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Adaptive Traffic Control SystemB r i n g i n g I n t e l l i g e n c e t o I n t e r s e c t i o n s

A traffic phase is defined as the green, change, and clearance

intervals in a cycle assigned to specified movement(s) of traffic.

PHASE

A series of non-conflicting phases which run together.

STAGE

A cycle is defined as the total time to complete one sequence of

signalization for all movements at an intersection.

CYCLE

The difference between the GREEN initiation times at two adjacent

intersection.

OFFSET

Actual time available for the vehicles to cross the intersection.

EFFECTIVE GREEN TIME

TRAFFIC DOMAIN

The DoS of an intersection is a measure of how much demand it is

experiencing compared to its total capacity.

DEGREE OF SATURATION (DoS)

TRAFFIC DOMAIN

Signal timings derived from the statistical data

Duration and order of all green phases are fixed

Cannot respond to real-time demand

Requires frequent re-configurations and updates

Traditional Signal System

Low level of lane discipline

High mix of traffic

Lack of local expertise

Poor junction geometry

Lack of expertise

Power and Network connectivity interruptions

Challenges in INDIA

Solution

A solution for a smooth and safer journeys

Adaptive Traffic Control System

What is ATCS ?

Adaptive Traffic Control System adapts to real time

traffic patterns to optimize the traffic flow by

dynamically change the green split timings.

Detectors

monitors

traffic

Algorithms

compares to

current plan

Change

timings if

needed

1

2

3

ATCS

An ATCS uses Advanced Machine Learning algorithms that adjust

❖ Cycle length

❖ Phase sequence to

Minimize delays Reduce the number of stops Decrease the travel time

OBJECTIVES

Reduce Accident Rates Increase Travel Speeds Reduce Stops, Delays & Queues

Increase Operational

Efficiency

Real Time Information management

Create a platform for sharing traffic to other systems

Where is

ATCS most effective?

Where frequent and unpredictable

changes of demand, events, weather

situations, etc., creates unexpected

fluctuations in the system

Where unpredictable traffic changes

results in delays or stops that cannot

be addressed by conventional signal

timing.

ATCS does not necessarily

solve the capacity problems

of over saturated corridors.

Adaptive Traffic Control System

Completely Designed for Indian Traffic Conditions

Bringing Intelligence to Intersections

Employs advanced Machine Learning Algorithms

Traffic data from junctions is consolidated in a central traffic system

Dynamically adapts to changing traffic conditions

Junction green-green synchronization

1. Vehicle detector

6. Web Interface

7. Adaptive Algorithm

8. Real-time Reports

9. ML based forecasting

10. API Services

4. Master Controller

5. Edge Application

2. LED Signal Lamps

3. Countdown Timer

ATCS Controller

Slave ControllersSerial Wired / WirelessControl Logic & Split

Optimization

Signal Aspects

Switching Logic

Vehicle Detectors

Communication Interface

Ethernet / GPRSVehicle data, Stage timing, Saturation etc.

Configured Data[Routes, Scheduled Timings, One-ways, Preferences etc.]

KPIs calculation for intersection, approach &

corridor

Configured Data[min/max phase length, Cycle lengths, Pedestrian timings]

Current Signal Timings

Route/Corridor Selection

Critical Cycle Time & New Phase Time Calculation

Offset Calculation

Cycle & Split Calculation

New Timings Calculation

ATCS Algorithm

Vehicle Detection

Phase Sequence Information

Way Volume Calculation

Saturation Flowrate Calculation

Online Split Optimization Learning Data

Traffic Intersection

Machine Learning AlgorithmStage Optimization / Performance Index

Vehicle data, Stage timing, Saturation etc.

Central Server

Timings TranslationPreferences & Observations

Offset OptimizationGroup Cycle Length

CalculationKPIs calculationWeights & Bias

New timings & Preferences

Machine Learning AlgorithmTraffic Forecasting

Vehicle Data, Events, KPIs, Forecasting Data

Integration APIs

Web interface

Switching Logic

Mode of Operation Stage timings execution Vehicle Detectors Input Pre-emption Cycle Time

Fixed Time (Pre-timed) As per site specific time-table. Ignored Not made on any stage Constant

Vehicle Actuation with Allstages Pre-emption

As per demand from vehicle detectors YesFor all demand actuatedstages

Variable

Semi-ActuationAs per demand from vehicle detectors forvehicle actuated stages. Remaining stagesexecute maximum green time configured.

YesFor all demand actuatedstages

Variable

Vehicle Actuation with Fixed Cycle Length

As per demand from vehicle detectors YesFor all demand actuatedstages except for prioritystage

Constant

Adaptive Traffic ControlAs per demand from vehicle detectors forthe stage and cycle time computed bycentral algorithm

YesFor all demand actuatedstages except for prioritystage

Variable

Manual (Power Down – Blank,Amber Blinker, Green corridorand Police Hurry Call)

As per setting, only one defined stage Ignored Not made on any stage Constant

Transit Signal Priority forPassenger Buses / Emergencyvehicles

As per setting, only one defined stageIgnored Not made on any stage Constant

Fixed Mode (For 2 cycles)

Vehicle Actuated

Mode

Semi Actuated

Mode

ATCSMode

Powered UP

cameras.connected = 0

cameras.connected > 0 .and.

< cameras.config.countcameras.connected = 0

cameras.connected = cameras.config.countcameras.connected > 0

.and.< cameras.config.count

central.connect = true

central.connect = false.and.

(cameras.connected > 0.and.

< cameras.config.count)

central.connect = false.and.

cameras.connected = cameras.config.count

cameras.connected = 0

central.connect = true.and.

cameras.connected = cameras.config.count

Manual/Priority

Mode

manual.control = true.or.

vehicle.priority = true

manual.control = false.and.

vehicle.priority = false.or.

timeout.event = true

central.connect = true&

cameras.connected = cameras.config.count

ATCS ELEMENTS

API

Services

Adaptive

Algorithm

ML based

Forecasting

Edge

ApplicationMaster

Controller

Countdown

timers

LED signal

lamps

Vehicle

Detectors

Web

Interface

Real-time

reports

1

6

8

4

7

10

3

5

2

9

ATCS

MASTER CONTROLLER

Inputs derived from Cameras/Sensors/Radar will allow the ATCS Controller to

adaptively adjust the junction timing pattern and communicate the same to the

next junction and the control room.

VEHICLE DETECTORS

Detects traffic flow, headway, average speed, occupancy and queue

length by using in-built advanced machine learning algorithms.

Cover up-to 1-3 lanes at a time and has 90% detection accuracy

Any adaptive traffic control system relies upon good detection of the current conditions in real-

time in order to allow a quick and effective response to any changes in the current traffic situation.

LED SIGNAL LAMPS

EN 12368 Compliant

Premium quality LEDs

10+ years working life

Designed as per Indian Conditions

COUNTDOWN TIMERS

EN 12966 Compliant

Signal time indications to road commuters

10+ years working life

Designed as per Indian Conditions

ADAPTIVE ALGORITHM

The well advanced ATCS algorithm fulfil the ATCS main objectives

based on Indian traffic conditions. ATCS algorithm determines

optimized red-green phases of traffic signals in order to achieve

junctions green-green synchronization.

ATCS

EDGE APPLICATION

Offers a high-level framework which provides a single access

point for all the component systems and support for the whole

life cycle of a system: implementation, operation, updating and

planning.

Process Vehicle detector data

Capture and store all signalling events

Able to run junction in VA/Fixed modes when networks fails

Auto data backup & recovery mechanism

In built edge computing capabilities

ATCS

WEB INTERFACE

Intelligent Web browser-based access, requiring no local setup on

the control centre with hierarchy based secured login to operators

and city managers for their dynamic and strategic planning in real

time.

Core traffic management application in ATCS

Secure user level based authentication

Centrally monitor/control/configure junctions from one place

Interactive UI to use any novice user without prior domain knowledge

Inbuilt monitor, control, reports modules

ATCS

WEB INTERFACE

Live monitoring for quick insights & decisions

Junction mimic screen

Junction Configuration

Junction Configuration

Signal Configuration

Day plans Configuration

Green Corridor Feature

REAL-TIME & HISTORICAL

ADAPTIVE REPORTS

Exceptionally flexible and user-friendly graphical interface which

is also multilingual. The clear graphics allow rapid and intuitive

interpretation of the real-time status of the network.

KPI Reports – Time space Diagram

MACHINE LEARNING BASED

TRAFFIC FORECASTING

ATCS uses machine learning algorithms to analyse real-time traffic

data to determine signal timings that are optimal for existing

traffic conditions along the corridors.

MACHINE LEARNING BASED

TRAFFIC FORECASTING

Predictive analytics for prescriptive maintenance

API SERVICES

This gives all applications access to high quality data, which is

available to operators and city managers for their strategic

planning. The DBs themselves remain independent in order to

keep the system open and flexible.

High quality data set

Get quick junctions signal & health events in JSON with simple API call

Various data formats for heterogenous utilisation like RLVD, VMS info etc.,

Get live traffic situations to display at Information sign boards

Quick alerts with faster response

BENEFITS

Bus priority compensation and emergency vehicle pre-emption.

Integration to share the predicted forecasts to different dissemination

systems.

Suggestions to future infra requirements based on the real time traffic

density.

Power saving by regulating the intensity based on ambient light

sensor.

Standard Models Comparison

SCOOT SCATS efftronics ATCS

Upstream detection Downstream detection Downstream detection

Centralized system Distributed system Distributed system

Fixed traffic region Adjustable region Adjustable region

Fallback - fixed Fallback - VA Fallback - VA

Model based [Time generated] Algorithmic [Plan selection] Algorithmic [Time generated]

User Interface was little bit complexlacks user-friendly interface

features to support day-to-day operation

user-friendly interface features to support day-to-day operation

Doesn’t make real-time adjustments as traffic volume

changes

Does not have the predictive capability

Has predictive capability

Limited scalability Limited scalability High scalability

Not fit for developing nations Not fit for developing nations Designed for developing nations

SCOOT - Split Cycle Offset Optimisation TechniqueSCATS - Sydney Coordinated Adaptive Traffic System

CASE STUDY

Gandhinagar Smart CityGujarat, INDIA

Gandhinagar Smart City, India’s first smart city, and the second planned

city after Chandigarh. Efftronics ATCS played a major role in solving the

most vulnerable traffic problems and leads to the Vision of the city of

being an equitable urban centre that provides a high quality of life to all its

citizens.

Reduce travel times by

12-20%

20-40%Less waiting time

10-20%more friendly to

environment

Reduce Number of stops

in a corridor by

15-30%

Thank You

@efftronics_ltd /efftronics /company/efftronics

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