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Towards a Framework for Context-Aware Intelligent Transportation System: Case of Kigali

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ICT Systems and Sustainability

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 321))

Abstract

The intelligent transportation system (ITS) proved to be a cost-effective transportation solution. Artificial intelligence (AI), machine learning (ML) and the Internet of things (IoT) are supposed to take advantage of big data’s accessibility for successful data processing. Development of platforms compatible with innovative services will improve living standards. Research in the ITS field together with their deployment is focused on developed countries. It is important to explore the concept in developing countries. In this paper, a survey was conducted using a random sampling technique to obtain opinions, readiness for ITS, existing technologies and transportation applications. The analysis of the results showed that 73.78% are not familiar with ITS. An overview of the challenges for intelligent transport in the region with a specific focus on road safety is presented. An IoT-based conceptual framework is proposed to improve the transportation system specifically in Rwanda. This research contributes to raising awareness of the possibility of ITS.

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References

  1. United Nations. World Urbanization Prospects The 2014 Revision-Methodology, Online available: https://population.un.org/wup/Publications/Files/WUP2014-Methodology.pdf. Accessed on 20 April 2021

  2. Jonathan B, Sally M, Robert B, Laura W (2021) Housing need in Kigali - C-38406-RWA-1. Available online: https://theigc.org/wp-content/uploads/2019/07/Bower-et-al-2019-Final-report.pdf. Accessed on 2 Mar 2021

  3. Smart City Rwanda Masterplan. Online available: https://unhabitat.org/sites/default/files/documents/2019-05/rwanda_smart_city-master_plan.pdf Accessed on 15 Jan 2021

  4. Bagloee SA, Tavana M, Asadi M, Oliver T (2016) Autonomous vehicles: challenges, opportunities, and future implications for transportation policies. J Modern Transp 24(4): 284–303. https://doi.org/10.1007/s40534-016-0117-3

  5. Fagnant DJ, Kockelman K (2015) Preparing a nation for autonomous vehicles: opportunities, barriers and policy recommendations. Transp Res Part A: Policy Pract 77: 167–181. https://doi.org/10.1016/j.tra.2015.04.003

  6. Habib S, Khan MM, Abbas F, Sang L, Shahid MU, Tang H (2018) A comprehensive study of implemented international standards, technical challenges, impacts and prospects for electric vehicles. IEEE Access 6: 13866–13890. https://doi.org/10.1109/ACCESS.2018.2812303

  7. Tintelecan A, Dobra AC, Marţiş C (2019) LCA indicators in electric vehicles environmental impact assessment. In: 2019 Electric Vehicles International Conference (EV), pp 1–5. https://doi.org/10.1109/EV.2019.8892893

  8. Huang W, Li P, Zhang T (2018) RSUs placement based on vehicular social mobility in VANETs. In: 2018 13th IEEE Conference on Industrial Electronics and Applications (ICIEA), pp 1255–1260. IEEE. https://doi.org/10.1109/ICIEA.2018.8397902

  9. Mousavi SS, Schukat M, Howley E (2017) Traffic light control using deep policy-gradient and value-function-based reinforcement learning. IET Intelligent Transp Syst 11(7): 417–423. https://doi.org/10.1049/iet-its.2017.0153

  10. Pang J, Huang J, Du Y, Yu H, Huang Q, Yin B (2018) Learning to predict bus arrival time from heterogeneous measurements via recurrent neural network. IEEE Trans Intelligent Transp Syst 20(9): 3283–3293. https://doi.org/10.1109/TITS.2018.2873747

  11. Lv Y, Duan Y, Kang W, Li Z, Wang FY (2014) Traffic flow prediction with big data: a deep learning approach. IEEE Trans Intelligent Transp Syst 16(2):865–873. https://doi.org/10.1109/TITS.2014.2345663

  12. Lozano Dominguez JM, Mateo Sanguino TJ (2019) Review on V2X, I2X, and P2X communications and their applications: a comprehensive analysis over time. Sensors 19(12):2756. https://doi.org/10.3390/s19122756

  13. Shi Y, Cui L, Qi Z, Meng F, Chen Z (2016) Automatic road crack detection using random structured forests. IEEE Trans Intelligent Transp Syst 17(12):3434–3445. https://doi.org/10.1109/TITS.2016.2552248

  14. Nyamawe AS, Mbosso EC (2014) Road safety: adoption of ICT for tracking vehicles’ over-speeding in Tanzania. Int J Comput Appl 96(16): 12–15. https://doi.org/10.5120/16877-6876

  15. Pawłowicz B, Salach M, Trybus B (2019) Infrastructure of RFID-based smart city traffic control system. In: Conference on automation. Springer, Cham, pp 186–198. https://doi.org/10.1007/978-3-030-13273-6_19

  16. Byshov N, Simdiankin A, Uspensky I (2017) Method of traffic safety enhancement with use of RFID technologies and its implementation. Transp Res Proc 20: 107–111. https://doi.org/10.1016/j.trpro.2017.01.030

  17. United Nations (UN) (2020) The 2030 Agenda for Sustainable Development. Online available: https://ec.europa.eu/environment/sustainable-development/SDGs/index_en.htm. Accessed on 19 Dec 2020

  18. David S, Bill E, Tim L (2021) Urban Mobility Report 2019. Available online: https://mobility.tamu.edu/umr/report/. Accessed on 21 Mar 2021

  19. World Road Association (2020) Road safety manual: a manual for practitioners and decision-makers on implementing safe system infrastructure. Paris; 2015. Online Available: https://roadsafety.piarc.org/en. Accessed on 27 Dec 2020

  20. Global Plan for the Decade of Action for Road Safety 2011-2020. Online available: https://www.who.int/roadsafety/decade_of_action/plan/global_plan_decade.pdf. Accessed on 25 May 2020

  21. Mihyeon Jeon C, Amekudzi A (2005) Addressing sustainability in transportation systems: definitions, indicators, and metrics. J Infrastructure Syst 11(1):31–50

    Google Scholar 

  22. Ministry of Infrastructure. Transport Sector Strategic Plan for the National Strategy for Transformation (NST1). Online available: https://www.mininfra.gov.rw/index.php?id=transportstrategicplan. Accessed on 05 May 2021

  23. Government of Rwanda. Smart Rwanda Master Plan. Available online: http://minict.gov.rw/fileadmin/Documents/Strategy/SMART_RWANDA_MASTER_PLAN_FINAL.pdf (accessed on 10 October 2020)

  24. National ICT Strategy and Plan, NICI-2015. http://www.rdb.rw/uploads/tx_sbdownloader/NICI_III.pdf (accessed on 2 February 2021)

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Acknowledgements

This study was funded by the African Center of Excellence in Internet of Things established at College of Science and Technology, University of Rwanda.

Author information

Authors and Affiliations

  1. African Center of Excellence in Internet of Things, College of Science and Technology, University of Rwanda, Kigali, Rwanda

    Gatera Antoine & Andras Valko

  2. Department of Physics, University of Malawi, Zomba, Malawi

    Chomora Mikeka

  3. Department of Computer and Software Engineering, College of Science and Technology, University of Rwanda, Kigali, Rwanda

    Gaurav Bajpai

  4. Department of Information Technology, SRM Institute of Science and Technology, Chennai, 603203, India

    Kayalvizhi Jayavel

Authors
  1. Gatera Antoine
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  2. Chomora Mikeka
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  3. Gaurav Bajpai
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  4. Andras Valko
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  5. Kayalvizhi Jayavel
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Editor information

Editors and Affiliations

  1. Singidunum University, Belgrade, Serbia

    Milan Tuba

  2. ITM University, Gwalior, Madhya Pradesh, India

    Shyam Akashe

  3. Global Knowledge Research Foundation, Ahmedabad, Gujarat, India

    Amit Joshi

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© 2022 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

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Antoine, G., Mikeka, C., Bajpai, G., Valko, A., Jayavel, K. (2022). Towards a Framework for Context-Aware Intelligent Transportation System: Case of Kigali. In: Tuba, M., Akashe, S., Joshi, A. (eds) ICT Systems and Sustainability. Lecture Notes in Networks and Systems, vol 321. Springer, Singapore. https://doi.org/10.1007/978-981-16-5987-4_60

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