Traffic Congestion Hot-Spots Area And Traffic Demand Analysis By Using Travel Demand Modeling, In Downtown Adama City

Abstract

Nowadays almost all over the world especially in developing countries, the influence of rapid urbanization results in rapid motorization that leads to traffic congestion in urban mobility. Traffic congestion hotspots are a dynamic phenomenon in urban life characterized by a high traffic delay in the transportation system. Traffic demand is the over-dependence of people in transportation. Adama has experienced an alarming rate of urbanization and growth. Over the past years, the city has observed an amazing expansion and an increment in population size. Traffic congestion and traffic demand in the city are due to rapid urbanization, increased transport demands, and increment of private vehicle ownership, leading to significant motorization in the urban center. The study aims to analyze traffic congestion hotspots and traffic demand in Adama City's downtown using travel demand modeling. Cordon count which is a manual field count of traffic volume was employed to identify the most congested route in the traffic analysis zone. Survey, interview, and questionnaire was the major instrument for primary data collection for origin-destination analysis, household travel survey, and for travel demand modeling analysis. The study carries out a trip generation and attraction model analysis to examine the volume of trip production in the study zone of Gurmmu Kebele. Households, private car owners, and public transport users who commute regularly to the central business district are the representative target of this study. A sample of 210 was chosen which was stratified into 70 samples for each target group. Data were analyzed by using descriptive statistical tools, network analysis, and analysis of relationships. For all chosen routes in the traffic analysis zone, the study found that the route from Franco to Posta Bet was extremely congested especially at peak hour (morning and evening), with a total peak hour volume of 1946 vehicles per 15-minute interval, resulting in a Level of Service grade of F(constrained maneuverability at peak hour). The Franco to Posta Bet route experiences increased travel times and decreased speeds during morning and evening peak hours, with a higher travel time in the evening compared to the morning. During evening peak hours, covering the distance takes an average of 250.5 seconds. The overall origin-destination trips of households are held within the traffic analysis zone, with an average work distance of 1.5km. The study found that a trip of household origin-destination in the traffic analysis zone made an average of 7.8 trips per weekday and household members averaged 3.0 trips per weekday. The trip production and attraction results show a total trip production of 9007 per weekday across the four-study zone. The highest trip production was in Gurmmu Kebele's zone two, with 3,236 trips generated in weekday travel. As a mitigation measure modeling traffic and flexible work schedules can spread traffic volume across the day, reducing peak-hour demand and improving overall traffic conditions.