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Systematic Review

Simulation framework for connected vehicles: a scoping review

[version 1; peer review: 2 approved with reservations]
PUBLISHED 09 Dec 2021
Author details Author details
OPEN PEER REVIEW
REVIEWER STATUS

This article is included in the Research Synergy Foundation gateway.

Abstract

Background: V2V (Vehicle-to-Vehicle) is a booming research field with a diverse set of services and applications. Most researchers rely on vehicular simulation tools to model traffic and road conditions and evaluate the performance of network protocols. We conducted a scoping review to consider simulators that have been reported in the literature based on successful implementation of V2V systems, tutorials, documentation, examples, and/or discussion groups.
Methods: Simulators that have limited information were not included. The selected simulators are described individually and compared based on their requirements and features, i.e., origin, traffic model, scalability, and traffic features. This scoping review was reported according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR). The review considered only research published in English (in journals and conference papers) completed after 2015. Further, three reviewers initiated the data extraction phase to retrieve information from the published papers.
Results: Most simulators can simulate system behaviour by modelling the events according to pre-defined scenarios. However, the main challenge faced is integrating the three components to simulate a road environment in either microscopic, macroscopic or mesoscopic models. These components include mobility generators, VANET simulators and network simulators. These simulators require the integration and synchronisation of the transportation domain and the communication domain. Simulation modelling can be run using a different types of simulators that are cost-effective and scalable for evaluating the performance of V2V systems in urban environments. In addition, we also considered the ability of the vehicular simulation tools to support wireless sensors.
Conclusions: The outcome of this study may reduce the time required for other researchers to work on other applications involving V2V systems and as a reference for the study and development of new traffic simulators.

Keywords

V2V, network simulator, mobility generator, simulations, connected vehicles, microscopic models

Introduction

In recent decades, a significant increase in vehicle use has increased traffic congestion and fatalities1. According to the World Health Organization, 1.25 million people are killed and severely injured involving vehicle accidents2. Hence, connected vehicle technology responds to this constraint, aiming to leverage inter-vehicle communication to produce safe, user-friendly, and fuel-efficient vehicle assistive technologies3,4. One of the main aspects of connected vehicle research is to optimise traffic flow through the exchange of information5. This communication can be sorted in terms of vehicle (V2V), infrastructure (V2I), a pedestrian (V2P), and network (V2N)6,7. The exchange of information, collectively known as V2X communications, could assist drivers in preventing accidents by providing warnings of danger invisible to drivers and other sensors (e.g. collision avoidance, lane departure warning and speed limit alert)8,9.

Nevertheless, the adoption of connected vehicle technology poses a range of challenges, particularly in urban environments. It is challenging to analyse the effectiveness of the application of connected vehicles under traffic conditions1012. As such, simulations using traffic and network simulators as well as mobility generators are viable alternatives to modelling and determining the effectiveness of such deployments in the real world13,14, as it provides an affordable and scalable method for analysing model compliance in various contexts and parameters.

Traffic simulations are categorised by level of detail into three separate categories15. First, the most precise information on each vehicle in the system is microscopic simulations16. Second, mesoscopic simulations exploit aggregate velocity-density functions to represent their behaviour and view traffic as a continuous stream of vehicles17. Finally, macroscopic simulation is the large-scale traffic model, which focuses on combined traffic status18. Microscopic simulations provide the highest degree of detail for modelling, although they are the slowest to execute19,20.

In addition, mobility generators are a possible option for modelling vehicle elements such as traffic, temporal and spatial mobility, and generating mobility traces21,22. These traces are then uploaded to a network simulator, which mimics vehicle-to-vehicle communication. Furthermore, these traces can be generated by observing real-world vehicles on the road and then used in network simulations23,24. The effect of network parameter modifications on traffic mobility is a strategic objective simulation25. It is also restricted to the use of the trace controlled by the mobility model. Another option is to use a simulator that directly integrates the mobility framework.

For Vehicular Adhoc Networks (VANET), it is necessary to rely on network protocols to assess their performance22,23, given that actual experiments are not possible. Over the last decade, efforts have been made to produce a full transport simulator for VANET solutions, including a wireless network simulator for modelling and evaluation24,25. A wide range of simulators can be used for VANET simulation modelling, both commercial and open source. Older simulators provide a network simulator to communicate with stationary mobility models. Many researchers have examined various mobility models with simulation tools for several contexts. Such simulator tools are not yet well explored since many researchers base their simulations depending on their use case settings. Thus, this motivates the identification of different simulators do not yet exist. Therefore, this study conducted a systematic scoping review to identify the applicability and availability of existing mobility generators, network simulators, and combination simulators.

Methods

A popular approach to synthesize research evidence which have no definitive procedure established is known as a scoping review. To conduct the review process, we adopted the PRISMA Extension for a Scoping Review26. The process involves determining the subjective and objective outcomes, identifying and selecting relevant studies, organising and summarising the findings, and reporting the outcomes (see Figure 1). Review questions were developed as follows:

  • 1. What are available mobility generators which are currently active in vehicle simulations?

  • 2. What is the criteria of network simulators commonly used in vehicle simulation active development?

  • 3. Which mobility networks and network simulators have been integrated to study vehicle communication protocols?

b1e03f49-8ee6-461d-9573-8dac274703d8_figure1.gif

Figure 1. PRISMA Flow Diagram.

Search, sources and inclusion criteria

Relevant studies were identified from IEEE and ScienceDirect, only including journal and conference papers with a published status. All searches were initiated in November 2019, and articles published in English starting from 2015 were considered for evaluation as our analysis of the literature shows that it is a relatively new but rapidly growing field of academic endeavour.

Controlled phrases and free-text word phrases related to vehicular communications that investigated V2V safety applications, vehicle network performance, driver behaviour, vehicle simulation tools, and VANET were considered for inclusion (see Box 1).

Mendeley was used to import the search results (www.mendeley.com) and remove duplicate articles.

Box 1. Search string

"VANET"

#1 AND Simulation

#1 AND #2 AND Simulators

#1 AND #2 AND #3 AND Routing

#1 AND #2 AND #3 AND #4 AND Mobility

#1 AND #2 AND #3 AND #4 AND #5 AND Urban

Screening

Once duplicate articles had been removed, further screening was performed at the title or abstract level based on the inclusion criteria. In addition, related technical reports were also included from Google Scholar. For confirmation, filtering (e.g. possible synonyms or other related terms) was also done at the full-text level afterwards. Citations of the articles included were searched for other relevant articles.

To facilitate the screening task, we imported the bibliographic citation file in RIS format from Mendeley into Rayyan (https://www.rayyan.ai/). Three reviewers (S.Y., A.A., and M.F.A.A.) were involved in the screening process to minimise bias and ensure the consistency of the selected articles. The first screening process ended in April 2020 and was later updated in January 2021.

Data extraction and analysis

All reviewers reviewed the same article and reports during the data extraction phase before collating their findings in an MS Excel spreadsheet. Data related to objective outcomes were collected from each included article wherever available, including year, type of traffic model, architecture and simulation language, type of network simulator, type of mobility generator, implementation or experimentation scenario and type of license. The spreadsheets were compared to ensure consistent data extraction by all reviewers. The contribution of the studies was further analysed based on descriptions provided in the publications paper to consider in our scoping review. In March 2021, the data extraction and analysis were finalised by consensus among the reviewers.

Results

A total of 269 publications were found initially. After removing duplicates, a total of 184 titles and abstracts were screened, from which 72 publications were subjected to full-text review after excluding those not of interest to this study. In total, ten studies and reports fulfilled the criteria for inclusion and were included in the analysis (see Figure 1).

We found that open-source mobility and network simulators were popular among researchers. Microscopic models were preferable for research related to vehicular communications since the simulations provide the most precise information of each vehicle or mobile node and the highest degree of detail for modelling compared to macroscopic and mesoscopic models. Common network simulators were NS-2, Ns-3 and OMNeT++. However, not all mobility simulators supported active development, which is important in current active research domains such as vehicular communications. The summary of mobility generators and network simulators found are in Table 1 and Table 2, respectively. A list of all ten studies can be found in Table 3.

Table 1. Mobility generators.

Reference(s)Name of
mobility
generator
Active
development
ReleaseLicenseMapTraffic modelNetwork simulator
2729SUMOY2021Open SourceReal and User
Defined
Microscopic
Mesoscopic
NS-2, NS-3, OMNeT++
3032MATSimY2021Open SourceReal and User
Defined
MicroscopicN/A
33DTALiteY2021Open SourceRealMesoscopicN/A
34,35SMARTSY2020Open SourceReal and User
Defined
MicroscopicN/A
21,36,37PARAMICSY2020CommercialReal and User
Defined
MicroscopicNS-2, OMNeT++
31,37MovSimY2018Open SourceBuilt-InMicroscopicN/A
21,38,39VISSIMY2016CommercialReal and User
Defined
Microscopic
Mesoscopic
NS-2, QualNet
40VNEtIntSimN2015Open SourceReal and User
Defined
MicroscopicIntegration OPNET
37TraffisimN2014Open SourceReal and User
Defined
MicroscopicN/A
41CityMobN2009Open SourceBuilt-InMicroscopic
Macroscopic
NS-2
41FreeSimN2008Open SourceRealMicroscopic
Macroscopic
N/A
41STRAWN2007Open SourceBuilt-InMicroscopicNS-2, SWANS
41Vanet-
MobiSim
N2007Open SourceReal and User
Defined
MicroscopicNS-2, QualNEt,
OMNeT++, GloMoSim

Y = Supported, N = Not Supported

Table 2. Network simulators.

Reference(s)Name of network
simulators
Active
development
ReleaseLicense802.11p
Support
Architecture
Language
Simulation
Language
42,43OPNETY2021CommercialYC++C++
OTCL
32,42,44NS-3Y2021Open SourceYC++
Python
C++
Python
42OMNeT++Y2020Open SourceYC++C++
32,42QualNetY2019CommercialYC++C++
42,45NS-2N2011Open SourceYC++C++
OTCL
32,42JiST/SWANSN2005Open SourceNJAVAJAVA
40,45GloMoSimN2000Open SourceNCC

Y = Supported, N = Not Supported

Table 3. Previous studies.

ReferenceContributionScenarioProtocol
Used
Mobility
Simulator
Network
Simulator
Simulator and
Framework
46This paper provides a comparison of three
routing protocols in the VANET scenario. The
result focuses on determining the effectiveness
of routing protocols for several performance
measures of which the vehicle is an essential
aspect of the evaluation.
UrbanDSDV
AODV
DSR
SUMO
MOVE
NS-2N/A
47The paper provides a simulation in the VANET
scenario at a vast scale. The result is focused
on the performance of four routing protocols
under different checks in terms of delay, packet
delivery, overhead, and transmission power.
UrbanOLSR
DSDV
AODV
DSR
SUMONS-3N/A
48This paper uncovers an automatic routing
protocol for the VANET scenario. The idea is
to disseminate the information provided by
several roadside units. There are three routing
protocols evaluated using several performance
metrics in terms of delay, number of hops, total
service time, and number of fragments.
UrbanARP GSR
A-STAR
SUMOOMNeT++N/A
49The paper focuses on two routing protocols
within the VANET scenario. The idea is to
ensure an optimal path from source to
destination under a few performance measures
in terms of throughput and packet delivery
ratio.
GenericDYMO
OLSR
N/AQualNetN/A
50This paper investigates DSRC 5.9 GHz for the
V2V scenario in restricted areas. The findings
were reviewed using three routing protocols
using different performance parameters in
terms of delay and number of forwarding
nodes.
GenericEMDV
>MHVB
EDB
N/ANetSimN/A
29The paper provides an analysis of four routing
protocols within the VANET scenario. The
outcome was assessed based on a different
mobility model and speed and performance
parameters such as goodput, throughput,
packet receive performance and receive rate.
UrbanOLSR
AODV
DSDV
DSR
SUMONS-3N/A
27This paper provides a comparison of three
routing protocols for the VANET scenario.
The results show the performance in the
transmission of critical information within
the framework of several performance
assessments in terms of goodput and packet
delivery ratio.
GenericOLSR
AODV
DSDV
SUMONS-3N/A
51The paper presents a fuzzy logic method to
improve the routing protocol in the VANET
scenario. The study demonstrated the
simulation by considering the number of
vehicles, the extent of the transmission, and
vehicle speed movement.
Urban
Generic
AODVSUMOOMNeT++N/A
52This paper uncovers a road recovery
mechanism in the VANET scenario. The study
improved the pathway to better message
delivery by considering mobility measures such
as relative speeds and relative distance.
GenericCLARR
CCBR
N/ANS-2N/A
53The paper examined two routing protocols
for better message dissemination in V2V and
V2I scenarios. The findings demonstrated
optimised routing under several performance
assessments like throughput, packet loss,
packet delivery report, and delay.
UrbanAODV
DSR
SUMON/ANetSim

N/A – Not Applied

Discussion

Since this area of study is considered as a relatively new but rapidly growing field, this scoping review process only considers relevant papers published from 2015 onwards, which shows that extensive research has been conducted to create security standards for communication technologies, particularly the vehicular network. Although various simulators can be enhanced with library extensions, none of the simulators is related to security and privacy. Ultimately, researchers and professionals cannot compare their security measures to a given circumstance. For instance, ensuring the privacy of a vehicular user in a fast-moving network and disseminating messages in a secure vehicular environment. However, there is no simple practice of extending existing simulators to the desired security standard, which implies that future development research will need to be done.

In addition, the quality of a simulation depends largely on the precision of the models. The range of precision has increased dramatically recently, where several modules contain signal attenuation components, multiple antenna models, and environmental interferences. However, one continuous barrier to producing accurate simulations is the evolution of rapid prototyping and its increasing use in-vehicle networks. For example, vehicle nodes would depend on three-dimensional scenarios to communicate with other nodes. It would be crucial for current and future simulators to extend the current simulators to these new conditions.

Integration with real-time system modelling based on non-real-time events creates additional challenges. Due to resource limitations, current simulators do not correspond with the physical properties of the hardware prototype while simulating a comprehensive network with multiple vehicles. Several alternatives have been put forward to reduce the complexity that could speed the simulation. However, this approach usually does not include indirect outcomes, which could seriously impact the behaviour of real-world network components. It is, therefore, necessary to examine the interconnection between simulators and hardware devices with the security standards concerned.

Conclusions

Studies have led to the discovery of comprehensive and realistic simulation tools due to the increasing popularity and interest for the future transportation system. This work has examined the current availability of simulators. Although several simulators have many features, it is worth exploring further the improvement of the simulators for specific scenarios.

Data availability

Underlying data

All data underlying the results are available as part of the article and no additional source data are required.

Reporting guidelines

Zenodo: PRISMA-ScR checklist for ‘Simulation framework for connected vehicles: a systematic review’, https://doi.org/10.5281/zenodo.563780254

Data are available under the terms of the Creative Commons Attribution 4.0 International license (CC-BY 4.0).

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Abdul Razak SF, Yogarayan S, Azman A et al. Simulation framework for connected vehicles: a scoping review [version 1; peer review: 2 approved with reservations]. F1000Research 2021, 10:1265 (https://doi.org/10.12688/f1000research.73398.1)
NOTE: If applicable, it is important to ensure the information in square brackets after the title is included in all citations of this article.
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Current Reviewer Status: ?
Key to Reviewer Statuses VIEW
ApprovedThe paper is scientifically sound in its current form and only minor, if any, improvements are suggested
Approved with reservations A number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.
Not approvedFundamental flaws in the paper seriously undermine the findings and conclusions
Version 1
VERSION 1
PUBLISHED 09 Dec 2021
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Reviewer Report 04 Jan 2023
Mahmoud Zaki Iskandarani, Al-Ahliyya Amman University, Amman, Jordan 
Approved with Reservations
VIEWS 15
The article attempts to produce a guidance into the most appropriate simulators for V2V, and in general V2X communications. This effort is a good effort and in the right direction in terms of what is witnessed of V2X developments under ... Continue reading
CITE
CITE
HOW TO CITE THIS REPORT
Iskandarani MZ. Reviewer Report For: Simulation framework for connected vehicles: a scoping review [version 1; peer review: 2 approved with reservations]. F1000Research 2021, 10:1265 (https://doi.org/10.5256/f1000research.77046.r158671)
NOTE: it is important to ensure the information in square brackets after the title is included in all citations of this article.
  • Author Response 16 Feb 2023
    Siti Fatimah Abdul Razak, Faculty of Information Science and Technology, Multimedia University, Ayer Keroh, 75450, Malaysia
    16 Feb 2023
    Author Response
    The applicability of V2V or V2I (V2X) has been added in Table 2 (page 7).

    The comparative analysis has been highlighted in Table 3 (page 7).

    The conclusion ... Continue reading
COMMENTS ON THIS REPORT
  • Author Response 16 Feb 2023
    Siti Fatimah Abdul Razak, Faculty of Information Science and Technology, Multimedia University, Ayer Keroh, 75450, Malaysia
    16 Feb 2023
    Author Response
    The applicability of V2V or V2I (V2X) has been added in Table 2 (page 7).

    The comparative analysis has been highlighted in Table 3 (page 7).

    The conclusion ... Continue reading
Views
28
Cite
Reviewer Report 19 Jul 2022
Lionel Nkenyereye, Department of Computer and Information Security, Sejong University, Seoul, South Korea 
Approved with Reservations
VIEWS 28
The study surveys the existing simulation framework for connected vehicles. The works proposed a method based on PRISMA Extension for a Scoping Review. The previous study table is short but relevant contributions are presented. These contributions summarize the routing concept, dissemination of ... Continue reading
CITE
CITE
HOW TO CITE THIS REPORT
Nkenyereye L. Reviewer Report For: Simulation framework for connected vehicles: a scoping review [version 1; peer review: 2 approved with reservations]. F1000Research 2021, 10:1265 (https://doi.org/10.5256/f1000research.77046.r143137)
NOTE: it is important to ensure the information in square brackets after the title is included in all citations of this article.
  • Author Response 16 Feb 2023
    Siti Fatimah Abdul Razak, Faculty of Information Science and Technology, Multimedia University, Ayer Keroh, 75450, Malaysia
    16 Feb 2023
    Author Response
    The paper is mainly focusing on VANET deployment. The introduction has been revised as suggested (page 2 and 3). 

    The conclusion has been revised to specify the type of mobility ... Continue reading
COMMENTS ON THIS REPORT
  • Author Response 16 Feb 2023
    Siti Fatimah Abdul Razak, Faculty of Information Science and Technology, Multimedia University, Ayer Keroh, 75450, Malaysia
    16 Feb 2023
    Author Response
    The paper is mainly focusing on VANET deployment. The introduction has been revised as suggested (page 2 and 3). 

    The conclusion has been revised to specify the type of mobility ... Continue reading

Comments on this article Comments (0)

Version 2
VERSION 2 PUBLISHED 09 Dec 2021
Comment
Alongside their report, reviewers assign a status to the article:
Approved - the paper is scientifically sound in its current form and only minor, if any, improvements are suggested
Approved with reservations - A number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.
Not approved - fundamental flaws in the paper seriously undermine the findings and conclusions
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