Junction_Management_Strategies_Using_ITS.pptx

The presentation provides an overview of Junction management and measuring strategies using Intelligent Transportation Systems. It also provides information about best methods to reduce the congestion at Junctions

1. Junction Management Strategies Using Intelligent Transportation Systems (ITS) Enhancing Efficiency and Safety at Intersections

2. Introduction Intersections are critical points in urban traffic networks Poorly managed junctions lead to congestion, delays, and accidents ITS offers data-driven solutions for better control and safety

3. Objectives Optimize traffic flow at intersections Minimize waiting time and fuel consumption Enhance road safety Enable real-time traffic monitoring and control

4. Role of ITS in Junction Management Real-time data collection via sensors and cameras Adaptive traffic signal control Incident detection and management Integration with ATMS and ATIS

5. Key Technologies Used Video Cameras – vehicle detection and queue length estimation Inductive Loop Detectors – measure vehicle count and speed Radar and LiDAR Sensors – non-intrusive traffic monitoring IoT-based Controllers – inter-junction communication AI/ML Algorithms – predictive traffic control

6. Junction Management Strategies 1. Fixed-Time Signal Control 2. Actuated Signal Control 3. Adaptive Signal Control (SCATS, SCOOT) 4. Intelligent Roundabouts 5. Transit Signal Priority (TSP) 6. Emergency Vehicle Preemption

7. Adaptive Signal Control Systems Adjusts signal timing based on real-time traffic conditions Uses data from detectors and cameras Examples: - SCOOT (Split Cycle Offset Optimization Technique) - SCATS (Sydney Coordinated Adaptive Traffic System)

8. Case Study Example City: Bengaluru, India System: Adaptive Traffic Control System (ATCS) Outcome: • 20–25% reduction in average delay • Improved signal coordination • Better response to traffic fluctuations

9. Benefits of ITS-Based Junction Management Reduced congestion and emissions Enhanced safety through coordination Real-time decision-making Improved user satisfaction and reliability

10. Challenges and Limitations High investment and maintenance cost Integration with legacy infrastructure Data privacy and communication issues Requirement for skilled manpower

11. Future Trends AI-driven predictive control Integration with connected and autonomous vehicles Use of edge computing and 5G Smart intersections in Smart Cities