// THESIS GUIDANCE PORTAL · Engineering
Smart Traffic Management System for Kathmandu
1. Introduction & Problem Statement
Overview: Design an AI-based adaptive traffic signal control system for Kathmandu's major intersections. Uses real-time vehicle counting via YOLO object detection to optimize signal timing.
Background Context (Nepal): Kathmandu's traffic congestion causes an estimated NPR 28 billion annual economic loss. Traditional fixed-time signals are inefficient. Computer vision-based adaptive systems can reduce congestion by 20-40%.
2. Research Objectives
- ›Implement real-time vehicle detection using YOLOv8
- ›Design adaptive signal timing algorithm
- ›Simulate system on Kathmandu intersection data
- ›Build control dashboard for traffic police
- ›Measure congestion reduction vs fixed-time baseline
3. Proposed Methodology
- Video data collection from Kathmandu intersections
- YOLOv8 model training for Nepali traffic conditions
- Adaptive algorithm design — reinforcement learning
- SUMO traffic simulation for evaluation
- Dashboard development for deployment
4. Thesis Chapter-by-Chapter Outline
Chapter 1: IntroductionTU/KU standard
Kathmandu traffic problem, existing systems, research scope
Chapter 2: Literature ReviewTU/KU standard
Adaptive traffic systems, computer vision, RL in traffic control
Chapter 3: System ArchitectureTU/KU standard
Camera setup, detection pipeline, adaptive algorithm, dashboard
Chapter 4: ImplementationTU/KU standard
YOLO training, algorithm coding, simulation setup
Chapter 5: Simulation & ResultsTU/KU standard
SUMO simulation results, comparison analysis
Chapter 6: ConclusionTU/KU standard
Findings, deployment recommendations, future work
5. Recommended Tools & Technologies
To implement the practical, technical, or analytical portions of this thesis topic, the following software tools, libraries, or APIs are recommended:
6. Core References & Citations
- [1]DoR Nepal — Road Transport Statistics
- [2]Redmon, J. et al. (2016). You Only Look Once: Unified, Real-Time Object Detection.