IoT in Smart Traffic Management

Running head: NETWORKING PROJECT
Networking Project
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Introduction:
Internet of Things or the IoT is considered as the network of the physical connected
devices that can communicate between themselves and can exchange the data. The IoT is a
very much important concept for the development of smart city. In the aspects of the smart
city the IoT plays a vital role for the development of the smart traffic control which is one of
the essential part of the smart city. For a city truly be a smart city must maintain a good
traffic flow and need to be free from the traffic jams. In this aspects the IoT can help to build
the smart city by effectively providing various of data to the peoples of the city. IoT can help
in the sense by connecting different drivers at the same network so that most efficient route
can be found for the drivers. For building a smart city various of areas need to be covered
which includes water management, public safety, reducing energy waste and creating an
effective traffic flow. In this report specific discussion will be done on the IoT in smart traffic
management.
Problem Domain and Research Question:
With the current growth rate of the population cities are becoming larger and with that
the traffic size of the city also becoming larger. Due to the fact congestion on the road is
increasing and the number of death and injuries regarding the road accidents is also
increasing due to the fact of increased number of traffic. Ambulances and the other
emergency cars is also facing problem due to the contestation on the road as they are failing
to reach to the destination within time. In this aspect the IoT can make the difference. IoT is
able to effectively manage the traffic so that it can move freely within the city. Thus it will be
able to minimise the contestation on the road. Also the IoT can help in this aspect to reduce
the total number of injuries and deaths regarding road accidents. This study is mainly focused

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on development of the smart city by implementing the smart city facility by using the IoT.
Thus in this aspect he main research question are:
 How the IoT is applicable in the automotive industry?
 How IoT can help to achieve smart traffic management system?
 Is the autonomous vehicles are optimal solution for a smaet traffic management?
Background and Objective:
Literature Review:
Article 1:
As per the authors Pawłowicz, Salach and Trybus (2018), smart city has become very
much popular concept in the present generation for managing the urban cities and areas
perfectly. In this concept of smart city the network of 5G plays an important role. It has been
assessed that with the prior advantages of 5G network the cloud infrastructure and the RFID
transponders can effectively create a traffic monitoring system for the urban cities. The main
aim of this type of system is helping the drivers to reach their destinations within an optimal
time. This traffic monitoring system will assist the driver to stick in a specific route so that
the drivers can avoid the traffic jams. Thus this system will also minimise the overall fuel
consumption and will improve the overall environmental conditions. For the electrical
vehicles this system will improve the level of battery power and will also improve the battery
consumption level by the vehicles. In this paper the authors has presented this traffic
management system. For the evaluation of this traffic management system the authors has
described various aspects of the system which includes parking space monitoring based on
the RFID, 5G communication services and the cloud services for an ultimate control over the
network monitoring system. Also, the machine learning has been characterised in this case.
Article 2:

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According to Levinson et al. (2011), autonomous driving is one of the most important
concept in the present scenario and currently several of organization are working on this topic
to invent an industry ready autonomous driving car. To achieve a vehicle which can perform
autonomous actions considering the urban situations like unpredictable traffic, several of real
time systems need to be incorporated. This includes environmental perception, planning,
localization and control. With this other factors need to be considered which includes a robust
vehicle platform with having some computational hardware, appropriate sensors, software
infrastructures and networking system. A reference can be taken from the 2007 DARPA
Urban Challenge which was a closed course race competition. Inciting and historic progress
has been seen on the race course regarding the autonomous vehicle operations, but this
cannot be taken as a full representation of the real world situation regarding the autonomous
driving. The authors has presented a summary of their recent researches aiming towards the
goal of developing autonomous cars for the realistic situations with that this autonomous
system needs safe enough to be executing in the real world situations.
The authors has assessed that a trio of unsupervised algorithms is able to calibrate 64-
beam rotating LIDAR with an accuracy comparable with the hand measurements. From this
the authors has generated some high resolution maps of the environment. This map has been
used for online localization purpose with having accuracy near centimetres. The algorithms
of recognition and an improved perception helps to classify and track obstacles. This
obstacles are assumed as pedestrians, vehicles and cyclist by this autonomous car driving
system. In this system the traffic light is also considered. The new planning system utilizes
the incoming data for generating many new candidate trajectories per second. Through this
optimal path has been chosen dynamically. The improved controller also plays an important
role in this case. In this section the improved controller continuously selects brake, throttle