VANET-based traffic monitoring and incident detection system: A review

International Journal of Electrical and Computer Engineering (IJECE)
Vol. 11, No. 4, August 2021, pp. 3193~3200
ISSN: 2088-8708, DOI: 10.11591/ijece.v11i4.pp3193-3200  3193
Journal homepage: http://ijece.iaescore.com
VANET-based traffic monitoring and incident detection system:
A review
Mustafa Maad Hamdi1
, Lukman Audah2
, Sami Abduljabbar Rashid3
, Sameer Alani4
1,2,3
Faculty of Electrical and Electronic Engineering, Universiti Tun Hussein Onn Malaysia, Batu Pahat, Johor, Malaysia
4
Faculty of Information and Communication Technology, Universiti Teknikal Malaysia Melaka, Durian Tunggal,
Melaka, Malaysia
Article Info ABSTRACT
Article history:
Received Jul 9, 2020
Revised Mar 11, 2021
Accepted Mar 21, 2021
As a component of intelligent transport systems (ITS), vehicular ad hoc
network (VANET), which is a subform of manet, has been identified. It is
established on the roads based on available vehicles and supporting road
infrastructure, such as base stations. An accident can be defined as any
activity in the environment that may be harmful to human life or dangerous
to human life. In terms of early detection, and broadcast delay. VANET has
shown various problems. The available technologies for incident detection
and the corresponding algorithms for processing. The present problem and
challenges of incident detection in VANET technology are discussed in this
paper. The paper also reviews the recently proposed methods for early
incident techniques and studies them.
Keywords:
Early detection
Incident detection
Incident management
Traffic monitoring centre
VANET This is an open access article under the CC BY-SA license.
Corresponding Author:
Lukman Audah
Faculty of Electrical and Electronic Engineering
Universiti Tun Hussein Onn Malaysia
86400 Parit Raja, Batu Pahat, Johor, Malaysia
Email: hanif@uthm.edu.my
1. INTRODUCTION
Nowadays, network technology is rapidly developing and widely applied. Vehicular ad hoc network
(VANET) is a technology that uses cars as mobile nodes in mobile ad-hoc network (MANET) [1]. VANET
converts all participating cars into a router or wireless node, allowing cars 100 to 300 meters away to connect
to an extensive network. Because cars are out of the signal range and out of network, other cars can connect
and connect vehicles to create a mobile internetwork as shown in Figure 1. VANET is a sophisticated
technology that integrates ad hoc networks, wireless LANs, mobile technology, and sensor networks to
provide advanced intelligent communications between vehicles, roadside sensors, and infrastructure [2].
VANETs are self-organizing and decentralized systems. VANET enables dedicated short-range communication
(DSRC) of vehicles in the 5.9 GHz band through the IEEE 802.11 p standard. Moreover, VANET has a
different scenario of communications such as vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I)
communications for near and remote environments. Recently, VANET has been widely used in intelligent
transportation systems (ITS) applications. Therefore, VANET is a technology that enables the integration of a
single framework for conventional ITS applications [3].
The basic idea of the ITS environment is to use VANET technology to communicate vehicles to
each other and communicate the infrastructure of the roadside unit to share information through the network.
In safety applications and user applications, ITS applications can be divided. The number of traffic accidents
will be significantly decreased, with the consequence that 60% of incidents could be prevented if the driver

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were warned within 0.5 seconds of the collision. Throughout the meantime, safety applications may be used
to alert drivers that the path to the next is too close. According to the US department of transportation, 45%
of all registered cars and 21% of road accidents accounted for accidents at intersections in 2003 [4]. VANET
can control the rate of data dissemination, which facilitates the transmission of only relevant data (for
example, the traffic status of nearby roads) to each vehicle and send data to the traffic monitoring centre
(TMC) [5]. Since traffic data can be distributed by multiple hops broadcasting, remote managers are likely to
receive traffic data well in advance. This allows the driver to respond to the traffic information they receive
in traffic monitoring [6]. Different scenarios will happen and affect the flow of data to TMC, such as wither
conditions, accidents, and rush hours. These incidents will impact traffic flow and influence system
performance. Hence, a new incident technique is required to be built in such a system [7]. Collecting data and
detect incidents in ITS can be done by different techniques that we will discuss in the next section. An early
warning performs frequent surveys when road accidents occur and produce alerts providing concise
information about the type of accident designation. A method of accident prediction attempts to identify an
unexpected event and its location as quickly as reliably as possible automatically [8]. However, identifying
non-blocking collisions and incidents under light load is still a challenge as a difference from standard
patterns of traffic may be negligible. Therefore, the limitations are that most of these algorithms do not know
exactly when or what occurred [9]. We organized this paper as follow: Section 2, present all issue and
challenges that implemented in incident detection and showing the points of the strength and weakness to all
of them. In section 3, we will explain the recent advancement in the early incident detection system and
summary of existing related work done in the past with the conclusion of this paper.
Figure 1. VANET model [10]
2. ISSUE AND CHALLENGES IN INCIDENT DETECTION
Road incidents can be made up of many factors; some are (somehow) predictable, such as road
construction, rush hour, and others are unpredictable, such as accidents, weather conditions, human behavior,
and other unusual or special events affecting roadways. Without having any prior information to the drivers,
road accidents, traffic congestion, and other road incidents are the most serious possible problem. As a result,
the more serious the incident, the longer it will take to rectify it once the cause has been eliminated or
repaired. During an incident, normal road capacity is limited, and there are often queues and delays, like in
case of traffic congestions. Incidents are primarily responsible for delays and have far-reaching consequences
for safety, congestion, pollution, and travel costs [11]. Earlier research has shown that incidents are one of
the main causes of lost time and the increase in avoidable costs for transportation networks [12].
 The irrelevancy of incident information: Only relevant information should be provided to drivers.
Independent and unnecessary information should be filtered out. This includes using accurate information
dissemination. In many cases, irrelevant information transmitted by encircled vehicles or the detector
node has a significant impact on traffic management. There have been cases where false alarms have been
activated, and the same information has been transmitted to every node in the vehicle, which changes the
direction of the traffic and obstructs the unnecessary traffic at the roadside, which complicates the ITS
system. Therefore, the information to be transmitted to vehicles is an important aspect of the detection of
VANET-based incidents in ITS.

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VANET-based traffic monitoring and incident detection system: A review (Mustafa Maad Hamdi)
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 Real-time inaccessibility of information: Traffic information must be accessible in real-time. In other
words, the necessary traffic information must be available to high-speed drivers. It is often the case that
information transmitted by a sensor or vehicle node arrives late at other nodes. In many cases, when an
emergency alert is required to prevent fatal accidents, it is transmitted late and causes an undesired
accident. Therefore, access to real-time information is critical in VANET-based ITS.
Detecting and managing incidents offers better traffic monitoring. Many forms of traffic monitoring
can detect an incident. The current techniques of the incident detection such as inductive loop detectors,
video detection system, microwave radar sensors, automatic vehicle identification, automatic vehicle
location, and wireless location technology. Table 1 present the points of strength and weakness for
techniques implemented in incident detection.
Table 1. Simulation parameters for the baseline
Technique Strength Limitation Characteristics
Inductive loop detectors Data for traffic with
volume, occupancy.
Maintenance, Installation,
and replacement of ILDs.
Intrusive, comprising a wire coiled.
Video detection system A single controller a
combination of cameras.
Some periodic maintenance. Non-intrusive, Software for image
and camera processing.
Microwave radar sensors Measure speed directly. Accuracy is not good. Non-intrusive
Automatic vehicle
identification
Provide effective vehicles
with data collection.
Include important
infrastructure on the roads.
Non-intrusive
Automatic vehicle location Few fixed infrastructure
components are
necessary.
Sample size limitations. Relies on a global positioning system
(GPS) data.
Wireless location
Technology
Some vehicle owners
include cell phones.
Produce reliable speed and
travel time measurements.
The use of cell phones is mainly
based on vehicles.
3. RECENT ADVANCEMENT IN EARLY INCIDENT DETECTION SYSTEM
In the past, many attempts have been made to invent an early incident detection system that can
detect errors in intelligent transport systems as quickly as possible, to provide people with accurate primary
information about alert data, and possible response times to resistance. The measures adopted to develop
these systems took into account; i) the information on the accident is irrelevant drivers should only be given
the applicable information. Non-relevant and redundant information should be provided. This includes the
dissemination of accurate information, ii) the inaccessibility of information in real-time traffic information
must be immediately accessible. In other words, basic traffic information should be accessible to drivers at
high speed and iii) No timely information available Road accident information should be made available to
drivers as soon as possible so that they have sufficient time to act (for example, to make a decision ahead or
at the beginning). However, the implementation of the existing system could hardly produce these desirable
properties. These features can save time in obtaining information on expected road accidents alongside end-
user fuel. The following section discusses different research studies to develop an early incident detection
system. Baiocchi et al. [5] have developed a traffic flow estimation method with GPS data and promising
performance. Hojati et al. [13] have provided a model to estimate the time interval between accidents and
clean-up based on road and infrastructure differences. Even IT technology has been included in traffic,
incident detection, and more. The neural networks [14], supporting vector machines [15] or hidden Markov
models [16] are used in these studies. In a study, Lee et al. [17] evaluated the quality of exploited data
collected mostly through various roadside sensors. They pointed out that reliable and error-free data was
difficult to obtain. He suggested the use of Microwave Sensors (RTSS) to obtain more reliable traffic data for
traffic management systems and provided several examples in Ontario. He also introduced methods for
identifying these mistakes and evaluating such models with real data. Masters et al. [18] analyzed the
integrated Toronto COMPASS traffic accident detection system based on distance, road use, and speed
parameters to detect data anomalies.
Feng et al. [19] calculated the corresponding data using the Bayes model to calculate the average
travel time. Pascale et al. [20] focused on calculating road capacity and suggested increasing efficiency.
Some studies process images and videos based on data from CCTV cameras [21]. The consequence of these
systems is the ability to monitor various vehicles and their activities. Ad hoc vehicle networks are also
utilized in traffic data grouping models [22], but communication and data transmission are not particularly
easy in various road situations. Researchers also analyze the flow of traffic and incidents detection. The
researcher [23] presented the architectural prototype e-NOTIFICATION, a new proposal aimed at improving
the survival chances of passengers involved in road accidents. By using the automotive information
infrastructure systems, the planned device immediately identifies warnings and assists, incident passengers.
This method is built to include; i) a car immediately involved in an incident; ii) the automated transmission of

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the file containing important crash details for controlling onboard devices; and, iii) a summary and automated
classification, depending on information appropriate to the vehicles affected, of the losses incurred by the
automobile and its occupants; The system decides on the rescue services needed to maximize support in the
event of an accident, based on transmitted information and the approximate estimation of accidents.
The method aims at having the vehicle's location from the GPS receiver, transmitting the location
data from SMS to the mobile number of the vehicle owner, and through GPRS to the telematic operator's
server. It comprises modules; i) that require a GPS transmitter for accurate GPS GSM/GPRS satellite details;
ii) The GSM/GPRS modem transfers incident position information and other information through the GSM
network. The modem can be controlled using the AT commands using a microcontroller; iii) The GPS data is
received, all data are analyzed, and a vehicle location is transmitted to the owner and server by the
microcontroller (MCU). The scientists have suggested a safety prototype [24]. The main aim is the development
of some various programs which would affect the comprehensive application and preparation of the ITS
cooperatives. This also seeks to facilitate the introduction of European road cooperation programs, focusing
on all issues relating to connectivity between V2V and vehicle infrastructure (V2I). The initiative aims to
promote the establishment of cooperation structures on European roads. In another work carried out in [25],
with a proposed automatic accident prevention system and a safety system using the integrated GSM
interface, this designed system is automatic collision detection and warning system, from the GPS module
and a GSM using a modem. A reliable scheme must ensure successful mechanical interaction with the entire
structure of the vehicle to be secured. Throughout the case of a crash, the device can sense a rapid
deceleration of the car. The accelerometer measures vehicle speed continuously, detects speeds beyond the
threshold and transmits information through ADC to the microcontroller. The controller contrasts this with a
collection of thresholds and delivers the pre-defined numbers automatically to the SOS message. This
communication also conveys the GPS co-ordination for the vehicle, which it receives from the GPS module
on a continuing process. This device can be a great benefit to find and save vehicles for accidents.
Other authors [26] have implemented a working incident prevention system and a GPS and GSM
modem messaging framework. This research aims to recognize the condition of the car accident by
transmitting a message through the vehicle network. The main challenge is to preserve vehicle protection at
very reasonable costs. The main benefit of this check is that when the detector is activated, the GSM modem
is detected immediately on the cell phone numbers stored in the EEPROM. This device reliably determines the
incident location, automates the occurrence detection and communications method. The researchers from [27]
proposed an emergency call notification system via the Internet of Things and the cloud. The proposed
system has been Implemented using the XBee WiFi module, Xbee Shield, GPS module, Seeeduino, and the
shock sensors. The basic idea is to use shock sensors to discover an accident, identify the exact location of
the accident, and transmit the location coordinates via XBee WiFi to the nearest hospital via the cloud. The
aim was to suggest a system that would enable the Internet and the cloud to be connected abroad. Given the
above limitations, the framework represents a move forward to encourage participation in the broader
Internet of Things process. Data may be transmitted over long distances utilizing the application in the cloud.
This functionality may be further improved by designing the device to notify the victim's immediate family.
In another work [28], a prototype system specifically designed to detect and render quick resources to victims
of road accidents. The system requires that each vehicle be equipped with a control unit (CU) and an onboard
unit (OBU), which indicates the location of the accident to provide the rescue operation with the necessary
resources. The proposed system allows for the identification of road accidents to improve assistance to
injured passengers by reducing the response time of emergency services by effectively communicating
information on major accidents. The above section discusses the various related works and methods applied
to the system and techniques for the early detection of incidents. The following section summarizes the
researchers' current work in this area, as shown in Table 2 (see in Appendix).
4. CONCLUSION
This review paper provides an exhaustive study of existing incident detection techniques. Current
techniques have been studied based on traffic monitoring and incident detection. The paper presented a
relative study on roadways incident detection methods in terms of working with the pros and cons. Also,
proprietary incident detection techniques have been explored to determine applications for incident detection
and management. The review paper presented a comprehensive overview of field related research work.
However, the literature has provided a systematic overview of related work such as traffic monitoring
techniques, incident detection methods, VANET data dissemination, VANET safety, and traffic data. The
study compared all available accident detection techniques and presented a comparative study of strength and
weakness related to available incident detection techniques.

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APPENDIX
Table 2. Summary of existing related work done in the past
Authors Proposed scheme methodology Issues identified Benefits Simulation tool
[29] A new model for the dissemination of data
based on Clustering and Probabilistic
Broadcasting (CPB).
Frequent changes in topology
due to increasing node mobility.
Efficient utilization of
communication modes.
NS-3, SUMO
[30] An emergency message dissemination system
based on the VANET and FoG vehicle
technology congestion reduction scenario.
The speed, direction, and
density of the moving neighbors
are not compatible.
Reduces accessibility
delays and congestion.
MATLAB
[31] A modeling language based on the actor is used
and fitted with various model control engines.
Frameworks focused on
simulations cannot have assured
analyses.
Behavior and
performance were
outstanding.
Afra -modeling and
verification IDE
[32] The approach suggested is based on the concept
of a supernode for timely communication.
Moreover, the time barrier strategy is modified
to deal with this issue to prevent the
unnecessary broadcast, which can also cause
the diffusion storm.
Broadcast congestion or partial
broadcast.
Overhead message
reduction, transmitting
latency, better
coverage, and packet
delivery ratio.
OMNeT++, SUMO
[33] Vehicles are dynamically clustered to tackle the
storm issue and a location-based strategy aimed
at reducing communication gaps is proposed
that emergency messages are disseminated in
time.
The frequently changed network
topology contributing to
network instability is caused by
high mobility in-vehicle
networks.
Increased transmission
latency, coverage, and
delivery of packets.
OMNeT++, VEINS,
and SUMO
[34] A new security-related communications
protocol based on the non-redundant
Communication Range (NRCR, for short),
which can manage safety-relevant multi-hop
messages broadcast within the non-isomeric
area of communication vehicle scenario,
specifically heterogeneous VANET topology.
Effective messages broadcast
related to safety.
The protocol is perfect
for packet receiving
ratio, end-to-end delay,
and overhead network.
NS-2, SUMO
[35] A new technique to improve VANET
dissemination systems to prevent further cases
of emergencies and hazards by utilizing a
heuristic, fast and real-time method.
Network efficiency, based on
several variables including
bandwidth consumption,
transmission latency, and
quality of service (QoS).
Improved performance
of cluster duration,
delivery rate, and the
overhead.
NS3, VEINS, and
SUMO
[36] Across layer autonomous route recovery
(CLARR) system for enhancing routing activity
by decreasing the connectivity breaks for the
increased multimedia dissemination of data.
High-speed vehicles often
interrupted connections and loss
of data packets at minimum
latency.
The overall delay is
highly improved
efficiency.
NS3, SUMO
[37] A reliable emergency message dissemination
(REMD) framework is suggested which ensures
a pre-defined reliability of messages
dissemination in a variety of channel conditions
while serving the delay requirements.
Recent emergency message
dissemination schemes do not
reach pre-defined loss channel
reliability.
REMD satisfies latency
requirements.
NS3, VEINS, and
SUMO
[38] A method for the dissemination of performance
safety messages and detailed physical channel
synchronization measurements are suggested
for the connection. The organization of conflict
between CFs is suggested through a score-
based priority allocation mechanism for
candidate forwarders (CFs).
Signal propagation is highly
enhanced by obstacles at
intersections in specific.
The method exceeds
existing schemes for
multi-hop broadcasting.
OMNeT++, VEINS,
and SUMO
[39] Also, to ensure efficient bandwidth utilization,
the warning message scheme has been
developed for low priority messages. During
harsh weather conditions, the network provides
the highest high and low priority messaging.
The processing speed of drivers
as such conditions arise.
Message delay dissemination.
The efficient utilization
of bandwidth is less
delayed.
NS-2.34
[40] When the unexpected behavior is detected by
the RSU, send an EM message to all the
vehicles that are inside the RSU network. To
avoid traffic collisions, an EW message will be
received at the same moment.
Warning messages are timely.
The message broadcast was
delayed.
Low delay. NS-2.0
[41] The car selects the best carrier and
communicates the emergency message. The
transmitting of the emergency message to the
RSU by the transmitter vehicle.
The probability of accidents to
determine communication with
messages in VANETs.
Fewer overhead
message.
MATLAB, R2011b
Version
[42] The emergency message is broadcast by an
RSU to the other RSUs in its network. It
prevents an emergency message from
duplicating. Such messages enable the driver to
select a different route to prevent accidents.
Distribution of network capacity
broadcast-storm issue Network
congestion detection.
High throughput. End-
to-end High delivery
rate of the packet
NS-2.0

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Table 2. Summary of existing related work done in the past (continue)
Authors Proposed scheme methodology Issues identified Benefits Simulation tool
[43] The message is secured by all vehicles in the
cluster to provide specific information. A traffic
accident in the same cluster is identified and
incident information is transmitted to the other
of the cluster vehicles.
Simple Flooding. Transmission range
cluster size. Driver
reaction time.
SUMO, OMNET++
VEINS, Clustering
Algorithm
Techniques
[44] The drivers of vehicles have the intensity and
location of the vehicle when the traffic
congestion has been detected. The vehicle
affected by the incident transmits the warning
message to the RSU.
Bandwidth efficiency
transmission. Traffic detection
congestion. Transmission.
Efficient utilization of
bandwidth Low
overhead message
Net Beans IDE 7.0
Java
ACKNOWLEDGEMENTS
The authors would like to thank the Research Management Cntre (RMC), Universiti Tun Hussein
Onn Malaysia for the generous financial support under the RMC Research Fun (E15501).
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 ISSN: 2088-8708
3200
BIOGRAPHIES OF AUTHORS
Mustafa Maad Hamdi was born in Al-Anbar, Iraq. He received the B.Eng. degree in Computer
Engineering Technology from Al-Maarif University College, Iraq. And the M.Sc. degree in
Communication and Computer Engineering from University Kebangsaan Malaysia (UKM),
Malaysia. He is currently pursuing the Ph.D. degree in the department of communication
engineering, University Tun Hussein Onn Malaysia (UTHM), Malaysia. His research interests include
Wireless and Mobile Communications, VANET, MANET, and satellite Communication, and
Cryptographics.
Lukman Audah was born in Kuala Lumpur, Malaysia. He received the B.Eng. degree in
telecommunications from Universiti Teknologi Malaysia, in 2005, and the M.Sc. degree in
communication networks and software and the Ph.D. degree in electronic engineering from the
university of Surrey, U.K. He is currently a lecturer with the communication engineering
Department, University Tun Hussein Onn Malaysia. His research interests include wireless and
Mobile Communications, Internet Traffic Engineering, Network System Management, Data Security,
and Satellite Communication.
Sami Abduljabbar Rashid was born in Al-Anbar, Iraq. He received the B.Eng. degree in
computer engineering technology from Al-Maarif University College, Iraq, and the M.Sc. degree
in communication and computer engineering from University Kebangsaan Malaysia (UKM),
Malaysia. He is currently pursuing the Ph.D. degree in the department of communication
engineering, University Tun Hussein Onn Malaysia (UTHM), Malaysia. His research interests
include wireless and mobile communications and VANET.
Sameer Alani was born in Iraq, in 1989. He received the B.S. degree in computer engineering
and the M.Sc. degree in wireless communication and Computer networking technology from The
Universiti Kebangsaan Malaysia (UKM), in 2017. He is currently pursuing the Ph.D. degree in
wireless communication and networking. His research interests include antenna applications,
wireless communication, and networking Technology.

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