فصلنامه علمی کارافن

فصلنامه علمی کارافن

تدوین چرخه رانندگی در شهر سمنان با داده‌برداری به‌وسیله خودروی تعقیب‌گر و خوشه‌بندی با الگوریتم میانگین کی

نوع مقاله : مقاله پژوهشی (توسعه ای)

نویسندگان
دانشکده مهندسی مکانیک دانشگاه سمنان، سمنان، سمنان، ایران.
چکیده
چرخه رانندگی و ترافیک در شهر‌ها یکی از معضلات مهم و پیچیده در مدیریت شهری است. در فرایند داده‌برداری، خودروی داده‌بردار یک مسیر مشخص در شهر را در بازه زمانی انتخاب‌شده حرکت می‌کند و داده‌برداری با نرم‌افزار نصب‌شده بر تلفن همراه انجام می‌شود. در این تحقیق، به چرخه‌ رانندگی در شهر سمنان با استفاده از روش تعقیب‌گر و تکنیک خوشه‌بندی میانگین کی پرداخته شده است. مسافتی که در فرایند داده‌برداری طی شده است در هر مسیر حدود 12 کیلومتر بوده است. همچنین، مسافت کلی که در این تحقیق برای داده‌برداری طی شده است حدود 130 کیلومتر می‌باشد. اطلاعات مدل خودرو، سن و جنسیت رانندگان تعقیب‌شده به‌عنوان پارامتر تأثیرگذار ثبت شدند. سپس، با بهره‌گیری از تکنیک میانگین کی، داده‌های جمع‌آوری‌شده برای مسیرهای مختلف، به‌منظور استخراج الگوهای رفتاری در مسیرهای شهر سمنان تحلیل شد. همچنین در این تحقیق، تعداد دسته‌های مناسب برای خوشه‌بندی داده‌ها بررسی شد و با توجه به انحراف معیار داده‌ها نتیجه گرفته شد که تعداد بهینه دسته‌ها برابر با 5 دسته است. تعداد دسته‌های بیشتر علی‌رغم افزایش دقت محاسبات، زمان پردازش بیشتری را به دنبال دارد. بدین ترتیب، با انجام خوشه‌بندی با تعداد دسته‌های 2، 3، 4، 5 و 6، به‌ترتیب مشاهده شد که این تعداد دسته‌ها تقریباً 40، 80، 90، 98 و 99 درصد بهبود داشته است که نشان می‌دهد افزایش تعداد دسته‌ها بهبود قابل‌توجهی در نتایج را نشان دادند. این دسته‌ها شامل مسیر شهری، جاده‌ فرعی، بزرگراه، آزاد‌راه با ترافیک سبک و شروع- توقف می‌باشد. این اطلاعات می‌تواند به مسئولان شهری و مدیران ترافیک برای برنامه‌های بهبود ترافیکی و ایمنی، با توجه به الگوهای مشخص‌شده و مطالعات بعدی کمک کند و شناخت عمیق‌تری از رفتار رانندگی در شهر سمنان ارائه دهد. 
کلیدواژه‌ها
موضوعات

عنوان مقاله English

Designing a Driving Cycle in the City of Semnan with Data Collection Using Chasing Vehicles and Clustering with the K-means Algorithm

نویسندگان English

Mohammad Mohammad Zadeh
Ali Dadashi
Mohammad Azadi
Faculty of Mechanical Engineering, Semnan University, Semnan, Iran.
چکیده English

The driving and traffic cycle in cities is one of the most important and complex challenges in urban management. For the data collection process, the chasing vehicle moved in a certain route in the city through the selected time period, and data collection was conducted with software installed on a mobile phone. This research investigated the driving cycle in Semnan city using the chasing method and the K-means clustering technique. The distance covered during data collection was approximately 12 km for each route. Additionally, the total distance covered for the data collection in this study was approximately 130 km. The car model information, age, and gender of chased drivers were recorded as the influential parameters. Then, using the K-means technique, the data collected for different routes were analyzed to extract the behavioural patterns in the routes of Semnan city. Furthermore, in this study, the appropriate number of groups for data clustering was investigated, and considering the standard deviation of the data, it was concluded that the optimal number of clusters was 5. Increasing the number of clusters, despite improving the accuracy of calculations, led to longer processing times. Therefore, by clustering with 2, 3, 4, 5, and 6 groups, it was observed that these numbers of clusters improved by approximately 40, 80, 90, 98, and 99%, respectively, indicating that increasing the number of clusters showed a significant improvement in the results. These clusters included urban roads, secondary roads, highways, motorways with light traffic, and start-stop. This information can help city officials and traffic managers with traffic and safety improvement programs, according to the specified patterns, and provide a deeper understanding of driving behaviour in Semnan city.

کلیدواژه‌ها English

Driving Cycle Clustering K
Means Chasing Vehicle Semnan City
[1] Liu, T., Wang, B., & Yang, C. (2018). Online Markov Chain-based energy management for a hybrid tracked vehicle with speedy Q-learning. Energy, 160, 544-555. https://doi.o rg/10.1016/j.energy.2018.07.022
[2] Rahmatinejad, B., Rahimi Asiabaraki, H., Azimpour Shishevan, F., & Mohtadi Bonab, M. A. (2023). Experimental analysis of the effect of using aluminum oxide nanofluid in improving the heat transfer of XU7 engine radiator. The Journal of Engine Research, 70(2), 66-79. https://doi.org/10.22034/er.2023.2011671.1015
[3] Rahmatinejad, B., Rahimi Asiabaraki, H., & Azimpour Shishevan, F. (2023). Investigation of the effect of AL2O3 nanofluid in M13NI engine cooling system. The Journal of Engine Research, 70(1), 47-65. https://doi.org/10.22034/er.2023.1975318.0
[4] Rahmatinejad, B., Abbasgholipour, M., & Mohammadi Alasti, B. (2022). Experimental Evaluation of Heat Transfer of MF 285 Tractor Radiator, using Nano-fluid AL2O3+Water. Journal of Agricultural Machinery, 12(3), 281-299. https://doi.org/10.22067/jam.20 20.58870.0
[5] Andrade, G. M. S. D., Araújo, F. W. C. D., Santos, M. P. M. D. N., & Magnani, F. S. (2020). Standardized Comparison of 40 Local Driving Cycles: Energy and Kinematics. Energies, 13(20), 5434. https://doi.org/10.3390/en13205434
[6] Gebisa, A., Gebresenbet, G., Gopal, R., & Nallamothu, R. B. (2021). Driving Cycles for Estimating Vehicle Emission Levels and Energy Consumption. Future Transportation, 1(3), 615-638. https://doi.org/10.3390/futuretransp1030033
[7] Yang, C., Lu, Z., Wang, W., Li, Y., Chen, Y., & Xu, B. (2023). Energy management of hybrid electric propulsion system: Recent progress and a flying car perspective under three-dimensional transportation networks. Green Energy and Intelligent Transportation, 2(1), 100061. https://doi.org/10.1016/j.geits.2022.100061
[8] Saboohi, Y., & Farzaneh, H. (2008). Model for optimizing energy efficiency through controlling speed and gear ratio. Energy Efficiency, 1(1), 65-76. https://doi.org/10.1007/s12053 -008-9005-y
[9] Mafi, S., Kakaee, A., Mashadi, B., Moosavian, A., Abdolmaleki, S., & Rezaei, M. (2022). Developing local driving cycle for accurate vehicular CO2 monitoring: A case study of Tehran. Journal of Cleaner Production, 336, 130176. https://doi.org/10.1016/j.jcl epro.2021.130176
[10] Salihu, F., Demir, Y. K., & Demir, H. G. (2023). Effect of road slope on driving cycle parameters of urban roads. Transportation Research Part D: Transport and Environment, 118, 103676. https://doi.org/10.1016/j.trd.2023.103676
[11] Silvas, E., Hereijgers, K., Peng, H., Hofman, T., & Steinbuch, M. (2016). Synthesis of Realistic Driving Cycles With High Accuracy and Computational Speed, Including Slope Information. Institute of Electrical and Electronics Engineers Transactions on Vehicular Technology, 65(6), 4118-4128. https://doi.org/10.1109/TVT.2016.2546338
[12] Masclans Abelló, P., Medina Iglesias, V., de los Santos López, M. A., & Álvarez-Flórez, J. (2020). Real drive cycles analysis by ordered power methodology applied to fuel consumption, CO2, NOx and PM emissions estimation. Frontiers of Environmental Science & Engineering, 15(1), 4. https://doi.org/10.1007/s11783-020-1296-z
[13] Jeong, N. T., Yang, S. M., Kim, K. S., Wang, M. S., Kim, H. S., & Suh, M. W. (2016). Urban driving cycle for performance evaluation of electric vehicles. International Journal of Automotive Technology, 17(1), 145-151. https://doi.org/10.1007/s12239-016-0014-0
[14] Kessels, F. (2019). Introduction to Traffic Flow Modelling. In Traffic Flow Modelling: Introduction to Traffic Flow Theory Through a Genealogy of Models (pp. 1-19). Springer International Publishing. https://doi.org/10.1007/978-3-319-78695-7_1
[15] Zähringer, M., Kalt, S., & Lienkamp, M. (2020). Compressed Driving Cycles Using Markov Chains for Vehicle Powertrain Design. World Electric Vehicle Journal, 11(3), 52. h ttps://doi.org/10.3390/wevj11030052
[16] Liu, T., Tan, W., Tang, X., Zhang, J., Xing, Y., & Cao, D. (2021). Driving conditions-driven energy management strategies for hybrid electric vehicles: A review. Renewable and Sustainable Energy Reviews, 151, 111521. https://doi.org/10.1016/j.rser.2021.111521
[17] Sun, F., Yang, Q., Dahlquist, E., & Xiong, R. (2023). The Proceedings of the 5th International Conference on Energy Storage and Intelligent Vehicles (ICEIV 2022). Springer Nature. https://doi.org/10.1007/978-981-99-1027-4
[18] Pouresmaeili, M. A., Aghayan, I., & Taghizadeh, S. A. (2018). Development of Mashhad driving cycle for passenger car to model vehicle exhaust emissions calibrated using on-board measurements. Sustainable Cities and Society, 36, 12-20. https://doi.org/1 0.1016/j.scs.2017.09.034
[19] Azadi, M., Dezianian, S., Navi, A., Salmani, A., Qaraati, T., & Faraji, A. (2022). Development of a Driving Cycle Based on Data Recorded from an Electric-gasoline Hybrid Vehicle on Two Routes in Tehran City with K-means Algorithm. Quarterly Scientific Journal of National University of Skills, 19(1), 629-652. https://doi.org/10.48301/kssa.2022. 315133.1840
[20] Qaraati, T., Momeni Movahed, A., Azadi, M., & Moosavian, S. A. (2021). Comparison of Support Vector Machine and K-Means Algorithms Performance in Extracting the Real Driving Cycle of Combined Tehran-Amol. Amirkabir Journal of Mechanical Engineering, 53(9), 1177-1180. https://doi.org/10.22060/mej.2021.19222.6980
[21] Miri, S. E., Khalili, H., & Azadi, M. (2022, May 10). Development of driving cycle of Tehran-Semnan route based on real driving emission considerations with a hybrid car [Conference session]. Twelfth International Conference on Combustion Engines and Oil, Tehran, Iran. https://civilica.com/doc/1464963/
[22] Organisation for Economic Cooperation and Development. (2008). OECD glossary of statistical terms. https://doi.org/10.1787/9789264055087-en
[23] Maulik, U., & Bandyopadhyay, S. (2000). Genetic algorithm-based clustering technique. Pattern Recognition, 33(9), 1455-1465. https://doi.org/10.1016/S0031-3203(99)00 137-5
[24] Bradley, P. S., Bennett, K. P., & Demiriz, A. (2000). Constrained k-means clustering. Microsoft Research, Redmond, 1-8. https://www.researchgate.net/publication/2458036_Const rained_K-Means_Clustering
[25] Barlow, T. J., Latham, S., McCrae, I., & Boulter, P. (2009). A reference book of driving cycles for use in the measurement of road vehicle emissions. TRL. https://trid.trb.org /View/909274
[26] Montazeri-Gh, M., & Naghizadeh, M. (2007). Development of the Tehran car driving cycle. International Journal of Environment and Pollution, 30(1), 106-118. https://doi.org/ 10.1504/ijep.2007.014506
[27] Bholowalia, P., & Kumar, A. (2014). EBK-means: A clustering technique based on elbow method and k-means in WSN. International Journal of Computer Applications, 105(9), 17-24. https://doi.org/10.5120/18405-9674
[28] André, M. (2004). The ARTEMIS European driving cycles for measuring car pollutant emissions. Science of The Total Environment, 334-335, 73-84. https://doi.org/10.10 16/j.scitotenv.2004.04.070
[29] Norbakyah, J., Nordiyana, M., Anida, I., Ayob, A., & Salisa, A. (2021). myBas driving cycle for Kuala Terengganu city. International Journal of Electrical & Computer Engineering, 11(3), 2054-2061. https://doi.org/10.11591/ijece.v11i3.pp2054-2061
[30] Anida, I., & Salisa, A. (2019). Driving cycle development for Kuala Terengganu city using k-means method. International Journal of Electrical and Computer Engineering, 9(3), 1780-1787. https://doi.org/10.11591/ijece.v9i3.pp1780-1787
[31] Tourani, A., White, P., & Ivey, P. (2014). Analysis of electric and thermal behaviour of lithium-ion cells in realistic driving cycles. Journal of Power Sources, 268, 301-314. https://doi.org/10.1016/j.jpowsour.2014.06.010
[32] Wu, Y., & Liu, G. (2020). Research on construction of vehicle driving cycle based on Markov chain and global K-means clustering algorithm. Vehicle Dynamics, 4(1), 1-9. https://doi.org/10.18063/vd.v4i1.1135
[33] Shi, S., Lin, N., Zhang, Y., Huang, C., Liu, L., Lu, B., & Cheng, J. (2013, October 15-18). Research on Markov Property Analysis of Driving Cycle [Conference session]. 2013 IEEE Vehicle Power and Propulsion Conference, Beijing, China. https://doi.org/10. 1109/VPPC.2013.6671737
[34] Yuhui, P., Yuan, Z., & Huibao, Y. (2019). Development of a representative driving cycle for urban buses based on the K-means cluster method. Cluster Computing, 22(3), 6871-6880. https://doi.org/10.1007/s10586-017-1673-y
[35] Zhao, X., Zhao, X., Yu, Q., Ye, Y., & Yu, M. (2020). Development of a representative urban driving cycle construction methodology for electric vehicles: A case study in Xi’an. Transportation Research Part D: Transport and Environment, 81(2), 102279. https: //doi.org/10.1016/j.trd.2020.102279
[36] Abu Mallouh, M., Abdelhafez, E., Salah, M., Hamdan, M., Surgenor, B., & Youssef, M. (2014). Model development and analysis of a mid-sized hybrid fuel cell/battery vehicle with a representative driving cycle. Journal of Power Sources, 260, 62-71. https://do i.org/10.1016/j.jpowsour.2014.02.104
[37] Wang, L., Ma, J., Zhao, X., & Li, X. (2021). Development of a Typical Urban Driving Cycle for Battery Electric Vehicles Based on Kernel Principal Component Analysis and Random Forest. Institute of Electrical and Electronics Engineers Access, 9, 15053-15065. https://doi.org/10.1109/ACCESS.2021.3052820
[38] Huzayyin, O. A., Salem, H., & Hassan, M. A. (2021). A representative urban driving cycle for passenger vehicles to estimate fuel consumption and emission rates under real-world driving conditions. Urban Climate, 36, 100810. https://doi.org/10.1016/j.ucli m.2021.100810
[39] Humaira, H., & Rasyidah, R. (2018, January 24-25). Determining the appropiate cluster number using elbow method for k-means algorithm [Conference session]. Proceedings of the 2nd Workshop on Multidisciplinary and Applications, Padang, Indonesia. http ://dx.doi.org/10.4108/eai.24-1-2018.2292388
[40] Umargono, E., Suseno, J. E., & Gunawan, S. V. (2020, November 25). K-means clustering optimization using the elbow method and early centroid determination based on mean and median formula [Conference session]. The 2nd International Seminar on Science and Technology, Yogyakarta, Indonesia. https://doi.org/10.2991/assehr.k.201010.019
[41] Wang, Q., Huo, H., He, K., Yao, Z., & Zhang, Q. (2008). Characterization of vehicle driving patterns and development of driving cycles in Chinese cities. Transportation Research Part D: Transport and Environment, 13(5), 289-297. https://doi.org/10.1016/j.trd.2 008.03.003
[42] Tharvin, R., Kamarrudin, N., Shahriman, A., Zunaidi, I., Razlan, Z., Wan, W., Harun, A., Hashim, M., Ibrahim, I., & Faizi, M. (2018, August 15-17). Development of driving cycle for passenger car under real world driving conditions in Kuala Lumpur, Malaysia [Conference session]. International Conference on Advanced Manufacturing and Industry Applications, Sarawak, Malaysia. https://doi.org/10.1088/1757-899X/429/1/012047
[43] Hung, W. T., Tong, H. Y., Lee, C. P., Ha, K., & Pao, L. Y. (2007). Development of a practical driving cycle construction methodology: A case study in Hong Kong. Transportation Research Part D: Transport and Environment, 12(2), 115-128. https://doi.org/10.10 16/j.trd.2007.01.002
[44] Degraeuwe, B., & Weiss, M. (2017). Does the New European Driving Cycle (NEDC) really fail to capture the NOX emissions of diesel cars in Europe? Environmental Pollution, 222, 234-241. https://doi.org/10.1016/j.envpol.2016.12.050
[45] Zhao, X., Yu, Q., Ma, J., Wu, Y., Yu, M., & Ye, Y. (2018). Development of a Representative EV Urban Driving Cycle Based on a k-Means and SVM Hybrid Clustering Algorithm. Journal of Advanced Transportation, 2018(1), 1890753. https://doi.org/10.1155/20 18/1890753
دوره 21، شماره 3
فنی و مهندسی
پاییز 1403
صفحه 183-207

  • تاریخ دریافت 11 دی 1402
  • تاریخ بازنگری 06 فروردین 1403
  • تاریخ پذیرش 30 خرداد 1403