A Comprehensive Review on Enhancing Urban Efficiency in Klang Valley through Smart Sensor-Based Road Management

A Comprehensive Review on Enhancing Urban Efficiency in Klang Valley through Smart Sensor-Based Road Management


  • Ahgalya Subbiah Faculty of Information Science and Engineering, Management and Science University, Shah Alam, Selangor
  • Darren Darshan Faculty of Information Science and Engineering, Management and Science University, Shah Alam, Selangor
  • Asma Mahfoud Faculty of Information Science and Engineering, Management and Science University, Shah Alam, Selangor
  • Rizati Hamidu Malaysian Institute of Road Safety Research (MIROS), Selangor, Malaysia




Urban Road Management, Road Banning System, Road Banning, Freight Transportation, Traffic Flow, Smart Sensor Devices


Optimal urban road management is essential for city governance, yet the deficiencies in existing road banning systems have given rise to a host of issues that pose threats to the overall functionality and safety of urban road networks. These problems manifest as extended queues on crowded roads and an increase in accidents, primarily due to the disorderly parking of freight transports. Despite legislative efforts, urban cities still grapple with persistent challenges, hindering traffic flow and jeopardizing public safety. There’s a need for a detailed analysis on the key issues among freight drivers and the effectiveness of phase-out terms in improving the banning system. To address this matter, the paper thoroughly examines information from the most recent literature review. This study is also supported by the transport system authorities as well as road safety experts at the Malaysian Institute of Road Safety Research (MIROS), and public perspectives from netizens. The study focuses on issues with the temporary road banning systems, particularly in the Klang Valley area specified by the Kuala Lumpur Municipality Department (DBKL). Its goal is to reveal insights into current inefficiencies in road management and propose innovative solutions. Additionally, these findings will be used to create smart sensor devices, which have the potential to transform on how urban road traffic bans can be managed. Once in place, these devices are expected to provide data-driven solutions for developing smarter cities.


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buah kenderaan berat di saman dalam tindakan khas laluan waktu terhad, Portal Rasmi Dewan Bandaraya Kuala Lumpur. Retrieved October 15, 2023, from https://www.dbkl.gov.my/8-buah-kenderaan-berat-di-saman-dalam-tindakan-khas-laluan-waktu-terhad

Ameli, M., Lebacque, J., & Leclercq, L. (2020). Improving traffic network performance with road banning strategy: A simulation approach comparing user equilibrium and system optimum. Simul. Model. Pract. Theory, 99. https://doi.org/10.1016/j.simpat.2019.101995

Attalla, S. M.., Mohan, D.., Mohammed, J.., Ruhi, S.., Ashok Kumar, K.., Jeppu, A. K.., & Hanafy, N. A. (2021). Descriptive study of the stress level and stressors among medical cluster students during Covid-19 pandemic. Journal of Management &Science, 19(2), 8. https://doi.org/10.57002/jms.v19i2.229

Azhar, D., Mendes. E., and Riddle, P. (2012, September 21). A systematic review of web resource estimation. (PROMISE '12): 8th International Conference on Predictive Models in Software Engineering Association for Computing Machinery. ACM. https://doi.org/10.1145/2365324.2365332

El Ouadi J, Errousso H, Benhadou S. (2022). On understanding the impacts of shared public transportation on urban traffic and road safety using an agent-based simulation with heterogeneous fleets: A case study of Casablanca city. Quality and Quantity, 56(6).

Gao, K., Han, F., Dong, P., Xiong, N., & Du, R. (2019). Connected vehicle as a mobile sensor for real time queue length at signalized intersections. Sensors (Switzerland), 19(9). https://doi.org/10.3390/s19092059

Gent, H., & Rietveld, P. (1993). Road transport and the environment in Europe. Science of The Total Environment, 129, 205-218. https://doi.org/10.1016/0048-9697(93)90171-2.

Jahangiri, A., H. A. Rakha, and T. A. Dingus (2015, September 9). Adopting machine learning methods to predict red-light running violations. IEEE 18th International Conference on Intelligent Transportation Systems. IEEE Xplore. https://doi.org/10.1109/itsc.2015.112

Key World Energy Statistics 2020 – Analysis - IEA. (n.d.). IEA.https://www.iea.org/reports/key-world-energy-statistics-2020

Křivda, V., Petrů, J., Macha, D., Plocova, K., & Fibich, D. (2020). An analysis of traffic conflicts as a tool for sustainable road transport. Sustainability, 12, 7198. https://doi.org/10.3390/su12177198.

Kuatkuasa Larangan (2023, October 20). https://www.dbkl.gov.my/kuatkuasakan-laranganx

Kujawski A, Nürnberg M. (2023). Analysis of the potential use of unmanned aerial vehicles and image processing methods to support road and parking space management in urban transport. Sustainability (Switzerland), 15(4).

Martins-Turner, K., Grahle, A., Nagel, K., & Göhlich, D. (2020). Electrification of urban freight transport - A case study of the food retailing industry. Procedia Computer Science, 170, 757–763. https://doi.org/10.1016/j.procs.2020.03.159K.

Moufad, I. & Fouad, J. (2019). A study framework for assessing the performance of the urban freight transport based on PLS approach. Archives of Transport, 49(1), 69–85. https://doi.org/10.5604/01.3001.0013.2777.

Pani, A., Prasanta. K. S., & Furqan. A. B. (2021). Assessing the spatial transferability of freight (Trip) generation models across and within States of India: Empirical evidence and implications for benefit transfer. Networks and Spatial Economics, 21(2), 465–493. https://doi.org/10.1007/s11067-021-09530-z.

Prabha, C., Sunitha, R., & Anitha, R. (2014). Automatic vehicle accident detection and messaging system using GSM and GPS modem. International Journal of Advanced Research in Electrical, Electronics and Instrumentation Energy, 3(7), 10723–10727. https://doi.org/10.15662/ijareeie.2014.0307062

Rivera, N. (2021). Air quality warnings and temporary driving bans: Evidence from air pollution, car trips, and mass-transit ridership in Santiago. Journal of Environmental Economics and Management. https://doi.org/10.1016/J.JEEM.2021.102454.

Sahu, P. K, Agnivesh P., & Georgina S. (2022). Freight traffic impacts and logistics inefficiencies in India: Policy interventions and solution concepts for sustainable city logistics. Transportation in Developing Economies, 8(2). https://doi.org/10.1007/s40890-022-00161-8

Sumalee, A., & Ho, H. (2018b). Smarter and more connected: Future intelligent transportation system. IATSS Research, 42(2), 67–71. https://doi.org/10.1016/j.iatssr.2018.05.

Sundralingam, S., Maryam, Y. N., Aza, A. M. K., Shalome, D., Shanmugapriya, N. K., & Angeshwaran P. (2023). Board governance characteristics and corporate sustainability in Malaysia: A conceptual framework. Journal of Management & Science, 21(1). https://doi.org/10.57002/jms.v21i1.177

Trecozzi, M. R., Iiritano, G., & Petrungaro, G. (2022). Liveability and freight transport in urban areas: the example of the Calabria Region for City Logistics. Transportation Research Procedia, 60, 116–123. https://doi.org/10.1016/j.trpro.2021.12.016

Wu, Y., Wang, R., Zhou, Y., Lin, B., Fu, L., He, K., & Hao, J. (2010). On-Road vehicle emission control in Beijing: Past, present, and future. Environmental Science & Technology, 45(1), 147–153. https://doi.org/10.1021/es1014289

Zhankaziev, S., Gavrilyuk, M., Morozov, D., & Zabudsky, A. (2018). Scientific and methodological approaches to the development of a feasibility study for intelligent transportation systems. Transportation Research Procedia, 36, 841–847. https://doi.org/10.1016/j.trpro.2018.12.068




How to Cite

Subbiah, A., Darshan, D., Mahfoud, A., & Hamidu, R. (2024). A Comprehensive Review on Enhancing Urban Efficiency in Klang Valley through Smart Sensor-Based Road Management . Journal of Computing Research and Innovation, 9(1), 16–30. https://doi.org/10.24191/jcrinn.v9i1.390



General Computing