پژوهشنامه حمل و نقل

پژوهشنامه حمل و نقل

ارزیابی و مدل‌سازی تغییر خط رانندگان در جاده ها با توجه به عوامل ایمنی راه ها

نوع مقاله : مقاله پژوهشی

نویسندگان
1 استاد، دانشکده مهندسی عمران، دانشگاه علم و صنعت ایران، تهران، ایران
2 دانشجوی دکتری، دانشکده مهندسی عمران، دانشگاه علم و صنعت ایران، تهران، ایران
چکیده
مدل های تغییر خط به عنوان یکی از اجزای مهم در شبیه سازهای ترافیک میکروسکوپی محسوب می شوند که به طور فزاینده ابزار انتخابی برای طیف گسترده ای از کاربردهای ترافیکی در سطح عملیاتی هستند. در این مطالعه تلاش است تا با روشی نوین داده های مناسب جمع آوری شود و مدل برتر ارائه شود. حدفاصل زیباشهر قزوین تا گلشهر کرج به عنوان منطقه مورد مطالعه انتخاب شد. از طریق نصب دوربین و شناسایی تصویر با استفاده از نرم افزار های آماری به ساخت مدل پرداخته شد. مدل براونی به منظور ساخت مدل تغییر خط انتخاب شد. نتایج بیانگر آن هستند که مدل لگاریتمی نسبت به بقیه مدل ها ضریب تعیین بهتری دارد و مدل قدرتمندتری است. همچنین مدل "آر اس ام" با مقدار ضریب "خوبی برازش" بالاتر مدل بهتری را ارائه می دهد. متغیر پاسخ به طور سه بعدی در برابر تغییرات فاصله از جلو و فاصله از عقب بدست آمد. مقادیر فاصله از جلو و فاصله از عقب دارای اثرگذاری بیشتری نسبت به مقادیر فواصل از چپ و راست دارد. خروجی داده های آزمایشی از محل مورد مطالعه و مدل بروانی دارای اختلاف میانگین کمی بوده و انحراف معیار نیز بسیار کم گزارش شده است. میزان همبستگی نیز مقدار معقول و مطلوبی بدست آمد که نشانگر اختلاف کم بین مشاهدات میدانی و مدل حرکت براونی می باشد.
کلیدواژه‌ها

موضوعات


عنوان مقاله English

Evaluation and Modeling of Drivers Lane Changing on Roads According to Road Safety Factors

نویسندگان English

Shahriar Afandizadeh 1
Hamid Bigdeli Rad 2
1 Professor, School of Civil Engineering, Iran University of Science and Technology, Tehran, Iran.
2 Ph.D., Candidate, School of Civil Engineering, Iran University of Science and Technology, Tehran, Iran.
چکیده English

Lane change models are an important component in microscopic traffic simulators, which are increasingly the tool of choice for a wide variety of traffic applications at the operational level. In this study, an attempt is made to collect suitable data with a new method and present the best model. The area between Zibashahr Qazvin and Golshahr Karaj was chosen as the study area. By installing a camera and identifying the image using statistical software, the model was built. Brownie model was chosen to build the line change model. The results show that the logarithmic model has a better coefficient of determination than other models and is a more powerful model. Also, the "RSM" model with a higher "goodness of fit" coefficient provides a better model. The response variable was obtained three-dimensionally against the changes of distance from the front and distance from the back. The values of the distance from the front and the distance from the back have more effect than the values of the distances from the left and right. The output of experimental data from the study site and the Barwani model has a small average difference and the standard deviation is also reported to be very low. The correlation level was also a reasonable and favourable value, which indicates a small difference between the field observations and the Brownian motion model. 

کلیدواژه‌ها English

Driver Lane Changing
Statistical Modelling
Brownie Model
Freeway Safety
-Abdi, A., Mosadeq, Z., & Bigdeli Rad, H. (2020). Prioritization of factors affecting suburban road safety by fuzzy hierarchical analysis. Journal of Transportation Research.
-Abiodun, O. I., Jantan, A., Omolara, A. E., Dada, K. V., Umar, A. M., Linus, O. U., ... & Kiru, M. U. (2019). Comprehensive review of artificial neural network applications to pattern recognition. IEEE Access, 7, 158820-158846.
-Afandizade Zargari, S., Bigdeli Rad, H., & Shaker, H. (2019). Using optimization and metaheuristic method to reduce the bus headway (Case study: Qazvin Bus Routes). Quarterly Journal of Transportation Engineering, 10(4), 833-849.
-Afandizadeh, S., & Gharehdaghli, H. (2021). A new steady-state traffic noise model for estimating L10 (h) on free flow roads using Reference Energy Mean Emission Levels. Building and Environment, 196, 107685.
-Afandizadeh, S., Aziz Jalali, D., & Bigdeli Rad, H. (2023). Optimal routing for shared autonomous vehicles feeder services in urban networks. Journal of Transportation Research.
-Ahmed, K. L., Ben-Akiva, M., Koutsopoulos, H., & Mishalani, R. (1996). Models of freeway lane changing and gap acceptance behavior. Transportation and Traffic Theory, 13, 501-515.
-An, S., Xu, L., Qian, L., Chen, G., Luo, H., & Li, F. (2020). Car-following model for autonomous vehicles and mixed traffic flow analysis based on discrete following interval. Physica A: Statistical Mechanics and its Applications, 560, 125246.
-Balal, E., Cheu, R. L., & Sarkodie-Gyan, T. (2016). A binary decision model for discretionary lane changing move based on fuzzy inference system. Transportation Research Part C: Emerging Technologies, 67, 47-61.
-Bham, G. H. (2009). Estimating driver mandatory lane change behavior on a multi lane freeway. Proc. 88th Annu. Meet. Transp. Res. Board, 1-22.
-Cervantes, J., Garcia-Lamont, F., Rodríguez-Mazahua, L., & Lopez, A. (2020). A comprehensive survey on support vector machine classification: Applications, Challenges and Trends. Neurocomputing, 408, 189-215.
-Chen, N., van Arem, B., Alkim, T., & Wang, M. (2020). A hierarchical model-based optimization control approach for cooperative merging by connected automated vehicles. IEEE Transactions on Intelligent Transportation Systems, 22(12),
7712-7725.
-Gipps, P. G. (1986). A model for the structure of lane-changing decisions. Transportation Research Part B: Methodological, 20(5),403-414.
-Hajisoleimani, M. M., Abdi, A., & Bigdeli Rad, H. (2021). Intermodal Non-Motorized Transportation Mode Choice; Case Study, Qazvin City. Space Ontology Journal, International 10(3), 31-46.
-Hidas, P. (2002). Modelling lane changing and merging in microscopic traffic simulation. Transportation Research Part C: Emerging Technologies, 10(5-6), 351-371.
-Jeon, W., Zemouche, A., & Rajamani, R. (2019). Tracking of vehicle motion on highways and urban roads using a nonlinear observer. IEEE/ASME Transactions on Mechatronics, 24(2), 644-655.
-Kim, S., Bang, J. S., Kim, S., & Lee, H. (2020). Robust vehicle speed control using disturbance observer in hybrid electric vehicles. International Journal of Automotive Technology, 21, 931-942.
-Liu, Y., Wang, X., Li, L., Cheng, S., & Chen, Z. (2019). A novel lane change decision-making model of autonomous vehicle based on support vector machine. IEEE Access, 7, 26543-26550.
-Pisner, D. A., & Schnyer, D. M. (2020). Support vector machine. In Machine learning, 101-121. Academic Press.
-Ren, G., Zhang, Y., Liu, H., Zhang, K., & Hu, Y. (2019). A new lane-changing model with consideration of driving style. International Journal of Intelligent Transportation Systems Research, 17, 181-189.
-Rodríguez, A. J., Sanjurjo, E., Pastorino, R., & Naya, M. Á. (2021). State, parameter and input observers based on multibody models and Kalman filters for vehicle dynamics. Mechanical Systems and Signal Processing, 155, 107544.
-Samek, W., Montavon, G., Lapuschkin, S., Anders, C. J., & Müller, K. R. (2021). Explaining deep neural networks and beyond: A review of methods and applications. Proceedings of the IEEE, 109(3),247-278.
-Scanagatta, M., Salmerón, A., & Stella, F. (2019). A survey on Bayesian network structure learning from data. Progress in Artificial Intelligence, 8, 425-439.
-Sharma, O., Sahoo, N. C., & Puhan, N. B. (2022). Highway Lane-Changing Prediction Using a Hierarchical Software Architecture based on Support Vector Machine and Continuous Hidden Markov Model. International Journal of Intelligent Transportation Systems Research, 20(2),519-539.
-Yuan, J., Abdel-Aty, M., Cai, Q., & Lee, J. (2019). Investigating drivers' mandatory lane change behavior on the weaving section of freeway with managed lanes: A driving simulator study. Transportation Research Part F: Traffic Psychology and Behaviour, 62,11-32.
-Zheng Y, Hansen JHL (2017) Lane-change detection from steering signal using spectral segmentation and learning-based classification. IEEE Trans Intell Veh, 2(1):14–24.
-Zheng, Y., Ran, B., Qu, X., Zhang, J., & Lin, Y. (2019). Cooperative lane changing strategies to improve traffic operation and safety nearby freeway off-ramps in a connected and automated vehicles environment. IEEE Transactions on Intelligent Transportation Systems, 21(11), 4605-4614.