |
---|---|---|---|
Straight | |||
ACC car-following model | Jin [30] | 2011 | Car-following model based on driver behavior |
Su et al. [29] | 2018 | Personalized car-following model | |
Yang et al. [31] | 2019 | Data-driven car-following model | |
Lane-changing | |||
Lane-changing intention | Geng et al. [32] | 2015 | A priori and a posteriori lane-changing prediction |
Huang et al. [33] | 2019 | Trajectory planning and control based on driving style | |
Tejada et al. [34] | 2020 | Based on models of ‘typical’ human driving behavior | |
Lane-changing safety | Huang et al. [35] | 2015 | Behavior analysis method based on OBD |
Bussooa et al. [36] | 2019 | Monitoring illegal lane-changing behavior using IoT | |
Wu et al. [37] | 2019 | Collision avoidance model based on vehicle contour | |
Zhang et al. [38] | 2020 | AV high-speed collision avoidance model | |
Xue et al. [39] | 2020 | Dangerous vehicle marking | |
Intersections | |||
Intersection cooperative control | Xiong et al. [40] | 2014, 2015 | Intersection cooperative control method based on HMM |
Song et al. [41] | 2016 | Decision-making model for intersection behavior | |
Duan et al. [42] | 2020 | Multivehicle cooperative control based on V2I and V2V intersections |
Author | Year | Opinion or Model |
---|---|---|
Bose et al. [44] | 1999 | Automatic–manual mixed traffic flow characteristics in a single lane |
Huang et al. [46] | 2000 | Coexistence of AVs and manual vehicles |
Ioannou et al. [45] | 2003 | Analyzed and studied automatic and manual driving Q-K diagrams |
Qiu et al. [47] | 2016 | Mixed traffic flow model |
Ye et al. [50,51,52,53] | 2018 | ICV modeling method in mixed traffic flow |
Qin et al. [49] | 2019 | Car-following model of heterogeneous traffic flow |
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Hu, X.; Zheng, M. Research Progress and Prospects of Vehicle Driving Behavior Prediction. World Electr. Veh. J. 2021, 12, 88. https://doi.org/10.3390/wevj12020088
Hu X, Zheng M. Research Progress and Prospects of Vehicle Driving Behavior Prediction. World Electric Vehicle Journal. 2021; 12(2):88. https://doi.org/10.3390/wevj12020088
Chicago/Turabian StyleHu, Xinghua, and Mintanyu Zheng. 2021. "Research Progress and Prospects of Vehicle Driving Behavior Prediction" World Electric Vehicle Journal 12, no. 2: 88. https://doi.org/10.3390/wevj12020088
APA StyleHu, X., & Zheng, M. (2021). Research Progress and Prospects of Vehicle Driving Behavior Prediction. World Electric Vehicle Journal, 12(2), 88. https://doi.org/10.3390/wevj12020088