Smart Traffic: Traffic Congestion Reduction by Shortest Route * Search Algorithm
Smart Traffic: Traffic Congestion Reduction by Shortest Route * Search Algorithm |
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© 2023 by IJETT Journal | ||
Volume-71 Issue-3 |
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Year of Publication : 2023 | ||
Author : A. Lakshna, S. Gokila, K. Ramesh, R. Surendiran |
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DOI : 10.14445/22315381/IJETT-V71I3P244 |
How to Cite?
A. Lakshna, S. Gokila, K. Ramesh, R. Surendiran, "Smart Traffic: Traffic Congestion Reduction by Shortest Route * Search Algorithm," International Journal of Engineering Trends and Technology, vol. 71, no. 3, pp. 423-433, 2023. Crossref, https://doi.org/10.14445/22315381/IJETT-V71I3P244
Abstract
Traffic congestion is a major issue on the city side, resulting in an increased level of traffic and negative impacts on the environment and public health. In this research, the shortest route * search algorithm proposed a solution to find the simplest route with the minimum duration in traffic congestion. The shortest route * search algorithm searches for the simplest route from the origin to the destination while considering current traffic conditions. The shortest route * search approach involves traffic data pre-processing of previous records and current traffic data to create a weighted graph representation from the road network. The proposed algorithm works only on the best route and concentrates on the nearest shortest node to determine the simplest path. This approach optimizes the time complexity by avoiding search time for all nodes. The algorithm was evaluated on a traffic dataset, which resulted in 97% of high accuracy. The shortest route * search algorithm was compared with the existing algorithm. The results showed that the shortest route * search approach significantly reduced the travel time in traffic conditions, demonstrating the potential of a shortest route * search algorithm to improve transportation efficiency and reduce environmental impact.
Keywords
Shortest route prediction, Shortest route * search algorithm, Shortest paths, Fastest route, Minimum travelling time.
References
[1] Verma, K., and Paike, V, “Smart City Intelligent System Traffic Congestion Optimization Using the Internet of Thing,” Arxiv Preprint Arxiv:1911.01286,
CrossRef | Google Scholar | Publisher Link
[2] Xiaowei Chen, Harry Haoxiang Wang, and Bin Tian, “Visualization Model of Big Data Based on Self-Organizing Feature Map Neural Network and Graphic Theory for Smart Cities,” Cluster Computing, vol. 22, no. 6, pp.13293-13305, 2019.
CrossRef | Google Scholar | Publisher Link
[3] Zhibin Chen et al., “Path Controlling of Automated Vehicles for System Optimum on Transportation Networks with Heterogeneous Traffic Streams,” Transportation Research Part C: Emerging Technologies, vol. 110, pp.312-329, 2020.
CrossRef | Google Scholar | Publisher Link
[4] Mazhar Iqbal et al., "A Fast and Reliable Dijkstra Algorithm for Online Shortest Path," SSRG International Journal of Computer Science and Engineering, vol. 5, no. 12, pp. 24-27, 2018.
CrossRef | Google Scholar | Publisher Link
[5] Prashanth Venkatraman, and Michael W. Levin, “A Congestion-Aware Tabu Search Heuristic to Solve the Shared Autonomous Vehicle Routing Problem,” Journal of Intelligent Transportation Systems, vol. 25, no. 4, pp. 343-355, 2021.
CrossRef | Google Scholar | Publisher Link
[6] Ertugrul Bayraktar et al., “Traffic Congestion-Aware Graph-Based Vehicle Rerouting Framework from Aerial Imagery,” Engineering Applications of Artificial Intelligence, vol. 119, p.105769.
CrossRef | Google Scholar | Publisher Link
[7] Seyyed-Mahdi Hosseini-Motlagh, Maryam Farahmand, and Mina Nouri-Harzvili, “A Multi-Path Traffic-Covering Pollution Routing Model with Simultaneous Pickup and Delivery,” Computers & Industrial Engineering, vol. 173, p.108644, 2022.
CrossRef | Google Scholar | Publisher Link
[8] Dr. Shaveta Bhatia, "Survey of Shortest Path Algorithms," SSRG International Journal of Computer Science and Engineering, vol. 6, no. 11, pp. 33-39, 2019.
CrossRef | Publisher Link
[9] Carise E. Schmidt et al., “Time-Dependent Fleet Size and Mix Multi-Depot Vehicle Routing Problem,” International Journal of Production Economics, vol. 255, p.108653, 2023.
CrossRef | Google Scholar | Publisher Link
[10] Tianyu Zhao et al., “RNE: Computing Shortest Paths Using Road Network Embedding,” The VLDB Journal, vol. 31, pp. 504-528, 2022.
CrossRef | Google Scholar | Publisher Link
[11] Dian Ouyang et al., “Efficient Shortest Path Index Maintenance on Dynamic Road Networks with Theoretical Guarantees,” Proceedings of the VLDB Endowment, vol. 13, no. 5, pp. 602-615, 2020.
CrossRef | Google Scholar | Publisher Link
[12] R.Aaditya Mehra, and G.Charan Yadav, "Implementation of Novel Routing Algorithm for Updating the Road Network Data Instantaneously," SSRG International Journal of Geoinformatics and Geological Science, vol. 1, no. 1, pp. 10-13, 2014.
CrossRef | Publisher Link
[13] Lingxiao Li et al., “Continuously Monitoring Alternative Shortest Paths on Road Networks,” Proceedings of the VLDB Endowment, vol. 13, no. 12, pp. 2243-2255, 2020. CrossRef | Google Scholar | Publisher Link
[14] Mingyu Pi et al., “Visual Cause Analytics for Traffic Congestion,” IEEE Transactions on Visualization and Computer Graphics, vol. 27, no. 3, pp. 2186-2201, 2019.
CrossRef | Google Scholar | Publisher Link
[15] Sheema, D et al., “An Algorithm for Detection and Identification of Infestation Density of Pest-Fall Armyworm in Maize Plants Using Deep Learning Based on IoT,” International Journal of Engineering Trends and Technology, vol. 70, no. 9, pp. 240-251, 2022.
CrossRef | Google Scholar | Publisher Link
[16] Vaibhavi Patel, and Prof. Chitrabaggar, "A Survey Paper of Bellman-Ford Algorithm and Dijkstra Algorithm for Finding Shortest Path in GIS Application,” International Journal of P2P Network Trends and Technology, vol. 4, no. 1, pp. 21-23, 2014.
Publisher Link
[17] Jianzhong Qi et al., “A Graph and Attentive Multi-Path Convolutional Network for Traffic Prediction,” IEEE Transactions on Knowledge and Data Engineering, p.1, 2022.
CrossRef | Google Scholar | Publisher Link
[18] Mengxuan Zhang et al., “Stream Processing of Shortest Path Query in Dynamic Road Networks,” IEEE Transactions on Knowledge and Data Engineering, vol. 34, no. 5, pp. 2458-2471, 2022.
CrossRef | Google Scholar | Publisher Link
[19] Zetian Jiang, Tianzhe Wang, and Junchi Yan, “Unifying Offline and Online Multi-Graph Matching via Finding Shortest Paths on Supergraph,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 43, no. 10, pp. 3648-3663, 2020.
CrossRef | Google Scholar | Publisher Link
[20] Dhanushree.V et al., "Traffic Control and Vehicle Tracking Using RFID," SSRG International Journal of Electronics and Communication Engineering, vol. 5, no. 12, pp. 6-9, 2018.
CrossRef | Publisher Link
[21] Ranwa Al Mallah, Alejandro Quintero, and Bilal Farooq, “Prediction of Traffic Flow via Connected Vehicles,” IEEE Transactions on Mobile Computing, vol. 21, no. 1, pp. 264-277, 2022.
CrossRef | Google Scholar | Publisher Link
[22] Jiankun Wang et al., “Robot Path Planning via Neural-Network-Driven Prediction,” IEEE Transactions on Artificial Intelligence, vol. 3, no. 3, pp. 451-460, 2022.
CrossRef | Google Scholar | Publisher Link
[23] He-xuan Hu et al., “Multi-Source Information Fusion Based Dlaas for Traffic Flow Prediction,” IEEE Transactions on Computers, pp. 1-11, 2023.
CrossRef | Google Scholar | Publisher Link
[24] Sukhuman Rianthong et al., "The Reduction of Transportation Cost in Transportation Company by Evolutionary Methods," International Journal of Engineering Trends and Technology, vol. 69, no. 2, pp. 118-125, 2021.
CrossRef | Publisher Link
[25] Xiaohuan Liu et al., “Novel Best Path Selection Approach Based on Hybrid Improved A* Algorithm and Reinforcement Learning,” Applied Intelligence, vol. 51, pp. 9015-9029.
CrossRef | Google Scholar | Publisher Link
[26] Lamia Karim, Abdellah Daissaoui, and Azedine Boulmakoul, “Robust Routing Based on Urban Traffic Congestion Patterns,” Procedia Computer Science, vol. 109, pp. 698-703, 2017. CrossRef | Google Scholar | Publisher Link
[27] Yuan Gao et al., “Traffic Speed Forecast in an Adjacent Region Between a Highway and Urban Expressway: Based on MFD and GRU Model,” Journal of Advanced Transportation, vol. 2020, pp.1-18, 2020.
CrossRef | Google Scholar | Publisher Link
[28] C.Ambika, M.Karnan, and R.Sivakumar, "Resolving Dynamic Shortest Path Routing Problems in Mobile Adhoc Networks Using ABC and ACO,” International Journal of Computer & Organization Trends, vol. 3, no. 1, pp. 58-62, 2013.
Publisher Link
[29] Yan Zheng et al., “Real-Time Prediction and Navigation on Traffic Congestion Model With Equilibrium Markov Chain,” International Journal of Distributed Sensor Networks, vol. 14, no. 4, 2018.
CrossRef | Google Scholar | Publisher Link
[30] Yunchuan Sun et al., “Discovering Time-Dependent Shortest Path on Traffic Graph for Drivers towards Green Driving,” Journal of Network and Computer Applications, vol. 83, pp. 204-212, 2017.
CrossRef | Google Scholar | Publisher Link
[31] Junhua Zhang et al., “Efficient Label-Constrained Shortest Path Queries on Road Networks: A Tree Decomposition Approach,” Proceedings of the VLDB Endowment, vol. 15, no. 3, pp. 686-698, 2021.
CrossRef | Google Scholar | Publisher Link
[32] R.U.Yawle et al., “Smart Traffic Control System," SSRG International Journal of Electronics and Communication Engineering, vol. 3, no. 3, pp. 20-23, 2016.
CrossRef | Publisher Link
[33] Nils Werner, and Tim Zeitz “Combining Predicted and Live Traffic with Time-Dependent A* Potentials,” Leibniz International Proceedings in Informatics, vol. 244, 2022.
CrossRef | Google Scholar | Publisher Link
[34] Wei Yin, and Xiaoguang Yang, “An Astar-Based Multi-Path Algorithm for the Recognition of Reasonable Route Sets in-Vehicle Navigation Systems,” Procedia-Social and Behavioural Sciences, vol. 96, pp.1069-1078, 2013.
CrossRef | Google Scholar | Publisher Link
[35] Ms.S.Supraja, and Dr.P.Ranjith Kumar, "An Intelligent Traffic Signal Detection System Using Deep Learning," SSRG International Journal of VLSI & Signal Processing, vol. 8, no. 1, pp. 5-9, 2021.
CrossRef | Publisher Link
[36] Changshi Liu et al., “Time-Dependent Vehicle Routing Problem with Time Windows of City Logistics with a Congestion Avoidance Approach,” Knowledge-Based Systems, vol. 188, p.104813, 2020.
CrossRef | Google Scholar | Publisher Link
[37] Mun Chon Ho et al., “An Improved Pheromone-Based Vehicle Rerouting System to Reduce Traffic Congestion,” Applied Soft Computing, vol. 84, p.105702, 2019.
CrossRef | Google Scholar | Publisher Link
[38] Sayed Ahmed et al., “Mobile-Based Routes Network Analysis for an Emergency Response Using an Enhanced Dijkstra’s Algorithm and AHP,” International Journal of Intelligent Engineering and Systems, vol. 11, no. 6, pp. 252-260.
CrossRef | Google Scholar
[39] LS Jabbar et al., “A Modification of Shortest Path Algorithm According to Adjustable Weights Based on Dijkstra Algorithm,” Engineering and Technology Journal, vol. 41, no. 2, pp. 359-374, 2023.
CrossRef | Google Scholar | Publisher Link