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Modelling the Free Flow Speed and 85th Percentile Speed Using Artificial Neural Network (ANN) and Genetic Algorithm
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DOI: https://doi.org/10.15866/irece.v13i4.20678
Abstract
One of the main and crucial purposes of highway system is to provide a safe, comfortable, and efficient mode of transportation. Vehicular speed is considered as one of the high-priority issue to transportation engineers, planners and researchers, where it is a significant measure of effectiveness of traffic performance particularly under mixed traffic condition, which affects the traffic movement and level of service at different transportation facilities. In order to propose a new analytical method for vehicular speed, speed prediction models based on Artificial Neural Network (ANN) models and Genetic Algorithm (GA) have been developed for major urban arterial roads in Jordan. Prediction models have been developed with several input parameters and included within the ANN and GA. Traffic and geometric variables such as left lateral clearance, right lateral clearance, speed limit, Present Condition Index (PCI), shoulder width, lane width, access point density, International Roughness Index (IRI) and Present Serviceability Rating (PSR) have been included in both models. Meanwhile, the outputs of prediction models have been 85th percentile speed and Mean Free Flow Speed (MFFS) km/hr. The computational results show that the speeds predicted by the developed models are highly correlated with the measured ones. ANN modeling has a better performance than GA in estimation of 85th percentile speed. This study provides useful information to predict the FFS and 85th percentile speed on roads depending on variables, which are available on any constructed or to be constructed roads.
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References
S. Biswas, S. Chandra, and I. Ghosh, Estimation of Vehicular Speed and Passenger Car Equivalent Under Mixed Traffic Condition Using Artificial Neural Network, Arab. J. Sci. Eng., 2017.
https://doi.org/10.1007/s13369-017-2597-9
P. Tseng, F. Lin, and S.-L. Shieh, Estimation of Free-Flow Speeds for Multilane Rural and suburban highways, Transportation (Amst)., 2005.
D. Singh, M. Zaman, and L. White, Neural network modeling of 85th percentile speed for two-lane rural highways, Transp. Res. Rec., 2017.
A. Mahmoudabadi, Using artificial neural network to estimate average speed of vehicles in rural roads. 2010.
C. Bennett, A speed prediction model for rural two-lane highways, University of Auckland, New Zealand., 1994.
S. Nokandeh, M., Ghosh, I. and Chandra, Estimation of Capacity of Two-lane Inter-Urban Roads in India from Free Speed data, 15th International Conference on Transportation and Traffic, India, 2016. [Online-Accessed: 14-Sep-2019]. Available:
https://www.researchgate.net/publication/311355815_Estimation_of_Capacity_of_Two-lane_Inter-Urban_Roads_in_India_from_Free_Speed_data
S. K. S. Abbas, M. A. Adnan, and I. R. Endut, Exploration of 85th percentile operating speed model on horizontal curve: A case study for two-lane rural highways, in Procedia - Social and Behavioral Sciences, 2011.
https://doi.org/10.1016/j.sbspro.2011.04.456
H. R. A.-M. Bashar H Al-Omari, Effect of speed humps on traffic delay in Jordan, Road Transp. Res., vol. 11, no. 4, p. 49, 2002.
H. R. Al-Masaeid, Impact of pavement condition on rural road accidents, Can. J. Civ. Eng., 1997.
https://doi.org/10.1139/l97-009
M. A. O. Ahmed, Trained Neural Networks Ensembles Weight Connections Analysis, in Advances in Intelligent Systems and Computing, 2018.
https://doi.org/10.1007/978-3-319-74690-6_24
M. Mitchell, An Introduction to Genetic Algorithms (Complex Adaptive Systems), MIT Press, 1998.
A. Chipperfield, P. Fleming, and H. Pohlheim, Genetic Algorithm Toolbox for use with MATLAB, Dep. Autom. …, 1994.
https://doi.org/10.1049/ic:19950061
R. Putha, L. Quadrifoglio, and E. Zechman, Comparing Ant Colony Optimization and Genetic Algorithm Approaches for Solving Traffic Signal Coordination under Oversaturation Conditions, Comput. Civ. Infrastruct. Eng., 2012.
https://doi.org/10.1111/j.1467-8667.2010.00715.x
Z. Yang et al., A double-loop hybrid algorithm for the traveling salesman problem with arbitrary neighbourhoods, Eur. J. Oper. Res., 2018.
https://doi.org/10.1016/j.ejor.2017.07.024
R. K. Arakaki and F. L. Usberti, Hybrid genetic algorithm for the open capacitated arc routing problem, Comput. Oper. Res., 2018.
https://doi.org/10.1016/j.cor.2017.09.020
S. B. Pattnaik, S. Mohan, and V. M. Tom, Urban bus transit route network design using genetic algorithm, J. Transp. Eng., 1998.
https://doi.org/10.1061/(ASCE)0733-947X(1998)124:4(368)
S. Hanandeh, S. F. Alabdullah, S. Aldahwi, A. Obaidat, and H. Alqaseer, Development of a constitutive model for evaluation of bearing capacity from CPT and theoretical analysis using ann techniques, Int. J. GEOMATE, 2020.
https://doi.org/10.21660/2020.74.36965
X. Tang and X. Yang, Inverse Analysis of Pavement Structural Properties Based on Dynamic Finite Element Modeling and Genetic Algorithm, Int. J. Transp. Sci. Technol., vol. 2, no. 1, pp. 15-30, Mar. 2013.
https://doi.org/10.1260/2046-0430.2.1.15
Batayneh, W., Bataineh, A., Jaradat, M., Intelligent Adaptive Fuzzy Logic Genetic Algorithm Controller for Anti-Lock Braking System, (2021) International Review on Modelling and Simulations (IREMOS), 14 (1), pp. 44-54.
https://doi.org/10.15866/iremos.v14i1.19838
Idroes, R., Noviandy, T., Maulana, A., Suhendra, R., Sasmita, N., Muslem, M., Idroes, G., Kemala, P., Irvanizam, I., Application of Genetic Algorithm-Multiple Linear Regression and Artificial Neural Network Determinations for Prediction of Kovats Retention Index, (2021) International Review on Modelling and Simulations (IREMOS), 14 (2), pp. 137-145.
https://doi.org/10.15866/iremos.v14i2.20460
Goudjil, K., Sbartai, B., Optimization of Shear Wave Velocity (Vs) from a Post-Liquefaction Settlement Using a Genetic Algorithm Multi-Objective NSGA II, (2017) International Review of Mechanical Engineering (IREME), 11 (3), pp. 175-180.
https://doi.org/10.15866/ireme.v11i3.11226
Katruksa, S., Jiriwibhakorn, S., Evaluation of Mid-Term Load Forecasting Case Study Based on Adaptive Neuro-Fuzzy Inference System (ANFIS) and Artificial Neural Networks (ANNs), (2020) International Review of Electrical Engineering (IREE), 15 (4), pp. 283-293.
https://doi.org/10.15866/iree.v15i4.17766
Anggriawan, D., Amsyar, A., Firdaus, A., Wahjono, E., Sudiharto, I., Prasetyono, E., Tjahjono, A., Real Time Harmonic Load Identification Based on Fast Fourier Transform and Artificial Neural Network, (2021) International Review of Electrical Engineering (IREE), 16 (3), pp. 220-228.
https://doi.org/10.15866/iree.v16i3.18131
S. Hanandeh, A. Ardah, and M. Abu-Farsakh, Using artificial neural network and genetics algorithm to estimate the resilient modulus for stabilized subgrade and propose new empirical formula, Transp. Geotech., 2020.
https://doi.org/10.1016/j.trgeo.2020.100358
W. Al Bodour, S. Hanandeh, M. Hajij, and Y. Murad, Development of Evaluation Framework for the Unconfined Compressive Strength of Soils Based on the Fundamental Soil Parameters Using Gene Expression Programming and Deep Learning Methods, J. Mater. Civ. Eng., 2022.
https://doi.org/10.1061/(ASCE)MT.1943-5533.0004087
D. Singh, M. Zaman, and L. White, Neural Network Modeling of 85th Percentile Speed for Two-Lane Rural Highways, Transp. Res. Rec. J. Transp. Res. Board, vol. 2301, no. 1, pp. 17-27, Jan. 2012.
https://doi.org/10.3141/2301-03
I. H. Hashim, T. A. Abdel-Wahed, and Y. Moustafa, Toward an operating speed profile model for rural two-lane roads in Egypt, J. Traffic Transp. Eng. (English Ed., 2016.
https://doi.org/10.1016/j.jtte.2015.09.005
G. Sil, A. Maji, S. Nama, and A. K. Maurya, Operating speed prediction model as a tool for consistency based geometric design of four-lane divided highways, Transport, vol. 34, no. 4, pp. 425-436, Jul. 2019.
https://doi.org/10.3846/transport.2019.10715
M. A. Sahraei and O. Bin Che Puan, Traffic Delay Estimation Using Artificial Neural Network (ANN) at Unsignalized Intersections, Proceedings of the 3rd International Conference on Civil, Structural and Transportation Engineering (ICCSTE'18) Niagara Falls, Canada - June 10 - 12, 2018 2018.
https://doi.org/10.11159/iccste18.106
Maha Abdulrahim Talal Mahmoud, Estimation of Free Flow Speed at Suburban and Rural Divided Multilane Highways, Jordan University Of Science & Technology, 2013.
O. S. Eluyode and D. T. Akomolafe, Comparative study of biological and artificial neural networks, Eur. J. Appl. Eng. Sci. Res., 2013.
S. Chandra, Effect of road roughness on capacity of two-lane roads, J. Transp. Eng., 2004.
https://doi.org/10.1061/(ASCE)0733-947X(2004)130:3(360)
Genetic algorithms in search, optimization, and machine learning, Choice Rev. Online, 1989.
J. Koza, Genetic programming: on the programming of computers by means of natural selection. 1992.
C. Ferreira, Gene Expression Programming in Problem Solving, in Soft Computing and Industry, 2002.
https://doi.org/10.1007/978-1-4471-0123-9_54
M. A. Shahin, H. R. Maier, and M. B. Jaksa, Data division for developing neural networks applied to geotechnical engineering, J. Comput. Civ. Eng., 2004.
https://doi.org/10.1061/(ASCE)0887-3801(2004)18:2(105)
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