1. Agent Based Traffic Simulator for Autonomous Vehicle
BY:
Kamalika Saha
Ms. Sonia Rathee
Deptt. of CSE, Maharaja Surajmal Institute of Technology, New Delhi, India

2. Introduction
The project aims to provide a simulation for traffic management at intersections in case of autonomous vehicles which can further be implemented at a city- wide scale. The advent of driverless cars provides optimizing traffic in ways which were not possible before.
The project has been made to substitute the conventional means of controlling traffic particularly, the traffic signals.

3. Objective
This project aims to create a scalable, safe and efficient multi-agent framework for managing autonomous vehicles at intersection.
In the future with computers “behind the wheels”, it will make travel easier, safer and much more efficient.

4. What’s Wrong With The Conventional Traffic System?
Traditional traffic systems & stop signs are very inefficient.
Vehicles traversing intersections using these mechanisms experience large delays.
The intersections can only manage a limited traffic capacity – much less than that of the roads that feed into them.
The time that vehicles spend in case of traffic systems results in unnecessary wastage of fuel powering the vehicles.

5. Autonomous Intersection management
Autonomous Intersection Management (AIM) aims to provide an alternative to existing traffic signal optimization schemes.
In this approach, we use a program called the driver agent located in each vehicle that communicates with the server present at the intersection points and other agents in a multi-agent environment.
It also uses an intersection manager which is assumed to be a server present at each intersection.

6. The Reservation Idea….
Any intersection manager present at the intersection maintains a reservation table for the list of past requests made by any autonomous vehicle.
If there are no conflicts, the intersection manager issues a reservation. It becomes the vehicle’s responsibility to arrive at, and travel through, the intersection as specified.
In the case of a conflict, the intersection manager suggests an alternate later reservation.
The car may only enter the intersection once it has successfully obtained a reservation.

7. Implementation
The study of algorithms used in project implementation such as Intersection Manager Algorithm, FCFS (First Come First Serve), A* Search.
Development of GUI for a simulator using Java-Swing.
Implementation of the above described algorithms to create a stable simulation.

8. Demo Screen Shots

10. Limitations
If the traffic at the intersection is increased beyond certain limits then the simulator might not respond or is not able to support intersection policies simulation .
Lane Changing Algorithm is not implemented in our project.
Mechanical failures are not taken into account.

11. Conclusion
We, therefore, conclude that the project to create a simulation for Agent Based Traffic Simulator for autonomous vehicles has been implemented successfully, however, there is a wide scope to implement the project on a real time basis and implementing the lane changing algorithm successfully

12. References
Approximately Orchestrated Routing and Transportation Analyser: Large Scale Traffic Simulation for Autonomous Vehicles.
Vehicle to Infrastructure based Safe Trajectory: Planning for Autonomous Intersection Management.
Auction-based autonomous intersection management.