dynamic traffic lights scheduling system - using image processing
TRANSCRIPT
Introduction
Traffic Congestion is a severe problem…
"Just In Case" Time delays
Fuel Consumption And Pollution
Emergency Vehicles and Road rage
Important tasks getting late
Need for a more efficient traffic management system.
Improve mobility, safety, and traffic flows.
Dynamically allocate time according to traffic on lane…
TRAFFIC LIGHTS SCHEDULING SYSTEM
Sacchin Kamal
Problem Statement
“Disproportionate and diverse traffic indifferent lanes leads to inefficient utilizationof same time slot for each of themcharacterized by slower speeds, longer triptimes, and increased vehicular queuing.”
Thus, To create a system which enable thetraffic management system to take timeallocation decisions for a particular laneaccording to the traffic density on otherdifferent lanes with the help of cameras,image processing modules and μcontroller.
TRAFFIC LIGHTS SCHEDULING SYSTEM
Sacchin Kamal
Current Traffic Management Technique
Pre-determined fixed time is allocation…
• Each lane is assigned a same and fixed amount of time
• Without any regard to their individual traffic density.
• Time is wasted if some lane has very little or no traffic as it could have been utilized on busier lanes.
Need for a more efficient traffic management system.
Improve mobility, safety, and traffic flows.
Dynamically allocate time according to traffic on lane…
TRAFFIC LIGHTS SCHEDULING SYSTEM
Sacchin Kamal
Proposed Solution
The solution can be explained in four simple steps:
1. Get real time image of each lane.
2. Scan and determine traffic density.
3. Input this data to Time Allocation module.
4. The Output will be the time slots for each lane, accordingly.
TRAFFIC LIGHTS SCHEDULING SYSTEM
Sacchin Kamal
Modules Required (Software)
Image Processing – HaarTraining
• Set of programs (functions) of OpenCV that we will be utilizing for thedetection of the objects (cars) in a view (lane).
• Initially, it is trained with a Database of pictorial objects.
• Further, it automatically identifies the objects similar to training objects.
TRAFFIC LIGHTS SCHEDULING SYSTEM
Sacchin Kamal
Modules Required (Hardware)
Camera
• 4 Cameras
• One for each lane
Microprocessor
• To Receive signals from Image Processing module and glow traffic lightsaccordingly.
TRAFFIC LIGHTS SCHEDULING SYSTEM
Sacchin Kamal
Working
Sequence of operations performed:
1. Camera sends images after regular short intervals to our system.
2. The system determines further the number of cars in the lane and hencecomputes its relative density with respect to other lanes.
3. Time allotment module takes input (as traffic density) from this system anddetermine an optimized and efficient time slot.
4. This value is then triggered by the microprocessor to the respective TrafficLights.
TRAFFIC LIGHTS SCHEDULING SYSTEM
Sacchin Kamal
Working of HaarTraining
It is basically a 3 Stepped procedure:
1. Collect number of positive (car) images- that contain only objects of interest.This is done by manual cropping of natural images.
2. Collect negative (background) images- which are images other than the objectof interest. This is done to train the algorithm of what actually is the object weneed to detect and how to differ it from the surrounding.
3. Take some Natural Test Images (car in background) to test the functionality andaccuracy of Training.
TRAFFIC LIGHTS SCHEDULING SYSTEM
Sacchin Kamal
Limitations and Constraints
Image acquisition at night or in less light is problematic.
Constant Power Supply required.
TRAFFIC LIGHTS SCHEDULING SYSTEM
Sacchin Kamal
Conclusion
It can be concluded that,
• An opportunity to enhance the techniques of Traffic Management systems.
• High-quality performance.
• Since such concept-based techniques have already been successfullyimplemented in foreign countries, we strongly believe the need to implementit our country too.
TRAFFIC LIGHTS SCHEDULING SYSTEM
Sacchin Kamal