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Spatial Heterogeneity and Highway-Specific Traffic Demand Modelling in South-Eastern Nigeria: Evidence from Five Inter-State Highways
Subject area: Science,Engineering and Technology · Area of research: Traffic, Modelling
Abstract
Reliable understanding of spatial differences in highway traffic demand is essential for highway planning, pavement management, infrastructure investment, and transport-system development, particularly where traffic-count observations are geographically limited. This research investigates spatial heterogeneity in annual average daily traffic (AADT) and develops highway-specific traffic-demand models for five major inter-state highways in South-Eastern Nigeria: Umuahia-Ikot Ekpene, Onitsha-Owerri, Abakaliki-Ogoja, Enugu-Port Harcourt, and Owerri-Port Harcourt. A longitudinal dataset of 100 highway-year observations spanning 2001 to 2020 was analyzed using descriptive spatial profiling, highway-level variation measures, group-difference testing, pooled highway-effects regression, highway-specific log-linear regression, and interaction modelling. The results reveal substantial spatial heterogeneity. Mean AADT ranged from 588,709 PCU/day on Abakaliki-Ogoja to 2,202,095 PCU/day on Enugu-Port Harcourt, and highway differences accounted for approximately 82.6% of the unadjusted variation in AADT. The highway-specific models also differed markedly in explanatory structure. Passenger population density was particularly influential on Umuahia-Ikot Ekpene and Abakaliki-Ogoja, whereas GDP showed the strongest statistically significant association on Enugu-Port Harcourt. A pooled interaction model confirmed that the relationships between population density, GDP, and AADT varied significantly across highways (robust Wald χ² = 34.88, p < 0.001), providing evidence of spatially non-stationary traffic-demand relationships. These findings demonstrate that a single regional traffic-demand equation may conceal important highway-specific differences. Inter-state highway planning in South-Eastern Nigeria should therefore account for spatially differentiated demand structures. The study offers an empirical basis for more targeted highway planning, pavement management, and investment prioritization in comparable data-constrained contexts.
Keywords
annual average daily traffic, interstate highways, spatial heterogeneity, South-Eastern Nigeria, traffic-demand modelling
How to cite this paper
@article{1724960,
author = {Henry Kene Ugwuanyi, Ifeoma Mariagoretti Jideofor, Ibe Iro Uzoma, Innocent Ije, Ugwuanyi, Gloria Nkechi},
title = {Spatial Heterogeneity and Highway-Specific Traffic Demand Modelling in South-Eastern Nigeria: Evidence from Five Inter-State Highways},
journal = {Iconic Research And Engineering Journals},
year = {2026},
volume = {10},
number = {5},
pages = {2142-2156},
issn = {2456-8880},
url = {https://www.irejournals.com/formatedpaper/1724960.pdf},
abstract = {Reliable understanding of spatial differences in highway traffic demand is essential for highway planning, pavement management, infrastructure investment, and transport-system development, particularly where traffic-count observations are geographically limited. This research investigates spatial heterogeneity in annual average daily traffic (AADT) and develops highway-specific traffic-demand models for five major inter-state highways in South-Eastern Nigeria: Umuahia-Ikot Ekpene, Onitsha-Owerri, Abakaliki-Ogoja, Enugu-Port Harcourt, and Owerri-Port Harcourt. A longitudinal dataset of 100 highway-year observations spanning 2001 to 2020 was analyzed using descriptive spatial profiling, highway-level variation measures, group-difference testing, pooled highway-effects regression, highway-specific log-linear regression, and interaction modelling. The results reveal substantial spatial heterogeneity. Mean AADT ranged from 588,709 PCU/day on Abakaliki-Ogoja to 2,202,095 PCU/day on Enugu-Port Harcourt, and highway differences accounted for approximately 82.6% of the unadjusted variation in AADT. The highway-specific models also differed markedly in explanatory structure. Passenger population density was particularly influential on Umuahia-Ikot Ekpene and Abakaliki-Ogoja, whereas GDP showed the strongest statistically significant association on Enugu-Port Harcourt. A pooled interaction model confirmed that the relationships between population density, GDP, and AADT varied significantly across highways (robust Wald χ² = 34.88, p < 0.001), providing evidence of spatially non-stationary traffic-demand relationships. These findings demonstrate that a single regional traffic-demand equation may conceal important highway-specific differences. Inter-state highway planning in South-Eastern Nigeria should therefore account for spatially differentiated demand structures. The study offers an empirical basis for more targeted highway planning, pavement management, and investment prioritization in comparable data-constrained contexts.},
keywords = {annual average daily traffic, interstate highways, spatial heterogeneity, South-Eastern Nigeria, traffic-demand modelling},
month = {November},
}