Modeling of Motorists’ reactions on the use of Second Niger Bridge in Southern Part of Nigeria
DOI:
https://doi.org/10.54536/ajise.v5i2.7214Keywords:
Driving Behaviour, Motorist, Response Surface Methodology, Second Niger Bridge, Traffic flowAbstract
This study analyzed motorists’ reactions to the use of the Second Niger Bridge. It focused on safety perceptions, driving behavior, and traffic flow dynamics. Data were collected through field observations during peak and off-peak hours. Surveys were distributed to motorists using the bridge, either directly or through online platforms. Experimental data were also collected by observing driver responses. Data analysis used Response Surface Methodology (RSM) to model relationships between independent variables (e.g., expansion joint condition, corrosion level, traffic density) and dependent variables (e.g., motorist reactions, traffic flow). Results showed that most users perceive safety risks due to visible deterioration, insufficient safety features, and poor maintenance. Regarding travel time, 58% acknowledged a significant reduction due to the bridge. Improving expansion joints will also help achieve fuel savings, as 78% of users reported. Motorists adapt by reducing speed, changing lanes, and avoiding damaged sections. However, this behavior results in increased travel time, higher fuel consumption, and traffic inefficiency. 81% believe that accident risk rises during congestion, and 51% believe traffic improves when the bridge is in good condition. The study concludes that the bridge is crucial for regional transport. Still, its current state undermines safety, efficiency, and public confidence. Stronger maintenance policies, better safety features, and improved user engagement are essential for sustainability. The peak of the curve, located at a deviation of 0.000, signifies the highest design precision at that specific set of factor levels.
Downloads
References
AKM, A., Anwarul Islam, Frank Li, Hiwa Hamid, & Amer Jaroo. (2014). Bridge condition assessment and load rating using dynamic response. Youngstown State University.
Alfredo Camara, & Constantino Carlos Reyes-Aldasoro. (2024). Dynamic analysis of the effects of vehicle movement over bridges observed with CCTV images. Engineering Structures, 317, 118653. https://doi.org/10.1016/j.engstruct.2024.118653
E. I. Ogunjiofor, & F. O. Ayodele. (2023). Utilization of response surface methodology in optimization of locally sourced aggregates. Journal of Asian Scientific Research, 13(1), 54–67. https://doi.org/10.55493/5003.v13i1.4771
E. I. Ogunjiofor, N. G. Okoye, & I. E. Ezeonyi. (2023). Analysis of safety behaviour of workers under small-scale construction site: A case study of Anambra State. American Journal of Interdisciplinary Research and Innovation (AJIRI), 2(2), 44–50.
Emmanuel Ogunjiofor, & Ikechukwu Umeonyiagu. (2025). Use of PBridge for analysis and design of single span prestressed concrete bridge subjected to wind and thermal loads. World Journal of Advanced Engineering Technology and Sciences, 15(3), 27–38. https://doi.org/10.30574/wjaets.2025.15.3.0862
Emmanuel Ogunjiofor, Ikechukwu Umeonyiagu, & Emmanuel Uzuh. (2025). Analysis and design of wind and temperature load of a continuous span I-beam prestressed concrete bridge using PBridge software. International Journal of Engineering Research & Technology (IJERT), 14(5). Available from IJERT
Enemchukwu Nnaemeka, & Isaac Adelekun. (2023). The Niger Bridge and the Biafran economy during and after the Nigerian-Biafran war, 1967–1970. Mediterranean Journal of Social Sciences, 14(5), 49. https://doi.org/10.36941/mjss-2023-0031
G. Koch, M. P. H. Brongers, N. G. Thompson, Y. P. Virmani, & J. H. Payer. (2002). Corrosion cost and preventive strategies in the United States (Report No. FHWA-RD-01-156). Federal Highway Administration.
Jean-Charles Wyss, Di Su, & Yozo Fujino. (2011). Prediction of vehicle-induced local responses and application to a skewed girder bridge. Engineering Structures, 33(4), 1088–1097. https://doi.org/10.1016/j.engstruct.2010.12.020
M. Kohm, L. Stempniewski, & A. Stark. (2023). Influence of vehicle traffic on modal-based bridge monitoring. Journal of Civil Structural Health Monitoring, 13, 219–234. https://doi.org/10.1007/s13349-022-00630-z
R. H. Myers, D. C. Montgomery, & C. M. Anderson-Cook. (2016). Response surface methodology: Process and product optimization using designed experiments (4th ed.). Wiley.
Sang-Hyo Kim, Yong-Seon Lee, & Kwang-Yil Cho. (2005). Analysis of horizontal reactions due to moving vehicle loads in curved bridges with varied support conditions. Advances in Structural Engineering, 8(5), 529–545. https://doi.org/10.1260/136943305774858025
W. C. Anene, A. C. Okigbo, & P. E. Ubah. (2023). Assessment of causes and design solution to road traffic accident along Onitsha–Owerri Expressway in Eastern Nigeria. American Journal of Innovation in Science and Engineering (AJISE), 2(1), 17–24. https://doi.org/10.54536/ajise.v2i1.1237
W. C. Anene, M. O. Onuigbo, & J. C. Okeke. (2023). Analysis and remedy to avert traffic congestion at Eke-Nibo Junction, Awka South L.G.A, Anambra State, Nigeria. Trends in Transport Engineering and Applications, 10(2).
W. C. Anene, P. T. Agudosi, & E. I. Ogunjiofor. (2022). Design of traffic signal control system at Orlu Junction, Ihiala, Anambra State, Nigeria. International Journal of Transportation Engineering and Traffic System, 8(2), 38–49. https://doi.org/10.37628/IJTETS
W. C. Anene. (2022). Investigation into the understanding of traffic signs, symbols and safety rules among drivers in Southern Nigeria. Journal of Engineering Research and Reports, 23(5), 41–58.
Yangbo Chen, Maria Feng, & Chin An Tan. (2009). Bridge structural condition assessment based on vibration and traffic monitoring. Journal of Engineering Mechanics, 135(8), 747–758. https://doi.org/10.1061/(ASCE)0733-9399(2009)135:8(747)
Downloads
Published
Issue
Section
License
Copyright (c) 2026 Anene W. C., Ogunjiofor E. I., Udekwe I. C.; Ejike, E. C.; Clement, A. F., Amadi, E. C., Ikeorizu, C. C.
This work is licensed under a Creative Commons Attribution 4.0 International License.
