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1705481 Vol 7 · Issue 8 Download Paper

Assessing the Magnitude of Traffic Congestion Towards Planning for Building Smart City in Nigeria

Muhammad Sani Aliyu Hamza Hamza Musa Jibrin Abdullahi Mairiga Saleh Mamman Abdullahi Usman Hassan Ahmad

Subject area: Science,Engineering and Technology  ·  Area of research: Civil Engineering Technology

Abstract

As the economy grows and real income of household increases, vehicle population surges up, contributing to traffic congestion, particularly within cities. Given the critical importance of productivity on the Gross Domestic Product (GDP) growth, it is economically worthwhile, and of policy importance to recognize causes of congestion and their harmful effect. This study investigates the causes of traffic congestion, focusing on a selected road link (Karu-Keffi, Mararaba in Nasarawa State, Nigeria). Physical manual traffic survey was used to gather the data and Descriptive Statistics employed to analyze the data. The average traffic volume on the road was observed to be 4346veh/hr as compared to 2595 veh/hr (Model Road State (MRS) HCM 2000), signifying almost 170% increase. The average travel speed found to be 11kmph and the FFS of 45kmph, giving level of service (LOS) classification of F (signifying breakdown in the flow of traffic). The findings and recommendations herein will help to curb possible traffic congestion and ensure proper traffic management and control consistent with specifications for the smart city.

Keywords

Traffic Congestion, Smart City, Level of Service, Traffic Volume, Traffic Survey.

How to cite this paper

Muhammad Sani Aliyu, Hamza Hamza Musa, Jibrin Abdullahi Mairiga, Saleh Mamman Abdullahi, Usman Hassan Ahmad "Assessing the Magnitude of Traffic Congestion Towards Planning for Building Smart City in Nigeria" Iconic Research And Engineering Journals Volume 7 Issue 8 2024 Page 98-107
Muhammad Sani Aliyu, Hamza Hamza Musa, Jibrin Abdullahi Mairiga, Saleh Mamman Abdullahi, Usman Hassan Ahmad "Assessing the Magnitude of Traffic Congestion Towards Planning for Building Smart City in Nigeria" Iconic Research And Engineering Journals, vol. 7, no. 8, Feb. 2024
Muhammad Sani Aliyu, Hamza Hamza Musa, Jibrin Abdullahi Mairiga, Saleh Mamman Abdullahi, Usman Hassan Ahmad (2024). Assessing the Magnitude of Traffic Congestion Towards Planning for Building Smart City in Nigeria. Iconic Research And Engineering Journals, 7(8).
Muhammad Sani Aliyu, Hamza Hamza Musa, Jibrin Abdullahi Mairiga, Saleh Mamman Abdullahi, Usman Hassan Ahmad "Assessing the Magnitude of Traffic Congestion Towards Planning for Building Smart City in Nigeria" Iconic Research And Engineering Journals, vol. 7, no. 8, Feb. 2024.
@article{1705481,
      author = {Muhammad Sani Aliyu, Hamza Hamza Musa, Jibrin Abdullahi Mairiga, Saleh Mamman Abdullahi, Usman Hassan Ahmad},
      title = {Assessing the Magnitude of Traffic Congestion Towards Planning for Building Smart City in Nigeria},
      journal = {Iconic Research And Engineering Journals},
      year = {2024},
      volume = {7},
      number = {8},
      pages = {98-107},
      issn = {2456-8880},
      url = {https://www.irejournals.com/formatedpaper/1705481.pdf},
      abstract = {As the economy grows and real income of household increases, vehicle population surges up, contributing to traffic congestion, particularly within cities. Given the critical importance of productivity on the Gross Domestic Product (GDP) growth, it is economically worthwhile, and of policy importance to recognize causes of congestion and their harmful effect. This study investigates the causes of traffic congestion, focusing on a selected road link (Karu-Keffi, Mararaba in Nasarawa State, Nigeria). Physical manual traffic survey was used to gather the data and Descriptive Statistics employed to analyze the data. The average traffic volume on the road was observed to be 4346veh/hr as compared to 2595 veh/hr (Model Road State (MRS) HCM 2000), signifying almost 170% increase. The average travel speed found to be 11kmph and the FFS of 45kmph, giving level of service (LOS) classification of F (signifying breakdown in the flow of traffic). The findings and recommendations herein will help to curb possible traffic congestion and ensure proper traffic management and control consistent with specifications for the smart city.},
      keywords = {Traffic Congestion, Smart City, Level of Service, Traffic Volume, Traffic Survey.},
      month = {February},
  }