Passenger Car Equivalence Under Several Upgrade Road Conditions (For Cases under Addis Ababa City)

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Date

2023-10

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Addis Ababa University

Abstract

In developed countries, extensive studies have been conducted to estimate passenger car equivalence (PCE) values under various road geometry, traffic characteristics, and lane width conditions. However, it is important to note that these PCE values may not directly apply to local conditions in Ethiopia since Ethiopia possesses a distinct traffic environment characterized by heterogeneous traffic conditions, diverse road geometries, and unique traffic characteristics. Therefore, relying solely on PCE values derived from studies in developed countries may not accurately reflect the specific conditions and dynamics of Ethiopia's transportation system. There is also a lack of comprehensive understanding regarding the influence of vehicle characteristics in different road configurations in Ethiopia, particularly with respect to PCUs. The Highway Capacity Manual (HCM) of 2010 suggests treating road segments with steep grades separately, given their unique conditions. This study focuses on estimating Passenger Car Unit (PCU) values for six vehicle types, considering variations in traffic volume, road grade, and road lane configurations in Addis Ababa, Ethiopia. Data collection, conducted between 4:00 am-10:00 pm over four hours on Tuesday, Wednesday, and Thursday, covering both one-lane and three-lane roads in four selected areas. The utilization of an Artificial Neural Network (ANN) model aids in training and predicting speed, while the Dynamic PCE method determines PCE values. Multiple regression analysis established a mathematical relationship between PCE, vehicle type, road grade, and vehicle speed using SPSS software. Results indicate varying PCE values for different vehicle types on one-lane and threelane urban roads at different grades. Notably, heavy vehicles exhibit higher PCE on one-lane roads, while buses and medium trucks show consistently higher PCE on three-lane roads. In segments with high road grades, there is an inverse speed impact, starting high and concluding low in three-lane segments, and the inverse relationship continues in one-lane segments, starting with low speed and concluding with high speed on a high uphill grade. Moreover, the obtained PC values surpass those presented in the HCM, signifying their suitability for reflecting the current traffic conditions in the studied locality.

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Keywords

Passenger Car Equivalence (PCE), Artificial neural network (ANN), HCM (Highway Capacity Manual), Statistical Package for the Social Sciences (SPSS)

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