- ISSN 0258-2724
- CN 51-1277/U
- EI Compendex
- Scopus
- Indexed by Core Journals of China, Chinese S&T Journal Citation Reports
- Chinese S&T Journal Citation Reports
- Chinese Science Citation Database
| Citation: | HE Jie, YE Yuntao, XU Yang, ZHANG Changjian, QIN Pengcheng. Research on the Method for Freeway Driver Stress Detection Based on Multimodal Parameters[J]. Journal of Southwest Jiaotong University. doi: 10.3969/j.issn.0258-2724.20230327
|
To enable real-time driver stress detection without relying on physiological signals, this study proposes a method based on road alignment parameters, video images, and six-component tire forces. The proposed method utilizes computer vision model Deeplabv3 to extract semantic information of scene elements from driving videos for characterizing the driving environment. The scene element parameters are incorporated with vehicle dynamics parameters and roadway alignment parameters to construct a multimodal parameter feature set. Subsequently, machine learning algorithm is used to achieve driver stress detection. To verify the effectiveness of the proposed method, a field driving experiment was conducted on Jinliwen freeway for collecting driver eye-movement, heart rate data, vehicle dynamics parameters, roadway alignment parameters, and driving video. The eye-movement and heart rate data were utilized to measure stress levels. The random forest, support vector machine, XGBoost, and LightGBM algorithms were applied to build stress detection model, and SHAP was adopted to conduct analysis of influencing factors. The results showed that the LightGBM has best performance, with macro average and weighted average
| [1] |
中华人民共和国国家统计局. 中国统计年鉴[M]. 北京:中国统计出版社,2024.
|
| [2] |
KHATTAK A J, AHMAD N, WALI B, et al. A taxonomy of driving errors and violations: Evidence from the naturalistic driving study[J]. Accident Analysis & Prevention, 2021, 151: 105873.1-105873.20
|
| [3] |
WANG J J, XU W, GONG Y H. Real-time driving danger-level prediction[J]. Engineering Applications of Artificial Intelligence, 2010, 23(8): 1247-1254. doi: 10.1016/j.engappai.2010.01.001
|
| [4] |
USECHE S A, ORTIZ V G, CENDALES B E. Stress-related psychosocial factors at work, fatigue, and risky driving behavior in bus rapid transport (BRT) drivers[J]. Accident Analysis & Prevention, 2017, 104: 106-114.
|
| [5] |
HEALEY J A, PICARD R W. Detecting stress during real-world driving tasks using physiological sensors[J]. IEEE Transactions on Intelligent Transportation Systems, 2005, 6(2): 156-166. doi: 10.1109/TITS.2005.848368
|
| [6] |
胡月琦. 高速公路隧道路段驾驶人心智游移及心理负荷与安全风险研究[D]. 西安:长安大学,2021.
|
| [7] |
AGRAWAL S, PEETA S. Evaluating the impacts of situational awareness and mental stress on takeover performance under conditional automation[J]. Transportation Research Part F: Traffic Psychology and Behaviour, 2021, 83: 210-225. doi: 10.1016/j.trf.2021.10.002
|
| [8] |
HUANG J, LIU Y, PENG X Y. Recognition of driver’s mental workload based on physiological signals, a comparative study[J]. Biomedical Signal Processing and Control, 2022, 71: 103094.1-103094.9
|
| [9] |
URBANO M, ALAM M, FERREIRA J, et al. Cooperative driver stress sensing integration with eCall system for improved road safety[C]//IEEE EUROCON 2017 -17th International Conference on Smart Technologies. Ohrid: IEEE, 2017: 883-888.
|
| [10] |
黄晶,杨梦婷. 考虑初始情绪的个性化驾驶负荷状态评价[J]. 中国公路学报,2021,34(1): 167-176.
HUANG Jing, YANG Mengting. Initial emotion-based evaluation of the personalized driving load state[J]. China Journal of Highway and Transport, 2021, 34(1): 167-176.
|
| [11] |
TAVAKOLI A, HEYDARIAN A. Multimodal driver state modeling through unsupervised learning[J]. Accident Analysis & Prevention, 2022, 170: 106640.1-106640.17
|
| [12] |
CHEN L L, ZHAO Y, YE P F, et al. Detecting driving stress in physiological signals based on multimodal feature analysis and kernel classifiers[J]. Expert Systems with Applications, 2017, 85: 279-291. doi: 10.1016/j.eswa.2017.01.040
|
| [13] |
LEHTONEN E, LAPPI O, SUMMALA H. Anticipatory eye movements when approaching a curve on a rural road depend on working memory load[J]. Transportation Research Part F: Traffic Psychology and Behaviour, 2012, 15(3): 369-377. doi: 10.1016/j.trf.2011.08.007
|
| [14] |
LAZARO M J, YUN M H, KIM S. Stress-level and attentional functions of experienced and novice young adult drivers in intersection-related hazard situations[J]. International Journal of Industrial Ergonomics, 2022, 90: 103315.1-103315.9. doi: 10.1016/j.ergon.2022.103315
|
| [15] |
赵亮. 农村公路复杂条件下驾驶人典型生理心理指标变化规律及驾驶行为研究[D]. 西安:长安大学,2018.
|
| [16] |
RASTGOO M N, NAKISA B, MAIRE F, et al. Automatic driver stress level classification using multimodal deep learning[J]. Expert Systems with Applications, 2019, 138: 112793.1-112793.11
|
| [17] |
MOU L T, ZHOU C, ZHAO P F, et al. Driver stress detection via multimodal fusion using attention-based CNN-LSTM[J]. Expert Systems with Applications, 2021, 173: 114693.1-114693.11
|
| [18] |
符锌砂,葛洪成,鲁岳. 基于LightGBM的高速公路隧道段驾驶人压力负荷评估[J]. 交通运输研究,2022,8(5): 46-55.
FU Xinsha, GE Hongcheng, LU Yue. Driver stress load assessment of freeway tunnel sections based on LightGBM[J]. Transport Research, 2022, 8(5): 46-55.
|
| [19] |
LANATA A, VALENZA G, GRECO A, et al. How the autonomic nervous system and driving style change with incremental stressing conditions during simulated driving[J]. IEEE Transactions on Intelligent Transportation Systems, 16(3): 1505-1517.
|
| [20] |
ELAMRANI ABOU ELASSAD Z, MOUSANNIF H, AL MOATASSIME H. A real-time crash prediction fusion framework: an imbalance-aware strategy for collision avoidance systems[J]. Transportation Research Part C: Emerging Technologies, 2020, 118: 102708.1-102708.24
|
| [21] |
DI STASI L L, RENNER R, Catena A, et al. Towards a driver fatigue test based on the saccadic main sequence: a partial validation by subjective report data[J]. Transportation Research Part C: Emerging Technologies, 2012, 21(1): 122-133. doi: 10.1016/j.trc.2011.07.002
|
| [22] |
ESKANDARIAN A, MORTAZAVI A. Evaluation of a smart algorithm for commercial vehicle driver drowsiness detection[C]//2007 IEEE Intelligent Vehicles Symposium. Istanbul, Turkey. IEEE, 2007: 553-559.
|
| [23] |
ZHANG C J, HE J, YAN X T, et al. Exploring relationships between microscopic kinetic parameters of tires under normal driving conditions, road characteristics and accident types[J]. Journal of Safety Research, 2021, 78: 80-95. doi: 10.1016/j.jsr.2021.05.010
|
| [24] |
SANG F, LUO R, CHEN Y, et al. Factor analysis evaluation of asphalt pavement performance considering structural strength and hidden cracks[J]. Construction and Building Materials, 2023, 408: 133651.1-133651.12
|
| [25] |
WOOD J M. Vision impairment and on-road driving[J]. Annu Rev Vis Sci, 2022, 8: 195-216. doi: 10.1146/annurev-vision-100820-085030
|
| [26] |
KIM B, YIM J, KIM J. Highway driving dataset for semantic video segmentation[C]. British Machine Vision Conference. Newcastle: British Machine Vision Association, 2018: 52286240.1-52286240.12
|
| [27] |
LUNDBERG S M, LEE S I. A unified approach to interpreting model predictions[C]. 31st Conference on Neural Information Processing Systems. California: Curran Associates Inc, 2017: 4768–4777.
|
| [28] |
SACHS H K. On the influence of weight reduction and weight distribution on vehicle handling, ride and performance[J]. Vehicle System Dynamics, 1974, 3(3): 163-191. doi: 10.1080/00423117408968454
|
| [29] |
许金良,王荣华,冯志慧,等. 基于动视觉特性的高速公路景观敏感区划分[J]. 交通运输工程学报,2015,15(2): 1-9.
XU Jinliang, WANG Ronghua, FENG Zhihui, et al. Classification of expressway landscape sensitive zone based on dynamic visual characteristics[J]. Journal of Traffic and Transportation Engineering, 2015, 15(2): 1-9.
|
| [30] |
牛世峰,董景钊,常东风,等. 考虑空间稳定性的公路单车事故严重程度影响因素分析[J/OL]. 西南交通大学学报,1-15[2025-04-23]. http://kns. cnki. net/kcms/detail/51.1277. U. 20250324.1433. 002. html. NIU Shifeng,DONG Jingzhao,CHANG Dongfeng,et al. Analysis of factors influencing the severity of road single-vehicle accidents considering spatial stability[J/OL]. Journal of Southwest Jiaotong University,1-15 [2025-04-23]. http://kns.cnki.net/kcms/detail/51.1277.U.20250324.1433.002.html.
|
| [31] |
孔德文. 大型车辆对多车道高速公路交通运行影响研究[D]. 南京:东南大学,2018.
|
| [32] |
徐婷,邓恺龙,刘永涛,等. 基于航测数据的不同风格换道轨迹规划[J]. 西南交通大学学报,2024,59(3): 720-728.
XU Ting, DENG Kailong, LIU Yongtao, et al. Different styles of lane changing trajectory planning based on aerial survey data[J]. Journal of Southwest Jiaotong University, 2024, 59(3): 720-728.
|
| [1] | FAN Xinnan, WANG Jie, SHI Pengfei, LI Min. Pavement Crack Segmentation Algorithm Based on Pulse Coupled Neural Network with Brainstorming Optimization[J]. Journal of Southwest Jiaotong University, 2021, 56(3): 572-578. doi: 10.3969/j.issn.0258-2724.20190354 |
| [2] | SHI Chunlin, YANG Peizhang, ZHANG Chao, DU Lan, YE Kai, FAN Chengxiao, LI Jian, ZU Anran. Segmentation of Small-Field-of-Viewstar Images Based on Kittler Minimum Error Algorithm[J]. Journal of Southwest Jiaotong University, 2021, 56(1): 168-175. doi: 10.3969/j.issn.0258-2724.20190841 |
| [3] | XIANG Yu, CONG Deming, ZHANG Yang, YUAN Fei. Two-Stream Neural Network Fusion Model for Highway Fog Detection[J]. Journal of Southwest Jiaotong University, 2019, 54(1): 173-179. doi: 10.3969/j.issn.0258-2724.20180205 |
| [4] | ZHANG Changli, MENG Ying, LI Pengchao, SUN Ting. Monitoring Video-Based Visibility Detection Method and System for Highways in China[J]. Journal of Southwest Jiaotong University, 2018, 53(1): 136-145. doi: 10.3969/j.issn.0258-2724.2018.01.017 |
| [5] | YONG J. Yuan, HUANG Xiaoxia, TANG Yuantian. Real-time Detection of Defects in Train Bearings Based on Analysis of Signal Characteristics in Time-Frequency Domains[J]. Journal of Southwest Jiaotong University, 2017, 30(6): 1182-1187. doi: 10.3969/j.issn.0258-2724.2017.06.019 |
| [6] | ZHAI Donghai, CUI Jingjing, NIE Hongyu, DU Jia. Topic Link Detection Method Based on Semantic Similarity[J]. Journal of Southwest Jiaotong University, 2015, 28(3): 517-522. doi: 10.3969/j.issn.0258-2724.2015.03.021 |
| [7] | WANG Lidong, ZHANG Yin, LÜ, Mingqi. Document Semantic Compression Algorithm Based on Phrase Topic Model[J]. Journal of Southwest Jiaotong University, 2015, 28(4): 755-763. doi: 10.3969/j.issn.0258-2724.2015.04.027 |
| [8] | ZHU Tong, WU Ling, LU Qiaozhen. Effects of In-vehicle Information on Driver Eye Blink Duration and Workload[J]. Journal of Southwest Jiaotong University, 2015, 28(3): 504-510. doi: 10.3969/j.issn.0258-2724.2015.03.019 |
| [9] | YANG Qingfang, MA Minghui, LIANG Shidong, LI Zhilin. Stair-Like Control Strategies of Variable Speed Limit for Bottleneck Regions on Freeway[J]. Journal of Southwest Jiaotong University, 2015, 28(2): 354-360. doi: 10.3969/j.issn.0258-2724.2015.02.023 |
| [10] | TANG Zhihui, CHENG Jie, FANG Zhengnan. Causal Mechanism of Difference between Experienced and Novice Drivers in Hazard Perception Based on Fuzzy Signal Detection Theory[J]. Journal of Southwest Jiaotong University, 2013, 26(3): 532-538. doi: 10.3969/j.issn.0258-2724.2013.03.022 |
| [11] | XIE Feng, MA Zhimin, LUAN Weidong. Quality Evaluation of Expressway Pavement Based on Fuzzy Neural Networks[J]. Journal of Southwest Jiaotong University, 2013, 26(1): 160-164. doi: 10.3969/j.issn.0258-2724.2013.01.025 |
| [12] | CHENG Guozhu, XUE Changlong, HAN Juan. Changing Rule of Driver's Recognition Distance in Daytime and Nighttime on Freeway[J]. Journal of Southwest Jiaotong University, 2012, 25(6): 996-1002. doi: 10.3969/j.issn.0258-2724.2012.06.014 |
| [13] | DAI Xiaowen, CAI Zhiping, ZHONG Guiying. Video Shot Detection Method Based on Wavelet Transform and Wavelet Entropy[J]. Journal of Southwest Jiaotong University, 2008, 21(3): 314-318. |
| [14] | ZHANG Zutao, ZHANG Jiashu. Driver Fatigue Detection Based on Unscented Kalman Filter and Eye Tracking[J]. Journal of Southwest Jiaotong University, 2008, 21(6): 697-702. |
| [15] | CHENG Guozhu, PEI Yulong. Maximum Speed Limit on Freeway with Damaged Pavement[J]. Journal of Southwest Jiaotong University, 2008, 21(6): 714-717. |
| [16] | WANG Jian-ying, DENG Ya-bo, YIN Zhong-ke, CHEN Lei. Improved Beamforming Algorithm Based on Subspace Tracking[J]. Journal of Southwest Jiaotong University, 2004, 17(3): 314-317. |
| [17] | WANGJin-tao, LIUWen-yao, LUShuo. Application of Watershed Algorithm to Cell Image Segmentation[J]. Journal of Southwest Jiaotong University, 2002, 15(3): 290-294. |
| [18] | LONCYong, JiangGe-fu, FengYun-cai. nExPloratoryStudyonMeasuresto FormulateFreeway，STollStandard[J]. Journal of Southwest Jiaotong University, 2001, 14(4): 421-424. |
| [19] | LINJian-hui, CHENJian-zheng, ZHANG Yu-ming. The Real-Time Measurement and Signal Analysis of the Curve Parameter in Tilting Train[J]. Journal of Southwest Jiaotong University, 2000, 13(6): 666-669. |
Figures(8) / Tables(7)
HE Jie, YE Yuntao, XU Yang, ZHANG Changjian, QIN Pengcheng. Research on the Method for Freeway Driver Stress Detection Based on Multimodal Parameters[J]. Journal of Southwest Jiaotong University. doi: 10.3969/j.issn.0258-2724.20230327
DownLoad:
