This whitepaper proposes a Smart Penalty System (SPS), which has the potential to solve prevalent violation issues through the automation of the penalty system. The SPS uses pattern recognition to identify the vehicle license number plate and automatically sends the penalty to the owner of the vehicle.

1. Smart Penalty System (SPS) in
Traffi c Signa ls

2. Abbreviations
Table of Contents
Market Trends and Challenges
Common Issues
Conclusion
Smart
Penalty
Abstract
Solution
RReeffeerreennccee
Author Info
3
3
3
4
6
6
7
7
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3. Abstract
Smart Penalty System (SPS) in Traffic Signals | 3
One of the major impacts of traffic violations on the road are traffic jams, especially in metropolitan cities such
as Chennai, Bangalore, Mumbai and New Delhi. It is nearly impossible to control the explosion of traffic in such
areas, and consequently, smaller traffic violations at the signals often go unnoticed. Normally, people take
advantage of this and try to cross the road at the signals before the light turns green. Only by levying a reason-able
penalty on those who violate traffic rules, we would be able to control the city traffic to a good extent.
However, amidst so many fast-moving vehicles, it becomes extremely difficult to stop the violating vehicles in
the middle of traffic to enforce the law as that only adds to the frustration aammoonngg ccoommmmuutteerrss..
Through this whitepaper, we are thus proposing a Smart Penalty System (SPS), which has the potential to solve
prevalent violation issues through the automation of the penalty system. The SPS uses pattern recognition to
identify the vehicle license number plate and automatically sends the penalty to the owner of the vehicle.
Abbreviations
Sl.No
1
2
Acronyms (Page No.) Full Form
SPS (Page no: 4)
ALPR (Page No: 6)
Smart Penalty System
Automatic License Plate Recognition
Market Trends and Challenges
The current penalty system, being manual, requires a huge number of human resources, such as the traffic
police. Even though the current system is working well, incidents of violation are not reducing since it is not
possible to monitor all of the traffic efficiently. Even if we were able to monitor and cover an entire area of
moving traffic by installing cameras, we cannot stop everybody from violating rules nor penalize them amidst
such heavy traffic. This would lead to other unethical issues, such as taking bribes.
There are many reasons why we need an automated penalty system.
The increasing amount of traffic on roads due to the growing number of vehicles.
Traffic peak hours being extended to the entire day.
It is not possible to monitor the entire stretch of roadways. By using human resources we can control
or monitor traffic only at the signals or at some of the most highly populated areas.
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4. Smart Penalty System (SPS) in Traffic Signals | 4
The current system contains many gaps allowing violators to escape from paying penalties. For example, if a
person is warned and asked to pay the penalty for violating traffic rules at one signal, and he/she repeats the
same violation at another signal, when apprehended by the traffic police, he/she could show the penalty slip to
the cops and escape any additional penalty. This can be avoided through the automated system.
TThhee SPS can be implemented for the entire road network. There are many ways to identify traffic violations,
such as sudden lane switching, riding without helmets, parking violations, over-speeding, and more. This can be
a final solution for traffic control. Additionally, human resources can be diverted for other more important
purposes.
Solutions
SPS – Smart Penalty System
We recommend automating the existing traffic penalty system. The investments would only require placing
cameras at signals that are controlled by sensors (IR sensors). An organized database of all registered vehicles
along with owner details would help in more accurate automation.
Sensor Control Unit
IR
TXR
Camera Control
unit
Traffic Signal logic
controller
Traffic Signal
Figure 1: Penalty System block diagram
IR
RXR
Central Control
unit with
pattern
Recognition
Penalty
computation
and SMS
system
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5. Smart Penalty System (SPS) in Traffic Signals | 5
Figure 1 describes the penalty system. If any vehicle moves when the red signal is active, the IR sensor will
detect and trigger the camera, which takes a snapshot of the vehicle’s number plate. The pattern recognition
system identifies the vehicle number and finds the registration details. It can track previous violations too.
Based on this data, a reasonable penalty can be calculated and the information would be sent to the vehicle
owner’s mobile number.
We can implement this in 3 ways, and all of them provide different advantages.
Common CCTV cameras
ANPR cameras (HCL has an ANPR product)
Motion capture ANPR cameras
Each requires its own digital processing method and has different costs for the solution. Using Common CCTV
cameras is the minimum cost solution, where we might need to implement the entire plate recognition method
as follows:
Plate Orientation
Plate Localization Normalization
and Sizing
Penalty Search Engine
Triggering
System
Figure 2: Plate Recognition method
This can be used in cities with a normal traffic flow.
Character
Segmentation
Character
Recognition
Syntactial/Geo
Rule
Using ANPR cameras might increase the cost, but it is faster and requires less implementation costs. Motion
capture ANPR cameras can be used to detect vehicles that are over-speeding.
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6. Common Issues
Smart Penalty System (SPS) in Traffic Signals | 6
However, there are some practical limitations to implementing these methods effectively.
They require a reasonable investment for new camera sensor systems, making the system expensive
The system requires regular field checking for sensor performance
The recognition system must be highly reliable or it may lead to wrong results
Even though we do not need manpower in the traffic area, we do need them to monitor the data
captured through the SPS and effectively collect the penalties
TThhiiss system can be improved only if we implement it for all vehicles including government vehicles and
municipal buses, which present some complicated scenarios as to who will pay the penalties - the trans-port
department or the driver of the vehicle
This does not provide any solution for pedestrians who violate traffic rules
Conclusion
SPS goes a long way in automating the much needed vehicle traffic violation system. It has great potential to
increase compliance to traffic signals at intersections and to also do away with manpower, thereby eliminating
errors.
A smart red light violation detection system has been implemented in Trivandrum, Calicut, Kochi and Indore,
where cameras have been installed at signal intersections and automated slip-generation occurs. However,
people are able to receive these slips with captured picture evidence after a considerable time lag. The SPS can
eliminate time lags with an updated database and communications system that can send immediate messages
to the violating vehicle owner’s registered mobile number.
NNoowwaaddaayyss,, we have ALPR cameras (Automatic License Plate Recognition) and they can serve better than normal
CCTV cameras. Once the traffic is controlled at the signals, we can expand this to the entire city so that we can
monitor the entire road network.
But even if we are able to monitor the entire road network and control traffic by enforcing penalties through
automated systems like the SPS, the real control still lies with the person driving the vehicle!
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7. Smart Penalty System (SPS) in Traffic Signals | 7
Reference
1. ALPR - http://en.wikipedia.org/wiki/Automatic_number_plate_recognition
2. www.motorolasolutions.com/US-EN/Business+Product+and+
Sevices/Software+and+Applications/Public+Sector+Applications/Automatic%20License%20Plate%20Recognition_US-EN
3. ‘Real time number plate localization algorithms’ – Balazs Enyedi, Lajos Konyha and Kalman Fazekas.
4. ‘A Design flow for Robust License Plate Localization and Recognition in Complex scenes’ – Dhawal Wazalwar, Erdal Oruklu and
This whitepaper is published by HCL Engineering and R&D Services.
The views and opinions in this article are for informational purposes only and should not be considered as a substitute for professional
business advice. The use herein of any trademarks is not an assertion of ownership of such trademarks by HCL nor intended to imply
any association between HCL and lawful owners of such trademarks.
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Author Info
Ganesan C
HCL Engineering and R&D Services
Jafar Saniie.
55.. ‘‘SSeeggmmeennttaattiioonn MMeetthhooddss ffoorr CChhaarraacctteerr RReeccooggnniittiioonn:: FFrroomm SSeeggmmeennttaattiioonn ttoo DDooccuummeenntt SSttrruuccttuurree AAnnaallyyssiiss’’ –– HHiirroommiicchhii FFuujjiissaawwaa,,
Yasuaki Nakano and Kiyomichi Kurino.
6. ‘Automatic Number Plate Recognition System’ – Hakob Sarukhanyan, Souren Alaverdyan, and Grigor Petrosyan.