Modeling Risk Exposure: Fuzzy and Fuzzy Intuitionistic Approaches to Pedestrian and Vehicle Interaction
DOI:
https://doi.org/10.47839/ijc.24.1.3887Keywords:
intuitionistic fuzzy number, accident risk, risk exposure indicator, pedestrian-vehicle interaction, simulationAbstract
Road safety is a major concern that raises significant worries, especially regarding accidents involving pedestrians. Often, the study of interaction between pedestrians and vehicles focuses on various measurable factors such as vehicle speed and pedestrian crossing speed, often overlooking human behaviors that have a significant impact on this interaction. In this regard, studying road risks poses a challenge that requires a systematic approach to successful overcoming. In this article, we compare both fuzzy and intuitionistic approaches to assess pedestrians' exposure to accident risks. These two approaches take uncertainty into account in a more natural way than classical methods based on precise values. Being more adept at handling uncertainty than classical methods, these approaches provide a finer understanding of reality, thus enabling the development of more tailored safety measures to protect pedestrians. Comparative analysis of the results highlights a significant improvement in the accuracy of risk assessments, underscoring the effectiveness of these approaches in the context of road safety.
References
L. Govinda, M. R. SaiKiranRaju, K. V. R. Ravi Shankar, “Pedestrian-vehicle interaction severity level assessment at uncontrolled intersections using machine learning algorithms,” Safety Science, vol. 153, pp. 1-9, 2022. https://doi.org/10.1016/j.ssci.2022.105806.
X. Shen and P. Raksincharoensak, “Pedestrian-aware statistical risk assessment,” IEEE Transactions on Intelligent Transportation Systems, vol. 23, no. 7, pp. 7910-7918, 2022. https://doi.org/10.1109/TITS.2021.3074522.
R. Wu, X. Zheng, Y. Xu, W. Wu, G. Li, Q. Xu, Z. Nie, “Modified driving safety field based on trajectory prediction model for pedestrian–vehicle collision,” Sustainability, vol. 11, 6254, 2019. https://doi.org/10.3390/su11226254.
R. E. Amini, K. Yang, C. Antoniou, “Development of a conflict risk evaluation model to assess pedestrian safety in interaction with vehicles,” Accident Analysis & Prevention, vol 175, pp 1-16, 2022. https://doi.org/10.1016/j.aap.2022.106773.
L A. Zadeh, “Fuzzy sets,” Inform Control, vol. 8, issue 3, pp. 338-353, 2014. https://doi.org/10.1016/S0019-9958(65)90241-X.
K. T. Atanassov, “Intuitionistic fuzzy sets,” in Intuitionistic Fuzzy Sets. Studies in Fuzziness and Soft Computing, vol. 35, pp. 1-137, 1999. https://doi.org/10.1007/978-3-7908-1870-3_1.
M. Mandar, L. Karim, A. Boulmakoul, & A. Lbath, “Triangular intuitionistic fuzzy number theory for driver-pedestrians interactions and risk exposure modeling,” Procedia Computer Science, vol. 109, pp. 148-155, 2017. https://doi.org/10.1016/j.procs.2017.05.309.
M. A. Shafia and S. Abdollahzadeh, “Integrating fuzzy kano and fuzzy TOPSIS for classification of functional requirements in national standardization system,” Arabian Journal for Science and Engineering, vol. 39, no. 8, pp. 6555–6565, 2014. https://doi.org/10.1007/s13369-014-1251-z.
A. K. Mukherjee, K. H. Gazi, S. Salahshour, A. Ghosh, S. P. Mondal, “A brief analysis and interpretation on arithmetic operations of fuzzy numbers,” Results in Control and Optimization, vol. 13, 100312, 2023. https://doi.org/10.1016/j.rico.2023.100312.
P. G. Gipps, B. Marksjo, “A micro-simulation model for pedestrian flows,” Math Comput Simul, vol. 27, pp. 95-105, 1985. https://doi.org/10.1016/0378-4754(85)90027-8.
M. Pachter, P. R. Chandler, “Challenges of autonomous control,” IEEE Cont Syst Mag, vol. 18, pp. 92-7, 1998. https://doi.org/10.1109/37.710883.
A. Boulmakoul, M. Mandar, “Fuzzy ant colony paradigm for virtual pedestrian simulation,” The Open Operational Research Journal, vol. 7, pp. 19-29, 2011. https://doi.org/10.2174/1874243201105010019.
M. Dorigo, M. Birattari and T. Stutzle, “Ant colony optimization,” IEEE Computational Intelligence Magazine, vol. 1, no. 4, pp. 28-39, 2006. https://doi.org/10.1109/MCI.2006.329691.
K. Nagel, M. Schreckenberg, “A cellular automaton model for freeway traffic,” Journal de Physique I, vol. 2, issue 12, pp. 2221-2229, 1992. https://doi.org/10.1051/jp1:1992277.
M. Mandar, A. Boulmakoul, “Virtual pedestrians’ risk modeling,” International Journal of Civil Engineering and Technology, vol. 5, issue 10, pp. 32-42, 2014.
W. H. K. Lam, J. Y. S. Lee, K. S. Chan, P. K. Goh, “A generalized function for modeling bi-directional flow effects on indoor walkways in Hong Kong,” Transp Res, vol. 37, pp. 789-810, 2003. https://doi.org/10.1016/S0965-8564(03)00058-2.
G. Ren, C. Gu, L. Lu, Z. Zhou, C. Ding, “Modeling risk degree of conflicts between crossing pedestrians and vehicles at signalized intersections,” J. Transp. Syst. Eng. Info. Technol, vol. 12, issue 5, pp. 76–81, 2012. https://doi.org/10.1016/S1570-6672(11)60224-9.
X. Sun, K. Lin, Y. Wang, S. Ma, H. Lu, “A study on pedestrian – Vehicle conflict at unsignalized crosswalks based on game theory,” Sustainability, vol. 14, 7652, 2022. https://doi.org/10.3390/su14137652.
L. Lu, et al., “A cellular automaton simulation model for pedestrian and vehicle interaction behaviors at unsignalized mid-block crosswalks,” Accid. Anal. Prev, vol. 95, part B, pp. 425-437, 2016. https://doi.org/10.1016/j.aap.2016.04.014.
P. Chen, C. Wu, S. Zhu, “Interaction between vehicles and pedestrians at uncontrolled mid-block crosswalks,” Safety Science, vol. 82, pp. 68-76, 2016. https://doi.org/10.1016/j.ssci.2015.09.016.
J. D. Fricker, & Y. Zhang, “Modeling pedestrian and motorist interaction at semi-controlled crosswalks: The effects of a change from one-way to two-way street operation,” Transportation Research Record, vol. 2673, pp. 2-10, 2019. http.s://doi.org/10.1177/0361198119850142
L. Yue, M. A. Abdel-Aty, Y. Wu and J. Yuan, “An augmentation function for active pedestrian safety system based on crash risk evaluation,” IEEE Transactions on Vehicular Technology, vol. 69, no. 11, pp. 12459-12469, 2020. https://doi.org/10.1109/TVT.2020.3017131.
W. Zeng, H. Li, “Note on some operations on intuitionistic fuzzy sets,” Fuzzy Set, and Systems, vol. 157, pp. 990- 991, 2016. https://doi.org/10.1016/j.fss.2005.08.007.
J. Zhang, H. Wang, P. Li, “Cellular automata modeling of pedestrians crossing dynamics,” Journal of Zhejiang University - SCIENCE A, vol. 7, pp. 835-40, 2004. https://doi.org/10.1631/jzus.2004.0835.
B. J. Crowley-Koch, R. Van Houten, and E. Lim, “Effects of pedestrian prompts on motorist yielding at crosswalks,” Journal of Applied Behavior Analysis, vol. 44, no. 1, pp. 121–126, 2011. https://doi.org/10.1901/jaba.2011.44-121.
X. Liang, C. Wei, “An Atanassov’s intuitionistic fuzzy multi-attribute group decision making method based on entropy and similarity measure,” International Journal of Machine Learning and Cybernetics, vol. 5, issue 3, pp. 435-444, 2014. https://doi.org/10.1007/s13042-013-0178-0.
B. R. Kadali, N. Rathi, and V. Perumal, “Evaluation of pedestrian mid-block road crossing behaviour using artificial neural network,” Journal of Traffic and Transportation Engineering (English Edition), vol. 1, pp. 111–119, 2014. https://doi.org/10.1016/S2095-7564(15)30095-7.
U. Brude, and J. Larsson, “Models for predicting accidents at junctions where pedestrians and cyclists are involved. How well do they fit?” Accident Analysis & Prevention, vol. 25, pp. 499–509, 1993. https://doi.org/10.1016/0001-4575(93)90001-D.
S. Okazaki, “A study of pedestrian movement in architectural space. Part 1: pedestrian movement by the application of magnetic models, “Trans AIJ, vol. 283, pp. 9-111, 1979. https://doi.org/10.3130/aijsaxx.283.0_111.
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