Framework in Optimizing Traffic Congestion and Reduce Accidental Risk Using IoT and Neural Attention Models for Routing

Running head: RESEARCH PAPER
Research Paper
Topic: Framework in optimizing traffic congestion and reduce accidental risk using IoT and
neural attention models for routing
Name of the Student
Name of the University
Author Note

1
Abstract
Number of vehicles are growing each day and this is why traffic congestion occurs. This is a
huge issue and mostly all kinds of engineers are facing problems due to this in metropolitan
cities. A novel literature review is extracted in this chapter to analyze the frameworks in
optimizing traffic congestion and reduce accidental risk using IoT and neural attention
models for routing. These models would help in predicting the alternative and shortest routes
to the metro cities and once road congestion is predicted, a proactive vehicle rerouting
strategy based on global distance and local pheromone is employed to assign alternative
routes to selected vehicles before they enter congested roads.

2
Introduction
One of the most problematic situations around the entire world is the issues regarding
traffic congestion. The amount of transportation congestion has increased at such a level that
the reason was being studied. It was found that the primary reason behind this has been the
rapid increase in the number of vehicles so as it has been the number of populations. Since
this has been a problematic situation for the road commuters, it has been extremely essential
that a specific and effective solution is to be found so that the problems regarding the traffic
congestions can be reduced. Inclination to the technology and ease of travelling through
public and private transports is making the individuals spent more time on roads to travel
from one place to another and this is why, there have been several studies done and
techniques developed so that there might be a solution to the current situation (Alsrehin,
Klaib & Magableh, 2019). Based on these ideas, the following research would be evaluating
the different techniques used to control the transportation with the help of smart methods to
optimize the traffic congestions and at the same time reducing the risks of accidents with the
help of IoT. Several researches also focused on neural attention models for routing for
clearing out the road congestions and reducing traffic.
Literature Review/ Defining the problem context
The detailed description in this section would include the research papers by various
researchers who have already researched about the use of Artificial Intelligence in reducing
the transport congestions and making the transport commute a better occurrence. However,
before this, it is required that there are several areas that needs to be understood before the
implementation of Artificial Intelligence can be figured out. These are the issues and
challenges that are mostly faced by the people when in comes to the frequent congestion of
the vehicles on the roads nowadays.