ADAPTIVE TRAFFIC CONTROLLER

1. Professor Doshi Peter Petrakis (team manager) Marcin Celmer Matt Wilhelm Tom Stack ADAPTIVE TRAFFICCONTROLLER

2. BACKGROUND When driving down the road we often encounter traffic lights. The current design of these traffic lights is that of simple timing, which may cause drivers to stop unnecessarily. Suppose that there existed a system that could detect the density and velocity of the traffic that converged on an intersection. That the information gathered would then be used to determine a new traffic light timing cycle, one that would cause the driver to wait less at the intersection. This system will ensure a happier driver and a smoother flow of traffic.

3. Deliverables One prototype will be delivered which will be scalable from remote control cars up to actual cars. A deployable field of sensors will relay information to a central processing system that will process our traffic flow and adjust the traffic lights accordingly.

5. Ultrasonic Sensing • Sensors will be embedded in existing road • Net of sensors located at predetermined distance away from the intersection along with one sensor at the intersection.

6. Ultrasonic Sensing • As cars travel over these sensors, the signal will be reflected back to the sensor • Wireless transmission of sensor net to traffic controller • Ultrasonic sensors are inexpensive, small, and light • Implementation time varies from 10ms to 250ms depending on the range of the signal

7. RF Transmission • Master controller has a RF receiver which waits for input from the sensor nets. • Field bus transmit data collected from field bus (sensors) to master controller.

8. Signal Modulation • Incoming signal to master controller is acquired • Signal is filtered and amplified. • Result is passed off to DSP for A/D conversion and further processing.

9. Alternative Detection Methods • RFID • Infrared • RADAR

10. Digital Gateway • Multiple analog signals acquired from individual sensor fields. • Converted to digital • Processed for desired information • Evaluate the traffic flow / rank • Change traffic lights accordingly

11. Digital Signal Processing • Built in A to D conversion • Powerful Floating Point capability, free up microprocessor to focus on system control • Possible ability to determine traffic rank • Inexpensive ~ $5

12. Embedded Operating System • Real-Time • Low Latency • Ability to use higher level languages • Less code to debug. • Implementation Independent of CPU architecture • Possible Architectures including but not limited to Atmel, ARM, MIPS, PPC

13. Finite State Machine • Responsible for maintaining state of intersection • Simple/cost effective • Verilog • Keeps logical errors to a minimum • Ensures safe intersection states • Uses an Altera chip set

14. Traffic Light Controller We intend to interface with the existing control system at the intersection while leaving the existing control system intact. A strategy could be devised where if the data collected is not compelling enough that control of the lights could defer to the existing timer based control system.

15. A colored light bulb mock traffic light would be used to represent our test intersection which would be controlled by our primary control system. Demo Intersection

16. Target Acquisition Tracking Directory • Addresses privacy concerns • Will not store long term vehicle Identification • Size of the memory required is dependent on the ID scheme, and length of necessary tracking history

17. Evaluate the sensor array then using the collected data the algorithm for the traffic arbitration will be derived. A prototype sensor array will be designed for the purposes mentioned above. The central processing unit will be designed and the embedded OS will be evaluated. The RF transmitter, receiver, and carrier wave will be designed. MDR GOALS