THE IMPACT OF ARTIFICIAL INTELLIGENCE IN OPTIMIZING PUBLIC TRANSPORT ROUTES: A CASE STUDY OF KADUNA METROPOLITAN TRANSPORT AUTHORITY
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Background of the Study
Public transportation is a vital service in urban areas, connecting people to their workplaces, schools, and essential services. In Kaduna, the Metropolitan Transport Authority (KMT) faces challenges in optimizing routes to meet the growing demands of the city's population. Congestion, inefficiencies, and lack of data-driven planning have led to delays, high operational costs, and commuter dissatisfaction.
Artificial Intelligence (AI) offers innovative solutions to these challenges by analyzing real-time data from traffic patterns, commuter behaviors, and operational metrics. AI-powered systems can recommend route adjustments, predict peak demand, and optimize schedules. Such systems enhance commuter experiences, reduce travel times, and ensure efficient use of resources.
This study examines the impact of AI in optimizing public transport routes, focusing on its implementation and outcomes at the Kaduna Metropolitan Transport Authority.
Statement of the Problem
Inefficient public transport routes and schedules in Kaduna lead to long commute times, increased operational costs, and reduced customer satisfaction. Traditional methods of route planning often fail to adapt to real-time traffic conditions and commuter needs. This study investigates how AI-powered solutions can address these inefficiencies.
Aim and Objectives of the Study
Aim:
To evaluate the impact of Artificial Intelligence in optimizing public transport routes at the Kaduna Metropolitan Transport Authority.
Objectives:
- To identify the challenges in current public transport route planning.
- To assess the effectiveness of AI-driven solutions in optimizing transport routes.
- To evaluate the impact of optimized routes on commuter satisfaction and operational efficiency.
Research Questions
- What are the limitations of current public transport route planning methods in Kaduna?
- How can AI-driven solutions enhance route optimization and commuter experiences?
Research Hypotheses
- AI-powered solutions reduce inefficiencies in public transport route planning.
- Optimized transport routes enhance commuter satisfaction and reduce travel times.
- AI-driven systems improve the cost-effectiveness of public transport operations.
Significance of the Study
This study provides insights into how AI can transform public transport route optimization, offering solutions to policymakers, transport authorities, and urban planners for enhancing urban mobility and efficiency.
Scope and Limitation of the Study
The study focuses on the application of AI for route optimization within the Kaduna Metropolitan Transport Authority. Limitations include the availability of real-time traffic data and the study's focus on a single city.
Definition of Terms
- Artificial Intelligence (AI): The simulation of human intelligence by machines to perform tasks and make decisions based on data.
- Route Optimization: The process of determining the most efficient paths for vehicles to take.
- Public Transport: Systems that provide shared transportation services to the public, including buses and trains.
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