Controlling of Traffic Signal using Neural Network

Project Title

Controlling of Traffic Signal using Neural Network

Project Area of Specialization Electrical/Electronic EngineeringProject Summary

The increase in urbanization and traffic congestion creates an urgent need to operate our transportation systems with maximum efficiency. As traffic volume continues to increase, the streets become more and more congested. One of the most cost-effective measures for dealing with this problem is traffic signal control. Traffic signal retiming and coordination of existing signals have been proven to bring about substantial reductions in traffic delay, considerable energy savings, and consequently, huge reduction in travel time and increased safety for the public. Traffic is one of major problem in our metropolitan cities. By the dramatically growth of the population in cities requires the traffic system to be designed efficiently and sustainably by taken full advantages of modern day technology. Dynamic traffic flow is significant issue which bring about a block traffic movement. In such case where the traffic congestion issues has negative impact in our society to provide mechanism to predict traffic flow with the help of Neural Network.

Project Objectives

1. We are classifying the traffic conditions are important for determining traffic control strategies and management, for better utilization of public resources.
2. The benefits of classification we can get to know which lane has traffic, from which we can further check the reasons for traffic and to take appropriate decisions to improve the performance.3
3. Helpful For metropolitan cities, also useful urban area to improve the performance in traffic congestion.

Project Implementation Method

Explanation: Our traffic signal controlling mechanism provide as a solution of traffic congestion, it has negative impact on society, because lots of time is wasted in the form traffic congestion so it is necessary to resolve this issue and controlling the traffic congestion.

Controller: ATCS4

• The ATSC4 is capable of managing up to 32 signal (phase) group displays and up to 64 inputs from vehicles, pedestrians, bicycles or emergency services.

• Its design for all weather conditions.

• Can operate with variety power supply. Can operate with low supper supply

• Capable of managing up to 32 signals groups displays and up to 56 inputs from vehicles pedestrians ,bicycles or emergency services.

• Modular construction makes maintenance easy.

• Capable and controlling the wide range of lantern technology with various load. Ease to use interface with window software.

• Timers monitor the input from vehicle detectors and adaptive personality functionality assesses traffic density and generates appropriate times to ensure efficient use of available green time.

Neural Network:

• All traffic single are design on base of continues traffic signals .so problems is that we should need infinite horizon one. In horizon on limit finite memory .but problems I that we need infinite memory to storage capacity to overlooked.

• The first issue involves the appropriate usage of various relevant techniques that have good approximating capabilities while facing an ill-defined problem with a high level of associated uncertainty and diverse input data. In this case, well-known techniques in the field of computational intelligence, such as NNs, provide possible solutions.

Technic

• Multiagent

The performance of multiagent system evaluate two measure

1) Daley time of vehicle

2) Stop time of vehicle

The microscopic traffic simulation platform of PARAMICS has been used to take detailed measurements of various parameters associated with each vehicle that enters and leaves the traffic network.

Data Processing: In data processing we will do the data process in both ways through the surveillance camera and sensor base because in rough weather condition the surveillance camera did not properly so it will be difficulty to detected the vehicles in rough condition. So senor will work and sense the movement of vehicle in rough weather and can easy the flow of traffic

Signals:

Random signals will use.

Surveillance camera:

• Surveillance camera will use for surveillance of traffic presence on road will provide the data to the controller

• Will be connected with cables on poles.

Benefits of the Project

It can used at Traffic network with relatively low amount sensor. It will ensure to solve traffic congestion issue and maximum safety incase incident. Helpful of public resources, increase quality and reducing the operational cost of services offered to the citizens.

         3. Use in Traffic Network place where required.

1. It can used at Traffic network with relatively low amount sensor. It will ensure to solve traffic congestion issue and maximum safety incase incident.
2. Helpful of public resources, increase quality and reducing the operational cost of services offered to the citizens.

Technical Details of Final Deliverable

A traffic signal has eight basic components.

.Lantern

This is the most visible component of the traffic signal system. A Lantern may have a type assigned in terms of priority (primary, secondary or tertiary), a body type, a lamp type, or a display type (for example left turn, right turn, pedestrian).

.Controller

This is perhaps the most important component, though it is not usually visible to the motorist. The Controller is the "nerve center" of the intersection signal system, and may in fact control more than one intersection. A Controller also has a number of sub-components:

•Logic Rack

•Detector Card

•Software (for such purposes as Vehicle Preemption).

•Target Boards.

•Poles.

•Pole Attachments (for example, cameras).

•Pedestrian Call Boxes / Pedestrian Detectors.

•Loops (also known as Detector Loops)

.Cabling

Final Deliverable of the Project Hardware SystemCore Industry TransportationOther IndustriesCore Technology Artificial Intelligence(AI)Other TechnologiesSustainable Development Goals Sustainable Cities and CommunitiesRequired Resources

Elapsed time in (days or weeks or month or quarter) since start of the project	Milestone	Deliverable
Month 1	(Literature Review) November-2020	December-2020
Month 2	(Designing of Hardware Frame)January- 2021	Febuary-2021
Month 3	(Structuring) March- 2021	April -2021
Month 4	(Interfacing & Trial) April - 2021	July -2021
Month 5	(Testing & Fixing) July-2021	October-2021
Month 6	(Presentation Preparation) October -2021	November-2021