Integration of Advanced Sensors in Smart Transportation Systems: Enhancing Efficiency and Safety
Keywords:
Advanced Sensors, Smart Transportation Systems, wireless sensors and Vehicle Ad- hoc Networks (VANETs), traffic jams and safety concernsAbstract
The article examines how Smart Transportation Systems (STS) might revolutionize transportation, using Nigeria as a case study. It addresses worldwide urban transportation obstacles, such as traffic jams and safety concerns, and presents STS as a workable solution, outlining its main features and advantages. The study explores the classification of sensors in STS, including vehicle-based, traffic control, and supporting technologies, and clarifies how they contribute to traffic management, driving assistance, and safety improvements. The research delves into communication protocols as well, with a focus on wireless sensors and Vehicle Ad-hoc Networks (VANETs), which provide real-time data sharing between cars and infrastructure for enhanced traffic updates, route optimization, and safety precautions. The report highlights Nigeria's efforts and emphasizes the potential advantages of universal adoption, while admitting the limited implementation of STS in poor nations. In order to fully realize the advantages of STS in enhancing urban life and transportation systems, not just in Nigeria but also worldwide, it finishes by highlighting the need for ongoing research, legislative frameworks, and infrastructure investment.
References
. Sutar, S. H., Koul, R., & Suryavanshi, R. (2016). Integration of smart phone and IOT for development of smart public transportation system. International Conference on Internet of Things and Applications (IOTA) Maharashtra Institute of Technology, Pune, India.
. Guerrero-Ibanez, J., Zeadally, S., & Contreras-Castillo, J. (2018). Sensor technologies for intelligent transportation systems. Sensors, 18, 1212; doi: 10.3390/s18041212.
. Orie, C. J. (2022). Sensor technologies perception for intelligent vehicle movement systems on Nigeria road network. THE COLLOQUIUM, 10(1), 194-208.
. Qureshi, K. N., & Abdullah, A. H. (2013). A survey on intelligent transportation systems. Middle-East Journal of Scientific Research, 15 (5), 629-642. DOI: 10.5829/idosi.mejsr.2013.15.5.11215.
. Sriratnasari, S. R., Wang, G., Kaburuan, E., & Jayadi, R. (2019). Integrated smart transportation using IoT at DKI Jakarta. International Conference on Information Management and Technology, Singapore.
. Ajayi, O., Bagula, A., Isafiade, O., & Noutouglo, A. (2019) Effective management of delays at road intersections using smart traffic light system. Proceedings of the International Conference on e-Infrastructure and e-Services for Developing Countries, Porto-Novo, Benin, Springer: Cham, Switzerland, pp. 84–103.
. Bagula, A., Castelli, L., & Zennaro, M. (2015). On the design of smart parking networks in the smart cities: An optimal sensor placement model. Sensors, 15, 15443–15467.
. Maan, N. (2020). Sensors for onboard diagnostics and emissions monitoring. Retrieved from https://www.linkedin.com/pulse/sensors-onboard-diagnostic-emissions-monitoring-nakul-maan.
. Liu, K., Son, S.H., Lee, V.C.S., & Kapitanova, K. (2011). A token-based admission control and request scheduling in lane reservation systems. Proceedings of the 14th International IEEE Conference on Intelligent Transportation Systems (ITSC), Washington, DC, USA, 5–7, pp. 1489–1494.
. Wu, Y., Dai, H. N., Wang, H. (2021). A survey of intelligent network slicing management for industrial IoT: Integrated approaches for smart transportation, smart energy, and smart factory. IEEE Communications Surveys and Tutorials, 1-35.
. Akhlaq, M., Sheltami, T. R., Helgeson, B., & Shakshuki, E. M. (2012). Designing an integrated driver assistance system using image sensors. Journal of Intelligent Manufacturing, 23, 2109-2132.
. Ullo, S. L., & Sinha, G. R. (2020). Advances in smart environment monitoring systems using IoT and sensors. Sensors, 20(11), 3113.
. Bugdol, M., Segiet, Z., Krecichwost, M., & Miodonska, Z. E. (2014). Vehicle detection system using magnetic sensors. Transport Problems, 9(1), 49-60.
. Thakur, R. (2018). Infrared sensors for autonomous vehicles. IntechOpen, 81-96. https://dx.doi.org/10.5772/intechopen.70577.
. Shiv, H., Koul, R., & Suryavanshi, R. (2016). Integration of smart phone and IOT for development of smart public transportation system. International Conference on Internet of Things and Applications (IOTA) Maharashtra Institute of Technology, Pune, India, 73- 78.
. Wang, G., Zhao, Y., Huang, J., & Wu, Y. (2018). “An effective approach to controller placement in software defined wide area networks,” IEEE Transactions on Network and Service Management, 15(1). 344–355.
. Miao, W., G. Min, G., Wu, Y., Wang, H., & Hu, J. (2016). “Performance modelling and analysis of software-defined networking under bursty multimedia traffic,” ACM Transportation Multimedia Computer Communication Application, 12(5). 2016. https://doi.org/10.1145/2983637.
. Li, L., Chou, W., Zhou, W., & Luo, M. (2016). “Design patterns and extensibility of REST API for networking applications,” IEEE Transactions on Network and Service Management, 13(1), 154–167.
. Qi, S., Kulkarni, S. G., & Ramakrishnan, K. K. (2020). “Assessing container network interface plugins: Functionality, performance, and scalability.” IEEE Transactions on Network and Service Management, 1–15.
. Azizian, M., Cherkaoui, S., & Hafid, A. S. (2017). Vehicle software updates distribution with SDN and cloud computing. IEEE Communications Magazine, 74-79.
. Liu, S., Liu, L., Tang, J., Yu, B., Wang, Y., Shi, W. (2019). Edge computing for autonomous driving: Opportunities and challenges. Proceedings of the IEEE, 107(8), 1697-1716.
. Aamir, M., Masroor, S., Ali, Z.A., & Ting, B.T. (2019). Sustainable framework for smart transportation system: A case study of karachi. Wirel. Pers. Commun, 106, 27–40.
. Tubaishat, M., Zhuang, P., Qi, Q., & Shang, Y. (2009). Wireless sensor networks in intelligent transportation systems. Wireless Communications and Mobile Computing, 9(3), 287–302.
. Mukhtar, A., Xia, L., & Tang, T.B. (2015). Vehicle detection techniques for collision avoidance systems: A review. IEEE Transactions on Intelligent Transportation System,16(5), 2318– 2338.
. Chang, I. C., Tai, H. T., Yeh, F. H., Hsieh, D. L., & Chang, S. H. (2013). A vanet-based a route planning algorithm for travelling time-and energy-efficient gps navigation applications. International Journal of Distributive Sensors and Network, 9, 794521.
. Dressler, F., Hartenstein, H., Altintas, O., & Tonguz, O. K. (2014). “Inter-vehicle communication: Quo vadis”. IEEE Communications Magazine, 52(6), 170-177.
. Ahmad, K., Khujamatov, H., Lazarev, A., Usmanova, N., Alduailij, M., & Alduailij, M. (2023). Internet of things-aided intelligent transport systems in smart cities: Challenges, opportunities and future. Wireless Communications and Mobile Computing, 1-32. https://doi.org/10.1155/2023/7989079.
. Chen, C., Liu, B., Wan, S., Qiao, P., & Pei, Q. (2020). An edge traffic flow detection scheme based on deep learning in an intelligent transportation system. IEEE Transactions on Intelligent Transportation Systems, 22(3), 1840-1852.
. Kaffash, S., Nguyen, A. T., & Zhu, J. (2021). Big data algorithms and applications in intelligent transportation system: A review and bibliometric analysis. International Journal of Production Economics, 231, 107868.
. Bakare, B. I., Orike, S., & Urama, M. O. (2022). Development of safe road management system in Nigeria using data fusion and internet of things. Journal of Electronics and Communication Engineering Research, 8(6), 08-17.
. Okafor, C. C., Aigbavboa, C., & Thwala, W. D. (2021). A delphi approach to evaluating the success factors for the application of smart mobility systems in smart cities: A construction industry perspective. International Journal of Construction Management, 1- 10. DOI: 10.1080/15623599.2021.1968567.
. Olusanya, G. S., Eze, M. O., Ebiesuwa, O., & Okunbor, C. (2020). Smart transportation system for solving urban traffic congestion. Review of Computer Engineering Studies, 7(3), 55- 59.
. Ashidi, A. G., Obagade, T. A., & Orokhe, J. E. (2019). Automated vehicle toll system for smart transportation management and operations. I-manager’s Journal on Instrumentation & Control Engineering, 7(1), 1-8.
. Muthuramalingam, S., Bharathi, A., Kumar, S. R., Gayathri, N., Sathiyaraj, R., & Balamurugan,
. B. (20219). Internet of things and big data analytics for smart generation. Intelligent Systems Reference Library 154, https://doi.org/10.1007/978-3-030-04203-5_13.
. Elgazzar, K., Khalil, H., Alghamdi, T., Badr, A., Abdelkader, G., Elewah, A., & Buyya, R. (2022, November 21). Revisiting the internet of things: New trends, opportunities and grand challenges. https://doi.org/10.3389/friot.2022.1073780
. Zhang, Y., Ili?, M., & Bogenberger, K. (2023, January 1). Autonomous Vehicles as a Sensor: Simulating Data Collection Process. https://doi.org/10.48550/arXiv.2308.
. Yang, T., & Lv, C. (2022, November 15). A Secure Sensor Fusion Framework for Connected and Automated Vehicles Under Sensor Attacks. https://doi.org/10.1109/jiot.2021.3101502
. Palácio, C., & Gamess, E. (2021, April 15). Toward a collision avoidance system based on the integration of technologies. https://doi.org/10.1145/3409334.3452084
. Liu, S., Bo, Y., Tang, J., & Zhu, Q. (2021, December 5). Invited: Towards Fully Intelligent Transportation through Infrastructure-Vehicle Cooperative Autonomous Driving: Challenges and Opportunities. https://doi.org/10.1109/dac18074.2021.9586317
. Zi?bi?ski, A., Cupek, R., Erdogan, H., & Waechter, S. (2016, January 1). A Survey of ADAS Technologies for the Future Perspective of Sensor Fusion. Springer Science+Business Media, 135-146. https://doi.org/10.1007/978-3-319-45246-3_13
. Zhao, L., & Jia, Y. (2021, January 6). Intelligent transportation system for sustainable environment in smart cities. https://journals.sagepub.com/doi/10.1177/0020720920983503
. Ibáñez, J A G., Zeadally, S., & Contreras?Castillo, J. (2018, April 16). Sensor Technologies for Intelligent Transportation Systems. Multidisciplinary Digital Publishing Institute, 18(4), 1212-1212. https://doi.org/10.3390/s18041212
. Kloeker, L., Joeken, G., & Eckstein, L. (2023, September 24). Economic Analysis of Smart Roadside Infrastructure Sensors for Connected and Automated Mobility. https://doi.org/10.1109/itsc57777.2023.10422500
. Elias, J R., Chard, R., Levental, M., Liu, Z., Foster, I., & Chaudhuri, S. (2022, January 1). Real-Time Streaming and Event-driven Control of Scientific Experiments. https://doi.org/10.48550/arXiv.2205.
. Nie, T., Qin, G., Wang, Y., & Sun, J. (2023, March 9). Towards better traffic underdetermined and non-equilibrium problems via a correlation-adaptive graph convolution network. https://export.arxiv.org/pdf/2303.05660v2.pdf
. Jolfaei, A., Menon, V G., Lv, C., Bashir, A K., Tan, Y K., & Kant, K. (2021, July 15). Guest Editorial Advanced Sensing and Sensor Fusion for Intelligent Transportation Systems. https://doi.org/10.1109/jsen.2021.3081195
. Abdelkader, G., Elgazzar, K., & Khamis, A. (2021, November 19). Connected Vehicles: Technology Review, State of the Art, Challenges and Opportunities. https://doi.org/10.3390/s21227712
. Abdulkadir A. Adamu, A. A., Wang, D., Salau, A. O., & Ajayi, O. (2020). An integrated IoT system pathway for smart cities. International Journal on Emerging Technologies, 11(1), 01-09.
. Arif, M., Wang, G., Geman, O., Balas, V E., Peng, T., Brezulianu, A., & Chen, J. (2020, May 5). SDN-based VANETs, Security Attacks, Applications, and Challenges. https://doi.org/10.3390/app10093217
. Ajayi, O. O., Bagula, A. B., Maluleke, H. C., & Odun-Ayo, I. A. (2021). Transportation inequalities and adoption of intelligent transportation systems in Africa: A research landscape. Sustainability, 13, 12891. https://doi.org/ 10.3390/su132212891.
. Akhlaq, M., Sheltami, T. R., Helgeson, B., & Shakshuki, E. M. (2012). Designing an integrated driver assistance system using image sensors. Journal of Intelligent Manufacturing, 23, 2109-2132.
. Calafate, C. T., Soler, D., Cano, J., & Manzoni, P. (201). Traffic management as a service: The traffic flow pattern classification problem. Open Access. https://doi.org/10.1155/2015/716598.
. Dutta, A., Jain, M., Khan, A O., & Sathanur, A V. (2023, January 1). Deep Reinforcement Learning to Maximize Arterial Usage during Extreme Congestion. https://doi.org/10.48550/arxiv.2305.09600
. Kumar, N., & Raubal, M. (2021, December 1). Applications of deep learning in congestion detection, prediction and alleviation: A survey. https://doi.org/10.1016/j.trc.2021.103432
. Rezaei, M., Azarmi, M., & Mir, F M P. (2022, January 1). Traffic-Net: 3d Traffic Monitoring Using a Single Camera. RELX Group (Netherlands). https://doi.org/10.2139/ssrn.4152596
. Shima, N., Honda, K. F., Nakamura, R., Babasaki, M., & Higuchi, T. (2001). Fusion sensor for driving assistance system. Fujitsu Ten Tench, 17.
. Traffic Management. (2022, September 1). https://www.yunextraffic.com/portfolio/traffic-management/
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