Advanced_Traveler_Information_Systems_ATIS.pptx

ATIS is a core component of Intelligent Transportation Systems (ITS)

Provides real-time information to travelers for better decision-making

Enhances safety, reduces congestion, and improves travel efficienc

1. Advanced Traveler Information Systems (ATIS) Enhancing Mobility Through Real-Time Information Dr. B N Skanda Kumar – Jyothy Institute of Technology, Bengaluru

2. Introduction ATIS is a core component of ITS Provides real-time information to travelers for better decision-making Enhances safety, reduces congestion, and improves travel efficiency

3. Objectives of ATIS Deliver accurate and timely travel information Assist in route, mode, and departure time decisions Reduce travel time uncertainty Improve overall transportation network performance

4. Components of ATIS Data Collection Subsystem: Sensors, GPS, cameras, probe vehicles Data Processing and Integration: Data fusion, traffic modeling Information Dissemination: Variable Message Signs (VMS), mobile apps, radio, web portals

5. Information Types Provided Real-time traffic conditions Incident and accident alerts Public transport schedules and delays Parking availability and costs Weather and road conditions

6. Technologies Used GPS GIS Communication Networks (4G/5G, DSRC, IoT) Cloud Computing & Big Data Analytics AI and ML

7. ATIS Architecture Data Sources → Processing Center → Information Dissemination → Traveler Interface Integration with other ITS subsystems (ATMS, APTS, ATCS)

8. Modes of Information Dissemination Pre-trip: Websites, mobile apps, route planners En-route: Dynamic message signs, in-vehicle navigation, radio updates Post-trip: Feedback systems and data analytics

9. Case Studies 1. Google Maps / Waze: Real-time crowd-sourced traffic updates 2. Delhi Integrated Multi-Modal Transit System (DIMTS): Public transport tracking 3. US DOT 511 System: Free traveler information hotline

10. Benefits of ATIS Reduced congestion and travel time Enhanced traveler satisfaction and reliability Improved safety and environmental sustainability Supports multimodal transport integration

11. Challenges Data accuracy and integration Privacy and cybersecurity issues Infrastructure and maintenance cost Public awareness and adoption

12. Future Trends Predictive travel analytics Integration with connected & autonomous vehicles (CAVs) Personalized travel assistance using AI chatbots Augmented Reality (AR) for navigation and safety