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Smart Tolling through AI: Revolutionizing Payment Systems for Modern Transportation Networks
Subject area: Science,Engineering and Technology · Area of research: Artificial Intelligence
Abstract
The rapid development of artificial intelligence is transforming industries across the world, including transportation. Smart tolling, powered by AI technologies, is emerging as a revolutionary approach to modernizing payment systems within transportation networks. Traditional toll collection systems, often characterized by inefficiency, long queues, and static pricing, are being replaced by intelligent systems that provide real-time, seamless, and adaptive solutions. The paper discusses the use of AI-driven technologies, such as machine learning algorithms, computer vision, and natural language processing, on tolling systems for some of the most common and persistent challenges in traffic congestion, revenue optimization, and user experience. AI-powered tolling systems use real-time data from various IoT devices like cameras, sensors, and RFID readers to enable automatic vehicle identification, dynamic pricing, and contactless payment. The machine learning models study the pattern of traffic flow to estimate peak hours and thus optimize the rates of tolls. In this way, it helps in reducing congestion and enhancing efficiency. Moreover, computer vision technologies, including license plate recognition and vehicle classification, help in managing tolls by reducing human interference and hence errors. These developments contribute to better traffic management, operational efficiency, and environmental sustainability by reducing emissions and fuel consumption that come with congestion. The paper also examines the potential challenges and ethical considerations of smart tolling systems. Issues such as data privacy, cybersecurity, and public acceptance are critical for widespread adoption. Transparent governance frameworks, stakeholder engagement, and robust data protection measures are essential to address these concerns. In general, intelligent tolling with the use of AI is a new paradigm in transportation infrastructure. Integration of intelligent systems into tolling processes could enable governments and private operators to efficiently manage road utilization, improve revenue collection, and ensure a user-friendly experience. This paper highlights technological innovations, benefits, and future prospects of AI-driven tolling, providing a comprehensive understanding of its transformative potential in modern transportation networks.
Keywords
Smart Tolling, AI in Transportation, Intelligent Traffic Systems, Toll Collection Technology, AI-Powered Tolling, Autonomous Vehicles and Tolling, Electronic Toll Collection (ETC), Contactless Payment Systems, AI and Traffic Management, Real-Time Traffic Monitoring, Dynamic Pricing for Tolls, Smart Transportation Networks, Machine Learning in Tolling, Automated Toll Systems, Vehicle Recognition Technology, AI-Based Payment Systems, Digital Tolling Solutions, Traffic Flow Optimization, AI and Infrastructure, Transportation Network Innovation
References
[1] Gupta, S., & Khandelwal, S. (2021). AI-based Traffic and Toll Management for Smart Cities. Springer.
[2] Li, X., Wang, S., & Zhang, Y. (2020). Smart Transportation Systems: AI and IoT-Based Solutions. Journal of Traffic and Transportation Engineering, 7(2), 75-87.
[3] Kumar, A., & Soni, R. (2022). Artificial Intelligence in Transportation: Innovations and Practices. Elsevier.
[4] Zhao, H., Chen, M., & Zhang, L. (2019). Dynamic Pricing in Smart Tolling Systems: An AI-Based Approach. Transportation Research Part C: Emerging Technologies, 106, 35-50.
[5] Agarwal, A. V., & Kumar, S. (2017, October). Intelligent multi-level mechanism of secure data handling of vehicular information for post-accident protocols. In 2017 2nd International Conference on Communication and Electronics Systems (ICCES) (pp. 902-906). IEEE.
[6] Rajendran, R., & Iyer, P. (2021). Role of AI in Toll Collection Systems in Urban Areas. Urban Transport Journal, 14(1), 1-12..
[7] Liu, F., Zhan, Y., & Wei, X. (2020). Integration of AI-Powered Mobile Payment Systems for Toll Collection. IEEE Transactions on Intelligent Transportation Systems, 21(7), 2750-2760.
[8] Agarwal AV, Kumar S. Intelligent multi-level mechanism of secure data handling of vehicular information for post-accident protocols. In2017 2nd International Conference on Communication and Electronics Systems (ICCES) 2017 Oct 19 (pp. 902-906). IEEE.
[9] Yang, T., & Zhang, C. (2021). AI-Based Traffic Management Systems and Their Application in Tolling. Wiley & Sons.
[10] Nguyen, P., & Huynh, N. (2022). Privacy and Data Security in AI-Based Tolling Systems. Journal of Cyber Security Technology, 6(3), 200-214.
[11] Smith, J., Robinson, L., & Stevens, P. (2020). Cost-Effectiveness of Implementing AI in Transportation Infrastructure. Journal of Infrastructure and Transportation Economics, 18(4), 233-246.
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How to cite this paper
@article{1703187,
author = {Smart Dorcas},
title = {Smart Tolling through AI: Revolutionizing Payment Systems for Modern Transportation Networks},
journal = {Iconic Research And Engineering Journals},
year = {2022},
volume = {5},
number = {8},
pages = {359-363},
issn = {2456-8880},
url = {https://www.irejournals.com/formatedpaper/1703187.pdf},
abstract = {The rapid development of artificial intelligence is transforming industries across the world, including transportation. Smart tolling, powered by AI technologies, is emerging as a revolutionary approach to modernizing payment systems within transportation networks. Traditional toll collection systems, often characterized by inefficiency, long queues, and static pricing, are being replaced by intelligent systems that provide real-time, seamless, and adaptive solutions. The paper discusses the use of AI-driven technologies, such as machine learning algorithms, computer vision, and natural language processing, on tolling systems for some of the most common and persistent challenges in traffic congestion, revenue optimization, and user experience. AI-powered tolling systems use real-time data from various IoT devices like cameras, sensors, and RFID readers to enable automatic vehicle identification, dynamic pricing, and contactless payment. The machine learning models study the pattern of traffic flow to estimate peak hours and thus optimize the rates of tolls. In this way, it helps in reducing congestion and enhancing efficiency. Moreover, computer vision technologies, including license plate recognition and vehicle classification, help in managing tolls by reducing human interference and hence errors. These developments contribute to better traffic management, operational efficiency, and environmental sustainability by reducing emissions and fuel consumption that come with congestion. The paper also examines the potential challenges and ethical considerations of smart tolling systems. Issues such as data privacy, cybersecurity, and public acceptance are critical for widespread adoption. Transparent governance frameworks, stakeholder engagement, and robust data protection measures are essential to address these concerns. In general, intelligent tolling with the use of AI is a new paradigm in transportation infrastructure. Integration of intelligent systems into tolling processes could enable governments and private operators to efficiently manage road utilization, improve revenue collection, and ensure a user-friendly experience. This paper highlights technological innovations, benefits, and future prospects of AI-driven tolling, providing a comprehensive understanding of its transformative potential in modern transportation networks.},
keywords = {Smart Tolling, AI in Transportation, Intelligent Traffic Systems, Toll Collection Technology, AI-Powered Tolling, Autonomous Vehicles and Tolling, Electronic Toll Collection (ETC), Contactless Payment Systems, AI and Traffic Management, Real-Time Traffic Monitoring, Dynamic Pricing for Tolls, Smart Transportation Networks, Machine Learning in Tolling, Automated Toll Systems, Vehicle Recognition Technology, AI-Based Payment Systems, Digital Tolling Solutions, Traffic Flow Optimization, AI and Infrastructure, Transportation Network Innovation},
month = {February},
}