Predictive models for entry flow at rotary intersections in Akure-a developing city in Nigeria-have been developed. Data were collected at the intersections critical to traffic flow in the study area using a cine camera placed at a vantage point from the road sections during peak and off-peak periods in week days. Entry flow (qe) was modelled as a function of circulating flow (qc), delay (da), headway (h) and geometric features of the intersections. The data were fitted to a multiple linear regression equation to obtain the generalized flow models for peak and off peak periods. The equations obtained were validated using empirical data other than those used to calibrate the model. The adjusted R 2 values obtained during the peak and off peak periods were 95.8% and 87.7% respectively, indicating that the independent variables (circulating flow, delay and headway) made significant contributions in predicting the entry flow. The models developed can be used to evaluate entry flow at rotary intersections in the study area and other cities in developing countries with similar traffic characteristics for which such models are scarce, thereby facilitating planning and design of effective traffic control mechanisms.
Unsignalized intersections namely two-way stop-controlled intersection (TWSC) and all-way stop-controlled intersection (AWSC) are widely used in Akure. Five intersections consisting of three Tee and two Cross that were critical to traffic flow in the study area were selected for study. Data on geometric features were collected using odometer, while traffic parameters were captured and metered using cine camera placed at a vantage point from the road section during peak and off-peak periods on week days. Traffic flows at the intersections were expressed as functions of traffic characteristics and geometric features of the approaches; while the effect of distances of intersections before and after the intersections studied were also incorporated as a correction factors in the models. The models were developed using multiple linear regression technique with the aid of SPSS software and validated with empirical data other than those used for model calibration. Adjusted R2 values of 0.881 and 0.882 were obtained for Tee and Cross intersections respectively for peak period, while 0.938 and 0.940 respectively were obtained for the off-peak period. These indicate that the flow models are very robust in replicating the observed data. The predictive models have the potential to accurately estimate traffic flow at intersections in the study area and other cities of the world with similar traffic conditions.
Abstract:Unsignalized intersections namely two-way stop-controlled intersection (TWSC) and all-way stop-controlled intersection (AWSC) are widely used in Akure. Five intersections consisting of three Tee and two Cross that were critical to traffic flow in the study area were selected for study. Data on geometric features were collected using odometer, while traffic parameters were captured and metered using cine camera placed at vantage positions from the intersections during peak and off-peak periods on week days. Traffic flows at the intersections were expressed as functions of traffic characteristics and geometric features of the approaches; while the effect of distances of intersections before and after the intersections studied were also incorporated as correction factors in the models. The models were developed using multiple linear regression technique with the aid of SPSS software and validated with empirical data other than those used for model calibration. Adjusted R2 values of 0.881 and 0.882 were obtained for Tee and Cross intersections respectively for peak period, while 0.938 and 0.940 respectively were obtained for off-peak period. These indicate that the flow models are very robust in replicating the observed data. The predictive models have the potential to accurately estimate traffic flow at intersections in the study area and other cities of the world with similar traffic conditions.
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