AJET_Vol 07 N 01

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Browsing AJET_Vol 07 N 01 by Author "Mije, Fwanshak Gaius"

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    Empirical Assessment of Mixed Traffic Congestion on Selected Arterials in an Urban Metropolis, Nigeria
    (جامعة الوادي - university of el oued, 2022-09-27) Ako, Terseer; Tunde, Yusuf Ibrahim; Mije, Fwanshak Gaius
    The study was aimed at investigating the appropriateness and development of congestion indices and predictive model with operational parameters for congestion on the roads of a developing city. A manual 12-hour (6.00 am- 6.00 pm) traffic count was conducted for seven consecutive days of the week and converted to passenger car units (pcu) on Gboko, Iorchia Ayu, Otukpo, Joe Akaahan, Atom Kpera and Lafia roads of Markurdi to determine congestion spots. Five parameters of volume, headway, speed, density and delay were derived from the generated database in accordance with Highway Capacity Manual of 2010. Traffic congestion indices, with corresponding predictive models, were quantified, and a 15-year congestion forecast made to obtain the future operating scenarios on Makurdi roads. Makurdi roads were dominated by cars of 38.09-61.87%, motorcycles of 15.58-22.85%, minibuses of 10.63-31.33%, and tricycles, luxurious buses, lorries/trucks, trailers/tankers of 0.03-7.75%; with operating significant parameters at peak period of 2322-3134 pcu/h., 305-990 pcu/km., 1.7-2.2 s and 17-40 km/h for the volume, density, headway and speed, respectively; the degree of congestion on the selected routes were moderate to severe (volume capacity ratio of 0.51-1.32) and substantially dependent on the operating parameters, predictive model for the roadway traffic congestion index, CI = 107.071+0.028v+10.054Sl +0.013c with R2 = 0.97, was generated with volume (v), segment length (Sl) and capacity (c); and a 15-year projection indicated that Joe Akaahan Road would be heavily congested. All other segments would be severely congested. The present and 15-year projected CI values were 1.83 and 3.77 respectively, indicating extra vehicle kilometer travel due to congestion of 377%. It is recommended that congestion indices and predictive model are useful tools for management of congestion on urban roads of a developing city