GIS for traffic signal optimization.
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The document discusses the integration of Geographic Information Systems (GIS) in traffic signal management to address urban traffic challenges caused by increasing vehicle numbers. It outlines methodologies for static and dynamic traffic signal control, utilizing data collection and analysis to optimize traffic flow. The conclusion emphasizes the potential of GIS in enhancing traffic signal timing and data management for better urban traffic systems.
GIS for traffic signal optimization.
- 1. GIS FOR TRAFFIC SIGNAL SYSTEM PRESENTED BY- VINOD KUMAR NIKHIL KRISHNAN
- 2. OUTLINE • Introduction • What is GIS • Traffic signal • Types of traffic signal system • Application of GIS • Static method • Dynamic method • Conclusion
- 3. INTRODUCTION • Traffic is the biggest problem in the cities. The main cause of this traffic is number of vehicles on roads are increasing day by day but infrastructure is not capable of handling them properly. • Using latest technologies (GIS and ITS) traffic problem can be resolved easily. • Proper use of traffic signal can lead toward traffic management.
- 4. WHAT IS GIS • A geographic information system (GIS) is a computer system for capturing, storing, checking, and displaying data related to positions on Earth's surface. GIS can show many different kinds of data on one map. This enables people to more easily see, analyse, and understand patterns and relationships.
- 5. TRAFFIC SIGNAL • Traffic signals are control devices which could alternately direct the traffic to stop and proceed at intersections using red and green traffic light signals automatically. • The main requirements of traffic signal are to draw attention, provide meaning and time to respond and to have minimum waste of time.
- 6. TYPES OF TRAFFIC SIGNAL • Traffic control signal- (a) Fixed time signal (b) Manually operated signal (c) Traffic actuated signal • Pedestrian signal • Special traffic signal
- 7. APPLICATION OF GIS • GIS can be used in two different ways to manage traffic signals. (1) Static method (2) Dynamic method
- 8. STATIC METHOD • In this method we have to collect all the information regarding road networks, traffic load, signal timing and other things. • It involves construction of directed graph. • It involves construction of k depth tree.
- 9. PARAMETERS REQUIRED • Volume of traffic. • Type of road. • Distance between two intersection. • Width of road. • Speed limit. • Signal location.
- 10. CONSTRUCTION OF DIRECTED GRAPH • For this we require two parameters direction and weighted value. • The direction will show the flow of direction of traffic in that particular branch and weighted value gives average traffic load per minute in that branch.
- 12. Traffic load in particular branch
- 13. Directed graph
- 14. CONSTRUCTION OF K DEPTH TREE • Total number of tree will be equal to number of vertex in the graph.
- 15. Traffic load and cumulative traffic load ratio
- 16. Path of maximum traffic load • Here selected path is AF which traverses through A, C, H and F. As we know that traffic load in this particular path is very high so by sequentially controlling the signals of A, C, H and F vertex we can mange the traffic load path AF . • In practical situation traffic signal of that particular path can be turned green to manage the traffic load of the path.
- 17. DYNAMIC METHOD • This method is based on real time traffic data. • In this method we use CCTV cameras and other detector systems to calculate the traffic load on a particular branch. • GIS is used for generation of road network system, positions of cameras and signals.
- 18. METHODOLOGY • Two modules: a traffic data pre-processor and a GIS application. • The pre-processor calculates averages and maximums of queue lengths, traffic light periods and node saturation. • It acts as a client for DIME and as a server for the GIS application.
- 19. FLOW CHART
- 20. CASE STUDY-TEHRAN CITY • The proposed methods were implemented by ArcGIS utilization and customization • The integration value for every urban traffic network node (intersection) during four times a day is calculated and is classified in 4 classes by the equal interval classification approach.
- 22. RESULTS
- 23. CONCLUSION • By the application of GIS we can manage the huge amount of data. • We can allot exact timing to traffic signal. • For having better and up to date traffic information access, spatio-temporal GIS for transportation needs to interact with the ITS. • optimal control strategies for freeways and arterials.
- 24. REFERENCES • Traffic light control by using GIS and estimated traffic load in an area by Alok Tiwari et. all. • Approaches for Intelligent Traffic System: A Survey by Pratishtha Gupta, G.N Purohit, Amrita Dadhich .(2012) • A GIS-based traffic control strategy planning at urban intersections by Mina Khalesian, Parham Pahlavani and Mahmoud Reza Delavar.(2009) • Highway engineering by S.K Khanna, C.E.G Justo.