Synergistic Influence of Rainstorm and Waterlogging on Drivers’ Driving Behavior—An Experimental Study Based on High-Fidelity Driving Simulator
Abstract
:1. Introduction
- Heavy rainstorms, whose impact on traffic flow is undoubtedly much more prominent than normal rainfall or rainfall with intensity below normal, are rarely examined in the relevant research mentioned above. The main reason is that most relevant research is extremely dependent on real traffic data and meteorological data, while rainstorms and heavy rainstorms seldom happen in daily life;
- Besides rainfall and waterlogging, drivers’ driving behavior is associated with a variety of other factors, both external and internal. External factors consist mainly of road properties, traffic flow patterns, and other weather conditions, such as whether thunder and lightning are present. Internal factors consist mainly of drivers’ ages, genders, health levels, degrees of fatigue/drowsiness, reaction capability, disposition, mood, etc. It is hard to keep all of these potential factors uniform in different studies, causing a significant problem because the quantitative results from separate studies conducted in different blocks, cities, or countries (even under a similar weather conditions) may vary greatly, despite the qualitative results from different studies being very close.
2. Experiment
2.1. Hardware and Software
2.2. Subjects
2.3. Circumstance Design in the Experiment
2.4. Output Data from the Experiment
3. Methods of Data Processing
3.1. Two-Way ANOVA
3.2. Narrowly Defined Statistical Analysis
4. Results
4.1. Effects of Rainstorms and Waterlogging on Vehicles’ Speed
4.2. Effect of Rainstorm and Waterlogging on Vehicles’ Acceleration
4.3. Effect of Rainstorm and Waterlogging on Vehicles’ Deceleration
4.4. Effects of Rainstorm and Waterlogging on Vehicles’ Headway Distance
5. Validation
6. Limitations
7. Conclusions
- Both rainfall and waterlogging have significant weakening effects on drivers’ driving speed and acceleration, indicating that the drivers tend to adopt more conservative driving and acceleration strategies when encountering stronger rainfall and more severe waterlogging;
- The influence of rainfall on drivers’ deceleration performance is relatively complex and the absolute value of drivers’ deceleration first increases and then decreases with increased rainfall intensity. In contrast, the absolute value of drivers’ deceleration always decreases with increased water depth;
- The influence of water depth on the vehicles’ headway distance when drivers are in the car-following state is much more significant than the influence of rainfall intensity on vehicles’ headway distance, indicating that waterlogging may be the main factor affecting traffic flow in daily urban road traffic if considering that car-following is the principal state in urban road traffic.
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
- Chen, Y.; Zhou, H.; Zhang, H.; Du, G.; Zhou, J. Urban flood risk warning under rapid urbanization. Environ. Res. 2015, 139, 3–10. [Google Scholar] [CrossRef] [PubMed]
- Cheng, M.; Qin, H.; Fu, G.; He, K. Performance evaluation of time-sharing utilization of multi-function sponge space to reduce waterlogging in a highly urbanizing area. J. Environ. Manag. 2020, 269, 110760. [Google Scholar] [CrossRef] [PubMed]
- Meng, X.; Zhang, M.; Wen, J.; Du, S.; Xu, H.; Wang, L.; Yang, Y. A simple GIS-based model for urban rainstorm inundation simulation. Sustainability 2019, 11, 2830. [Google Scholar] [CrossRef] [Green Version]
- Liu, H.; Jia, Y.; Niu, C. “Sponge city” concept helps solve China’s urban water problems. Environ. Earth Sci. 2017, 76, 473. [Google Scholar] [CrossRef]
- Mitra, S. Sun glare and road safety: An empirical investigation of intersection crashes. Saf. Sci. 2014, 70, 246–254. [Google Scholar] [CrossRef]
- Ni, X.; Huang, H.; Chen, A.; Liu, Y.; Xing, H. Effect of heavy rainstorm and rain-induced waterlogging on traffic flow on urban road sections: Integrated experiment and simulation study. J. Transp. Eng. Part A Syst. 2021, 147, 10. [Google Scholar] [CrossRef]
- Do, M.; Kim, M.; Oh, J. Effects of Weather Conditions on Free-Flow Speeds. Proceedings of the 5th Conference of the Eastern Asia Society for Transportation Studies. 2003, pp. 1390–1403. Available online: http://www.easts.info/2003proceedings/papers/1390.pdf#[0,{%22name%22:%22FitH%22},845 (accessed on 26 May 2022).
- Dhaliwal, S.S.; Wu, X.; Thai, J.; Jia, X. Effects of rain on freeway traffic in southern California. Transp. Res. Rec. J. Transp. Res. Board 2017, 2616, 69–80. [Google Scholar] [CrossRef] [Green Version]
- Feng, H.; Li, C.; Zhao, N.; Hu, H. Modeling the impacts of related factors on traffic operation. Procedia Eng. 2011, 12, 99–104. [Google Scholar] [CrossRef] [Green Version]
- Hassan, S.A.; Wong, L.; Mashros, N.; Mohammed Alhassan, H.; Abdul Sukor, N.S.; Rohani, M.; Minhans, A. Operating speed of vehicles during rainfall at night: Case study in Pontian, Johor. J. Teknol. 2016, 78, 9–18. [Google Scholar] [CrossRef] [Green Version]
- Kurte, K.; Ravulaparthy, S.; Berres, A.; Allen, M.; Sanyal, J. Regional-scale spatio-temporal analysis of impacts of weather on traffic speed in Chicago using probe data. Procedia Comput. Sci. 2019, 155, 551–558. [Google Scholar] [CrossRef]
- Mirbaha, B.; Saffarzadeh, M.; Beheshty, S.A.; Aniran, M.; Yazdani, M.; Shirini, B. Predicting average vehicle speed in two lane highways considering weather condition and traffic characteristics. In World Multidisciplinary Civil Engineering-Architecture-Urban Planning Symposium (WMCAUS); IOP: Bristol, UK, 2017. [Google Scholar] [CrossRef] [Green Version]
- Mukhlas, N.A.; Mashros, N.; Che Puan, O.; Hassan, S.A.; Abdul Hassan, N.; Abdullah, R.A.; Rahman, R. Effect of rainfall on traffic flow characteristics during night Time. J. Teknol. 2016, 78, 1–7. [Google Scholar] [CrossRef] [Green Version]
- Wang, Y.; Luo, J. Study of rainfall impacts on freeway traffic flow characteristics. Transp. Res. Procedia 2017, 25, 1533–1543. [Google Scholar] [CrossRef]
- Zhang, W.; Li, R.; Shang, P.; Liu, H. Impact analysis of rainfall on traffic flow characteristics in Beijing. Int. J. Intell. Transp. Syst. Res. 2018, 17, 150–160. [Google Scholar] [CrossRef]
- Li, J.; Lam, W.H.K.; Li, X. Modeling the effects of rainfall intensity on the heteroscedastic traffic speed dispersion on urban roads. J. Transp. Eng. 2016, 142, 05016002. [Google Scholar] [CrossRef]
- Hu, S.; Lin, H.; Xie, K.; Dai, J.; Qui, J. Impacts of rain and waterlogging on traffic speed and volume on urban roads. In Proceedings of the 21st International Conference on Intelligent Transportation Systems (ITSC), Maui, HI, USA, 4–7 November 2018; pp. 2943–2948. [Google Scholar]
- Ji, X.; Shao, C. Modeling and analyzing free-flow speed of environment traffic flow in rainstorm based on geomagnetic detector data. Ekoloji 2019, 28, 4223–4230. [Google Scholar]
- Jia, Y.; Wu, J.; Du, Y. Modeling and simulation of rainfall impacts on urban traffic flow: A case study in Beijing. In Proceedings of the Theory, Methodology, Tools and Applications for Modeling and Simulation of Complex Systems, Beijing, China, 8–11 October 2016; pp. 475–484. [Google Scholar] [CrossRef]
- Liu, X.; Wu, B.; Zhao, Y.; Zheng, L. Analysis of speed characteristics of urban expressways under rainy conditions. In Proceedings of the2017 IEEE 20th International Conference on Intelligent Transportation Systems (ITSC), Yokohama, Japan, 16–19 October 2017. [Google Scholar] [CrossRef]
- Hussain, E.; Ahmed, S.I.; Ali, M.S. Modeling the effects of rainfall on vehicular traffic. J. Mod. Transp. 2018, 26, 133–146. [Google Scholar] [CrossRef] [Green Version]
- Chen, C.; Zhao, X.; Liu, H.; Ren, G.; Zhang, Y.; Liu, X. Assessing the influence of adverse weather on traffic flow characteristics using a driving simulator and VISSIM. Sustainability 2019, 11, 830. [Google Scholar] [CrossRef] [Green Version]
- Zhao, X.; Ren, G.; Chen, C.; Rong, J.; Chang, X. Comprehensive effects of adverse weather on driver’s car-following behavior based on driving simulation technology. J. Chongqing Jiaotong Univ. (Nat. Sci.) 2019, 38, 90–95. (In Chinese) [Google Scholar] [CrossRef]
- China Meteorological Service Association. Precipitation Grade of Approaching Short-Term Rainfall in the Aspect of Meteorological Service. Available online: http://www.chinamsa.org/57850-718.html (accessed on 26 May 2022). (In Chineses).
- Shariff, M.; Che Puan, O.; Mashros, N. Review of traffic data collection methods for drivers’ car—following behaviour under various weather conditions. J. Teknol. 2016, 78, 37–47. [Google Scholar] [CrossRef] [Green Version]
- National Research Council (U.S.). Highway Capacity Manual: Metric Units; Transportation Research Board: Washington, DC, USA, 2000; pp. 22–29. [Google Scholar]
- Smith, B.L.; Byrne, K.G.; Copperman, R.B.; Hennessy, S.M.; Goodall, N.J. An investigation into the impact of rainfall on freeway traffic flow. In Proceedings of the 83rd Annual Meeting of The Transportation Research Board, Washington, DC, USA, 11–15 January 2004. [Google Scholar] [CrossRef]
- Okamoto, N.; Ishida, H.; Furuya, H.; Furukawa, K. Including weather condition factors in the analysis of the highway capacity. In Proceedings of the 83rd Annual Meeting of the Transportation Research Board, Washington, DC, USA, 11–15 January 2004. [Google Scholar]
- Rakha, H.; Farzaneh, M.; Arafeh, M.; Sterzin, E. Inclement weather impacts on freeway traffic stream behavior. Transp. Res. Rec. J. Transp. Res. Board 2008, 2071, 8–18. [Google Scholar] [CrossRef]
- Wang, X. Study on traffic flow characteristics of urban expressway under rainstorm. In Transportation Planning and Management; Beijing Jiaotong University: Beijing, China, 2015. (In Chinese) [Google Scholar]
- Sun, H.; Yang, J.; Wu, B. Empirical analysis of the influence of rainstorm on the speed density relationship on expressway. J. Transp. Syst. Eng. Inf. Technol. 2016, 16, 221–227. (In Chinese) [Google Scholar]
Source of the Variation | SD | DOF | MSE | Statistics | Sig. | |
---|---|---|---|---|---|---|
Sum |
Source of the Variation | SD | DOF | MSE | Statistics | Sig. |
---|---|---|---|---|---|
11.349 | 4 | 2.837 | 176.437 | 0.000 * | |
10.398 | 5 | 2.080 | 129.322 | 0.000 * | |
4.996 | 20 | 0.250 | 15.533 | 0.000 * | |
22.192 | 1380 | 0.016 | |||
Sum | 48.935 | 1409 |
Source of the Variation | SD | DOF | MSE | Statistics | Sig. |
---|---|---|---|---|---|
176.253 | 4 | 44.063 | 118.331 | 0.000 * | |
56.541 | 5 | 11.308 | 30.368 | 0.000 * | |
28.359 | 20 | 1.418 | 3.808 | 0.000 * | |
513.874 | 1380 | 0.372 | |||
Sum | 775.027 | 1409 |
Source of the Variation | SD | DOF | MSE | Statistics | Sig. |
---|---|---|---|---|---|
76,107.5 | 4 | 19,026.9 | 109.7 | 0.000 * | |
3240.3 | 5 | 648.1 | 3.7 | 0.002 * | |
877.4 | 20 | 43.9 | 0.3 | 1.000 | |
239,324.3 | 1380 | 173.4 | |||
Sum | 240,201.8 | 1400 | 171.6 |
Author, Pub-Year | Description of Rainfall Intensity | Numerical Value of Rainfall Intensity | Indicator | Rates of Change |
---|---|---|---|---|
HCM ((U.S.), 2000) [26] | Heavy rain | Not mentioned | Capacity | [−15%, −14%] |
Smith et al., 2004 [27] | Heavy rain | >6.35 mm/h | Capacity | [−30%, −25%] |
Okamoto et al., 2004 [28] | [heavy rain, rainstorm] | [4.9, 9.6] mm/h | Capacity | −33% |
Rakha et al., 2008 [29] | [no rain, rainstorm] | 0–17 mm/h | Capacity | [−10%, 11%] |
Wang, 2015 [30] | Rainstorm | 30–70 mm/12 h or 50–100 mm/24 h | Capacity | [−19.5%, −5.7%] |
Jam density | [0%, +27.6%] | |||
Sun et al., 2016 [31] | Heavy rainstorm | 106.2–175.5 mm/24 h | Capacity | [−15.2%, −10.8%] |
This study | [heavy rain, heavy rainstorm] | [6.8, 34.0] mm/h | Capacity | [−35.7%, +9.1%] |
Jam density | [+11.0%, +25.5%] |
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. |
© 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Share and Cite
Ni, X.; Huang, H.; Li, R.; Chen, A.; Liu, Y.; Xing, H.; Liu, K.; Wang, M. Synergistic Influence of Rainstorm and Waterlogging on Drivers’ Driving Behavior—An Experimental Study Based on High-Fidelity Driving Simulator. Sustainability 2022, 14, 8517. https://doi.org/10.3390/su14148517
Ni X, Huang H, Li R, Chen A, Liu Y, Xing H, Liu K, Wang M. Synergistic Influence of Rainstorm and Waterlogging on Drivers’ Driving Behavior—An Experimental Study Based on High-Fidelity Driving Simulator. Sustainability. 2022; 14(14):8517. https://doi.org/10.3390/su14148517
Chicago/Turabian StyleNi, Xiaoyong, Hong Huang, Ruiqi Li, Anying Chen, Yi Liu, Han Xing, Kai Liu, and Ming Wang. 2022. "Synergistic Influence of Rainstorm and Waterlogging on Drivers’ Driving Behavior—An Experimental Study Based on High-Fidelity Driving Simulator" Sustainability 14, no. 14: 8517. https://doi.org/10.3390/su14148517