Index


Figures


Tables

An , Lee , Jang , Lim , Shin , Jang , Jang , and Yoon: Experimental Assessment of 5G-NR-V2X in a Real-life Highway

Byoungman An♦, Jimin Lee*, Seonghyun Jang*, Kitage Lim*, Daekyo Shin*, Soohyun Jang*, Junhyek Jang*, Sanghun Yoon°

Experimental Assessment of 5G-NR-V2X in a Real-life Highway

Abstract: This paper provides a comprehensive analysis of the practical assessment of 5G-NR-V2X technology in both an actual highway and a controlled testing facility. We propose a method designed to assess and verify the efficiency of self-driving services within a real-world road test environment, utilizing on-board and roadside units for 5G-NR-V2X communication. The evaluation required a minimum automation level of 4, a significantly high speed (150 Mbps or greater), minimal latency (3 ms or less), and a high degree of dependability (99.99%) to guarantee resilient communication even in hostile scenarios. This paper presents the 5G-NR-V2X communication system alongside its experimental evaluation, aiming to enhance V2X communication technologies known for their high speed, low latency, and reliable performance. Moreover, the proposed performance analysis technique is expected to enhance the technical competitiveness of road, transportation, logistics, and commerce industries by verifying services and testing hypothetical situations.

Keywords: V2X , 5G-NR-V2X , Self-driving , Communication , OBU , RSU , Autonomous Driving

Ⅰ. Introduction

The extensive use of automobiles as a mode of transportation in contemporary society has both positive and negative implications, including the potential to compromise road safety. The development of vehicle- to-everything (V2X) technology can be linked to progress in the Internet of Things (IoT). This technology aims to create links between automobiles, transportation infrastructure, pedestrians, and cloud platforms using various devices, including on-board units (OBUs) and roadside units (RSUs). The primary objective of V2X is to enhance road safety[1-5]. V2X facilitates the transmission of information and provides extensive driving solutions on a global scale through wireless connectivity and advanced processing technologies. Integrating intelligent decision-making and vehicle management systems can efficiently reduce traffic congestion, enhance driving efficiency, and improve road safety. Vehicles generate a significant amount of data to fulfill V2X requirements and address road safety concerns[6]. This data are essential for V2X communication and play a significant role in the development of future autonomous vehicles by providing vital driving information. Similarly, the consistent and precise transmission of V2X messages play a crucial role in ensuring safety. However, the spreading of false messages, whether intentional or unintentional, can cause confusion and even catastrophe among other drivers. Therefore, assessment of data precision in V2X communication is of substantial practical importance.

The existing global standards are outlined below. The 3rd Generation Partnership Project (3GPP) finalized the specifications for long-term evolution (LTE) vehicle communication (Rel.14) in March 2017. This achievement established the basis for the extensive adoption of vehicle communication by significantly reducing communication delays using LTE technology and enabling direct connections between vehicles. The 5G-NR-V2X (Rel.16) standard was formally introduced in July 2020, marking another key development in this field.

Modern communication technology is characterized by its ability to achieve extremely low latency, large capacity, and excellent reliability[7]. The deployment of new services required to achieve the Fourth Industrial Revolution is supported by 3GPP Release 17, which builds upon the established 5G advanced standards. These standards encompass all the requirements imposed by the commercialization process[8,9].

The 5G Automotive Association (5GAA) recently developed detailed definitions and requirements for several V2X cases. In addition, the association defined several innovative and groundbreaking applications across various categories. The radio layer standards are governed by the 3GPP, which is currently working on developing Release 18. This project, expected to be completed by the end of 2023, will incorporate further enhancements for V2X.

Regional standard development groups, such as ETSI, SAE International, NTCAS, C-SAE, and ARIB, are responsible for standardizing the higher layers of communication. This effort is in response to the need for further investigation of profiles and protocols in emerging advanced application scenarios, such as group initiation. The ISO has launched standardization efforts for automated valve parking in Europe and other regions. Advancements in technology, such as improved location, reduced power consumption, and the implementation of multiaccess edge computing, provide connected assistance and cooperative driving services. These advancements have been made possible through ongoing global standardization efforts and the introduction of the 3GPP 5G-V2X. The revised edition of the Roadmap has been shaped by a heightened comprehension of the software (SW) complexity and the need for cooperation within the system. Network-based solutions have been explored as potential methods for increasing awareness among vulnerable road users. Furthermore, the incorporation of certain safety measures and sophisticated autonomous driving scenarios, such as collective initiation and collaborative movements, will require additional time[10,11].

· Safety: Safety procedures, including emergency braking, junction management, collision warning, and lane changes, are equally applicable to autonomous vehicles and driver assistance systems.

· Self-driving: The use of cases for autonomous vehicle levels 4 and 5 provided valuable insights into the specific circumstances in which autonomous driving was considered acceptable. These cases emphasize the significance of effective and secure control systems, remote driving capabilities, dynamic mapping, and collaborative interactions among vehicles.

· Platooning service: Platooning involves collaboration between transport corporations, road operators, and road traffic authorities to implement strategies such as cluster driving management and cluster driving stability. These strategies are designed to improve the efficiency of infrastructure usage and achieve environmental advantages such as reducing emissions.

The remainder of this paper is organized as follows: Section II provides a thorough overview of the current research and commercially available methods related to the architecture of 5G-NR- V2X. This section also covers the message format used to create a link between cars and the infrastructure. In Section III, we present an experimental test approach for evaluating 5G-NR-V2X. In addition, we provide specific and useful details and analyze examples of data structures that would benefit from resource sharing among various devices. Section IV outlines the methodology for evaluating the communication efficiency of 5G-NR-V2X. The paper concludes by discussing the challenges that arise during the implementation of the proposed approach.

Ⅱ. 5G-NR-V2X Architecture and Message Formats

2.1 5G-NR-V2X Architecture

This section explores various methodologies to optimize interactions and facilitate the exchange of data between V2X automobile devices and the infrastructure. Our study aims to ensure continuous connectivity while maintaining the full functionality of V2X stacks and SDKs provided by V2X device manufacturers or in compliance with international safety standards. The essential components of the V2X communication equipment are described below.

· OBUs are transceivers installed on vehicles that collect data and instantaneously transmit it to other interconnected vehicles or RSUs.

· RSUs are fixed communication nodes positioned along roads that can exchange data with other OBUs in passing vehicles and relay the data to a centralized station.

· Control units act as intermediaries between the control center and research support units (RSUs). Considering the fundamental characteristics of the RSUs, they are likely to be mounted on the top part of the telephone pole alongside the antenna, function as mechanisms that control and coordinate RSUs operations. The presence of this equipment depends on the prevailing circumstances.

· Figure 1 presents a comprehensive depiction of the structure of the 5G-NR-V2X system, which comprises three separate systems: OBU/RSU system, and the 5G-NR-V2X modem IP system. Each system has specific roles and functions. The application system consists of five layers. The application layer comprises a service that employs a command line interface to perform real-time basic unit testing and debugging. In addition, it includes an application service that utilizes a graphical user interface (GUI) to display real- time graphical results. These scenarios are limited to the service-layer domain. Additional services, such as the service layer shown in Figure 1, can also be integrated. Examples of such services include platooning and analysis. The message layer is tasked with packetizing the V2X message data to meet the application service requirements. The SDK layer, as described in the previous section, plays a crucial role in the functionality of the system.

The OBU/RSU system consists of three separate layers: the application, SW stack, and hardware (HW). The application layer is responsible for managing the HW components of the device and facilitating communication with the application processor (AP) of the application service. The SW stack comprises 5G-NR-V2X SW for linking and 5G Uu operating SW. Moreover, the LTE-V2X operating SW and LTE-V2X SW stack guarantee backward compatibility as long as they are supported by the modem IP or configured as a separate LTE modem IP. The HW can function as either a 5G Uu or LTE-V2X modem within the OBU/RSU device, or it can create a link between the device and external environment. Figure 1 illustrates the setup consisting of an internal 5G Uu and LTE-V2X modem, as well as an external 5G-NR-V2X modem IP system. Currently, Qualcomm, AutoTalks, and Ettifos are collaborating on the development of the 5G-NR-V2X modem. The aim is to combine modern IP with Ethernet, allowing for the installation of various modems in the order they were initially released prior to their commercial availability[12].

Fig. 1.

Structure of 5G-NR-V2X communication performance verification system.
1.png
2.2 Message Formats

The 5G-NR-V2X message format was established as a scalable service-oriented V2X) message structure to validate extremely fast and reliable communication performance in both safety and nonsafety applications. The details of this message format are listed in Table 1. Using the recommended framework, we can determine the credibility of specific situations, such as platooning, sensor-sharing, remote driving, and advanced driving services. Furthermore, Figure 2 illustrates the proposed extensible message structure that incorporates the single-sign-on vehicle (SSOV) data format to validate the V2X performance[13].

Fig. 2.

Extensible message format of the 5G-NR-V2X protocol.
2.png

The following section presents the message format for verifying extremely fast and low communication performances in both safety and non-safety applications. By following the recommended framework, the authenticity of specific situations can be determined, such as platooning, sensor-sharing, remote driving, and advanced driving services.

Table 1.

Scalable service-oriented V2X data format.
Bit Offset
table1.png
DB_V2X_DEVICE_TYPE_E eDeviceType DB_V2X_TELECOMMUNCATION_TYPE_E eTeleCommType
ulDeviceId (32 bits)
ulTimeStamp (64 bits)
DB_V2X_SERVICE_ID_E eServiceId DB_V2X_ACTION_TYP E_E eActionType
DB_V2X_REGION_ID_E eRegionId DB_V2X_PAYLOAD_TYPE_E ePayloadType
DB_V2X_COMMUNCATION_ID_E eCommId usDbVer (16 bits)
usHwVer (16 bits) usSwVer (16 bits)
ulPayloadLength (32 bits)
Reserved (32 bits)
Payload (Data) ulPacketCrc32

Ⅲ. Testing Methodology

3.1 Overview of the Methodology

This section provides a concise explanation of the approach used to assess 5G-NR-V2X technologies on the Korea Expressway Corporation (EX) highway testbed. To ensure fair and unbiased test results for both equipment and automobiles, we used an identical HW version and application SW version and ensured that the communication model settings were identical as well. The communication modem was set up with the following configurations: the transmission power was configured at 20 dBm, the subcarrier spacing was set to 15 kHz, the central frequency was 5915 MHz, and the bandwidth was 20 MHz. The modulation and coding scheme (MCS) index achieved the maximum packet delivery ratio (PDR) with values ranging from 1 to 28 in the QAM64 table for MCS. Subsequently, the same experiment was conducted on both the autos.

3.2 ATHENA Framework

The autonomous telecommunication hyper- enhanced network architecture (ATHENA) functions as the core framework for overseeing the 5G-NR-V2X communication technologies of the South Korea V2X testbed, along with the services that utilize these technologies, as shown in Figure 4. This platform enables the incorporation of existing and future V2X technologies, such as C-V2X PC5 and C-V2X Uu (5G), over both short and long distances. Moreover, it enables the integration of sensors in vehicles or roadside infrastructure, vehicle actuators, human– machine interfaces, and third-party service providers. ATHENA offers assistance for SSOV services and is specifically built to accommodate a range of standardized cooperative intelligent transport system (C-ITS) services that may be activated dynamically. Moreover, the system can be easily upgraded in a modular manner to support future or customized C-ITS services. Messages can be conveyed in a flexible manner using one or several V2X technologies, which can enhance either transmission capacity or transmission reliability. In addition, the ATHENA framework is interoperable with several types of ITS devices, such as OBUs, RSUs, and servers. This SW has extensive logging capabilities that allow the collection of vital data for evaluating the efficiency of V2X technologies and their related services[14].

3.3 Logging of Data

To consolidate the data gathered from different tests, SQLite3 and CSV databases were set up on every communication device. The data collected from each device were organized systematically based on the dates when the tests were performed. To minimize the possibility of data loss owing to potential disruptions in connectivity, both OBUs and RSU locally store the data communicated and received during each test. After the test campaign is completed, local log files were transmitted to the central database server.

3.4 Test Cases

The evaluation of the 5G-NR-V2X wireless technology included organizing different test scenarios in which a series of tests were conducted, as shown in Figure 3. The test scenario was divided into four main sections. In the first and second test scenarios, as illustrated in Figures 3 (a) and (b), respectively, we determined the maximum effective communication area in a line-of-sight environment by varying the distance between the vehicle and the nearest and farthest points when the vehicle stopped. Furthermore, the PDR for each distance was confirmed to fall within the specified maximum effective communication range. The difference between the two scenarios is when the vehicle's antenna is facing in the opposite direction. You can see differences depending on the characteristics of the antenna.

Fig. 3.

Testing methdology of 5G-NR-V2X (scenarios of a test case).
3.png

Moreover, the experimental protocol entailed categorizing situations according to the orientation of the antennae of the vehicle, with one group having a line of sight towards the other and the other group looking in the same direction. The test evaluates the PDR at distances ranging from 50 m to 2 km. The distances analyzed were 50 m, 100 m, 250 m, 500 m, 750 m, 1 km, 1.25 km, 1.5 km, 1.75 km, and 2 km. Furthermore, one car underwent repair, and the resulting data were documented while the other vehicle was moving at a speed of 30 km/h within the specified maximum range for efficient communication. This experiment facilitated the assessment of communication efficiency in relation to mobility and the implementation of a mobile experiment based on antenna orientation (Figure 3 (c)). The experiment was conducted by replacing the vehicle to evaluate whether there were any variations depending on the vehicle used (Figure 3 (d)). The difference between the two scenarios can be used to determine whether there are differences in characteristics depending on the vehicle. Since the size and height are different for each vehicle, it is necessary to check whether there is a difference. Figure 4 (e) is a scenario to prove platooning performance when using 5G-NR-V2X technology. Vehicles can be used to conduct experiments to maximize verification.

Fig. 4.

SW Architecture of the ATHENA Framework.
4.png

Ⅳ. Experimental Results

This section analyzes and discusses the outcomes obtained from the assessment of several V2X technologies for the test scenarios outlined in Section III.

4.1 Test Environments

The Jetson Nano was employed as an AP linked to the OBU. Considering that the application service AP functions as a TCP/IP Packet, enabling the exchange of data between the OBU devices, no significant differences were observed in the performance of the high-performance Jetson ORIN and Nano devices in relation to the AP. The ATHENA SW, as outlined in Section III, was used to evaluate the communication efficacy of the AP.

4.2 PDR Measurement

The PDR was computed automatically using the ATHENA framework. The 5GAA set a service-level dependability of 99.9% at 800 m. The service-level reliability in the 5GAA was specified as 99.9% within a range of 800 m. A study was conducted to determine the relationship between 5G-NR-V2X and the 5GAA content. When the desired latency was specified as 100 ms, a transmission rate of once every 10 ms achieved a PDR of 99%. The probability of error for a single retransmission was determined to be 96.84% for this system. In this study, the minimum PDR per transmission was 96.84%. The objective was to achieve a PDR of 99.9%, assuming only one end[15].

The database was implemented in the database manager for automatic uploads, and the validated files are available as open databases[16].

4.3 Performance Evaluation

This section provided a description of the examination of V2V communication, as illustrated in Figure 5. Figure 5 (a) shows the outcome of the test case Scenario 1. The experimental findings demonstrated a PDR of 99.99% or higher in the range of 1.5 km. However, beyond this distance, the PDR decreased. The experiment confirmed that PDR values below 96.84% were obtained at 1.58 km, indicating that the maximum effective communication area was within this range. According to the findings presented in Figure 5 (b), the maximum range of effective communication in test Scenario 2 was determined to be 1.25 km. The experiment confirmed that the antenna exhibits varying characteristics depending on its direction. As illustrated in Figure 5 (c), there are instances where the standard outlined in Section 4.2 is surpassed and others where it is not.

Fig. 5.

Performance evaluation of 5G-NR-V2X
5.png

The establishment of a future plan was deemed necessary to enhance the trustworthiness of the results by conducting more repeated tests to confirm the minimum, maximum, and average outcomes. Figure 5 (d) shows the results of an experiment when two vehicles maintain a distance of 100m at a speed of 30km/h. The results showed that the PDR was over 99% and the delay time was within 10ms. The experimental results showed a minimum delay of 3ms, a maximum delay of 10ms, and an average delay of 5ms. Looking at the results, it was confirmed that 5G-NR-V2X was an excellent environment for cooperative driving compared to LTE and WAVE.

Table 2 shows the average results obtained through repeated experiments for scenarios 1 and 2. Because the experimental results are extensive, the minimum and maximum values are not included in this paper. The experiment measured PDR at various distances, Scenario 1 is when the antennas face each other, and Scenario 2 is the opposite. Each experiment was repeated for 5 minutes and was the average value, and a total of 10 experiments were repeated. In addition, in order to check the maximum distance, the MCS Index table was changed in various ways, and because the results for the values of QAM16 and QPSK showed excellent performance, only the corresponding results were presented in the paper. The results of the experiment are published in an open DB, and you can check the experiment results through the corresponding file. Through the overall experiment, we were able to confirm the excellent performance of 5G-NR-V2X, although it is still under development. We plan to conduct more repetitive experiments, verify characteristics in various environments, and verify performance on real roads.

Table 2.

The test results of Scenario 1 and 2.
Test Case Dist.(m) Dev. ID Antenna Directon Table MCS Index Total Tx Packets Total Rx Packets PDR (%) PER (%) Rx File Name
S1 50 OBU#1 Forward QAM64 10 (QAM16) 3173 3132 100 0 20240306-15-55-30_20240306-16-00-48_318secs.csv
OBU#2 Forward QAM64 10 (QAM16) 3132 3173 100 0 20240306-15-55-34_20240306-16-00-49_315secs.csv
100 OBU#1 Forward QAM64 10 (QAM16) 3047 3028 100 0 20240306-14-53-50_20240306-14-58-55_305secs.csv
OBU#2 Forward QAM64 10 (QAM16) 3028 3046 99.96 0.04 20240306-14-53-52_20240306-14-58-56_304secs.csv
250 OBU#1 Forward QAM64 16 (QAM16) 3044 3024 100 0 20240304-16-26-14_20240304-16-31-19_305secs.csv
OBU#2 Forward QAM64 16 (QAM16) 3024 3044 100 0 20240304-16-26-16_20240304-16-31-20_304secs.csv
500 OBU#1 Forward QAM64 10 (QAM16) 3084 3071 99.96 0.04 20240305-11-15-06_20240305-11-20-15_309secs.csv
OBU#2 Forward QAM64 10 (QAM16) 3072 3084 100 0 20240305-11-15-07_20240305-11-20-18_311secs.csv
750 OBU#1 Forward QAM64 10 (QAM16) 3247 3235 100 0 20240305-11-23-33_20240305-11-28-58_325secs.csv
OBU#2 Forward QAM64 10 (QAM16) 3235 3247 100 0 20240305-11-23-34_20240305-11-29-00_326secs.csv
1000 OBU#1 Forward QAM64 10 (QAM16) 3568 3565 99.97 0.03 20240305-11-48-32_20240305-11-54-30_358secs.csv
OBU#2 Forward QAM64 10 (QAM16) 3566 3567 99.97 0.03 20240305-11-48-32_20240305-11-54-31_359secs.csv
1250 OBU#1 Forward QAM64 8 (QPSK) 3070 3051 100 0 20240305-12-01-12_20240305-12-06-19_307secs.csv
OBU#2 Forward QAM64 8 (QPSK) 3051 3070 100 0 20240305-12-01-14_20240305-12-06-22_308secs.csv
S2 50 OBU#1 Reverse QAM64 10 (QAM16) 3586 3580 99.88 0.12 20240306-15-47-26_20240306-15-53-25_359secs.csv
OBU#2 Reverse QAM64 10 (QAM16) 3584 3583 99.91 0.09 20240306-15-47-26_20240306-15-53-28_362secs.csv
100 OBU#1 Reverse QAM64 10 (QAM16) 3489 3470 99.94 0.06 20240306-14-45-36_20240306-14-51-25_349secs.csv
OBU#2 Reverse QAM64 10 (QAM16) 3472 3489 100 0 20240306-14-45-38_20240306-14-51-31_353secs.csv
250 OBU#1 Reverse QAM64 16 (QAM16) 3415 3402 99.94 0.06 20240304-16-06-27_20240304-16-11-31_304secs.csv
OBU#2 Reverse QAM64 16 (QAM16) 3404 3415 100 0 20240304-16-33-09_20240304-16-38-50_341secs.csv
500 OBU#1 Reverse QAM64 10 (QAM16) 3046 3024 99.63 0.37 20240305-11-07-43_20240305-11-12-48_305secs.csv
OBU#2 Reverse QAM64 10 (QAM16) 3035 3043 99.9 0.1 20240305-11-07-44_20240305-11-13-25_341secs.csv
750 OBU#1 Reverse QAM64 10 (QAM16) 3042 3030 99.96 0.04 20240305-11-31-44_20240305-11-36-49_305secs.cs
OBU#2 Reverse QAM64 10 (QAM16) 3031 3042 100 0 20240305-11-31-45_20240305-11-36-51_306secs.csv
1000 OBU#1 Reverse QAM64 10 (QAM16) 3257 3207 99.78 0.22 20240305-11-39-33_20240305-11-44-59_326secs.csv
OBU#2 Reverse QAM64 10 (QAM16) 3214 3256 99.96 0.04 20240305-11-39-36_20240305-11-45-00_324secs.csv
1250 OBU#1 Reverse QAM64 4 (QPSK) 3023 2991 99.33 0.67 20240305-12-13-52_20240305-12-18-54_302secs.csv
OBU#2 Reverse QAM64 4 (QPSK) 3011 3018 99.83 0.17 20240305-12-13-53_20240305-12-18-55_302secs.csv

Ⅴ. Conclusions And Future Work

This paper presents an empirical assessment of 5G-NR-V2X on an actual highway and at a testing facility. The core structure, transmission protocol, and data format of 5G-NR-V2X are introduced. Moreover, the paper describes the testing methodology used and presents a detailed report of the experimental results in several test settings. Overall, this study achieved outstanding results; nevertheless, further testing is necessary to draw more reliable conclusions.

In the future, we will create a plan to evaluate the effectiveness of communication in 5G-NR-V2X, as shown in Figure 6. Our goal is to provide significant insights for autonomous driving businesses.

Fig. 6.

Future work of 5G-NR-V2X communication verification.
6.png

By implementing service validation and case scenario testing, the proposed performance analysis technique has the potential to enhance technical competitiveness in the road, transportation, logistics, and commercial sectors.

Biography

Byoungman An

Feb. 2010 : BS degree in Electronics & Electrical Engineering from Dankook University

Aug. 2012 : MS degree in Electronics & Electrical Engineering from Dankook University

Aug. 2021 : Ph.D. degree in Electronics & Electrical Engineering from Dankook University

2012~2018 : Software Center, Humax

2018~2019 : Software Center, Yura Cooperation

2019~2020 : Software Center, Humax

2020~2022 : Software Center, Hanwha Techwin

2022~Now : Principal Researcher in Mobility Platform Research Center, Korea Electronics Technology Institute (KETI).

[Research Interests] V2X Communication, C-ITS

[https://orcid.org/0000-0002-4127-0651]

Biography

Jimin Lee

Aug. 2022 : BS degree in Department of Applied Statistics and Data Science from Dongduk Women's University

2023~Now : Researcher in Mobility Platform Research Center, Korea Electronics Technology Institute (KETI).

[Research Interests] V2X Communication, C-ITS

Biography

Seonghyun Jang

Feb. 2006 : BS degree in electronic and computer engineering from Hanyang University.

Feb. 2013 : Ph.D. degree in electronic and computer engineering from Hanyang University.

2013~2021: Staff engineer in Modem Development Team, S.LSI, Samsung Electronics.

2021~Now : Principal Researcher in Mobility Platform Research Center, Korea Electronics Technology Institute (KETI).

[Research Interests] V2X Communication, C-ITS

[https://orcid.org/0000-0002-9451-4605]

Biography

Kitaeg Lim

Feb. 1994 : BS degree in electronic engineering from Hanyang University.

1996 : MS degree in electronic engineering from Hanyang University.

2013 : Ph.D. Candidate in electronic and computer engineering from Hanyang University.

1996~2024 : Chief Researcher in Mobility Platform Research Center, Korea Electronics Technology Institute (KETI).

2024~Now : A is currently employed at KETI and is on a secondment to Korea Planning & Evaluation Institute of Industrial Technology (KEIT).

[Research Interests] V2X Communication, C-ITS

Biography

Daekyo Shin

1998 : BS degree in electronic engineering from Ajou University.

2000 : MS degree in electronic engineering from Ajou University.

2003~Now : Chief Researcher in Mobility Platform Research Center, Korea Electronics Technology Institute (KETI).

[Research Interests] V2X Communication, C-ITS

Biography

Soohyun Jang

2009:BS degree in electronic engineering from Korea Aerospace University.

2011 : MS degree in electronic engineering from Korea Aerospace University.

2015 : Ph.D. degree in Electronics Engineering from Korea Aerospace University.

2015~Now : Principal Researcher in Mobility Platform Research Center, Korea Electronics Technology Institute (KETI).

[Research Interests] V2X Communication, C-ITS

Biography

Junhyek Jang

2018 : BS degree in electronic engineering from Columbia University.

2019 : MS degree in electronic engineering from Columbia University.

2022~Now : Senior Researcher in Mobility Platform Research Center, Korea Electronics Technology Institute (KETI).

[Research Interests] V2X Communication, C-ITS

Biography

Sanghun Yoon

Feb. 1998 : MS degree in electronic engineering from Hanyang University.

Feb. 2008 : Ph.D. degree in electronic engineering from Hanyang University.

2012~2024 : Principal Researcher in Mobility Platform Research Center, Korea Electronics Technology Institute (KETI).

2024~Now : A is currently employed at KETI and is on a secondment to Korea Planning & Evaluation Institute of Industrial Technology (KEIT).

[Research Interests] V2X Communication, C-ITS

[https://orcid.org/0000-0003-2080-8608]

References

  • 1 L. Zhao, T. Zheng, M. Lin, A. Hawbani, J. Shang, and C. Fan, "SPIDER: A social computing inspired predictive routing scheme for softwarized vehicular networks," in IEEE Trans. Intell. Transport. Syst., vol. 23, no. 7, pp. 9466-9477, Jul. 2022. (https://doi.org/10.1109/TITS.2021.3122438)doi:[[[10.1109/TITS.2021.3122438]]]
  • 2 S. Chen, et al., "Vehicle-to-everything (v2x) services supported by LTE-based systems and 5G," in IEEE Commun. Standards Mag., vol. 1, no. 2, pp. 70-76, 2017. (https://doi.org/10.1109/MCOMSTD.2017.1700 015)doi:[[[10.1109/MCOMSTD.2017.1700015]]]
  • 3 S. Chen, J. Hu, Y. Shi, L. Zhao, and W. Li, "A vision of C-V2X: Technologies, field testing, and challenges with chinese development," in IEEE Internet of Things J., vol. 7, no. 5, pp. 3872-3881, May 2020. (https://doi.org/10.1109/JIOT.2020.2974823)doi:[[[10.1109/JIOT.2020.2974823]]]
  • 4 P. Liu, Y. Zhang, T. Fu, and J. Hu, "Intelligent mobile edge caching for popular contents in vehicular cloud toward 6G," in IEEE Trans. Veh. Technol., vol. 70, no. 6, pp. 5265-5274, Jun. 2021. (https://doi.org/10.1109/TVT.2021.3076304)doi:[[[10.1109/TVT.2021.3076304]]]
  • 5 A. F. Magnussen, et al., "A survey of the inadequacies in traffic sign recognition systems for autonomous vehicles," Int. J., 2020. (https://doi.org/10.23940/ijpe.20.10.p10.158815 97)doi:[[[10.23940/ijpe.20.10.p10.15881597]]]
  • 6 C. Prehofer and S. Mehmood, "Big data architectures for vehicle data analysis," 2020 IEEE Int. Conf. Big Data (Big Data), pp. 3404-3412, Atlanta, GA, USA, 2020. (https://doi.org/10.1109/BigData50022.2020.93 78397)doi:[[[10.1109/BigData50022.2020.9378397]]]
  • 7 ETSI TS 122 186, "5G; Service Requirements for Enhanced V2X Scenarios," 3GPP TS 22.186 version 16.2.0 Release 16, Nov. 2020. (https://www.etsi.org/deliver/etsi_ts/122100_12 2199/122186/16.02.00_60/ts_122186v160200p. pdf)custom:[[[https://www.etsi.org/deliver/etsi_ts/122100_122199/122186/16.02.00_60/ts_122186v160200p.pdf)]]]
  • 8 ETSI TS 122 186, "5G; Service requirements Fig. 6. Future work of 5G-NR-V2X communication verification. 1668 for enhanced V2X scenarios," 3GPP TS 22.186 version 17.0.0 Release 17, Apr. 2022. (https://www.etsi.org/deliver/etsi_ts/122100_12 2199/122186/17.00.00_60/ts_122186v170000p. pdf)custom:[[[https://www.etsi.org/deliver/etsi_ts/122100_122199/122186/17.00.00_60/ts_122186v170000p.pdf)]]]
  • 9 ETSI TS 122 261, "5G; Service requirements for the 5G system," 3GPP TS 22.261 version 17.11.0 Release 17, Oct. 2022. (https://www.etsi.org/deliver/etsi_ts/122200_12 2299/122261/17.11.00_60/ts_122261v171100p. pdf)custom:[[[https://www.etsi.org/deliver/etsi_ts/122200_122299/122261/17.11.00_60/ts_122261v171100p.pdf)]]]
  • 10 5GAA, "A visionary roadmap for advanced driving use cases, connectivity technologies, and radio spectrum needs," Nov. 2022. (https://5gaa.org/content/uploads/2023/01/5gaawhite-paper-roadmap.pdf)custom:[[[https://5gaa.org/content/uploads/2023/01/5gaawhite-paper-roadmap.pdf)]]]
  • 11 Qualcomm Research, "3GPP Rel. 17: To bring new system capabilities and expand 5G to new devices, applications, and deployment completing the first phase of the 5G evolution," Mar. 2022. (https://www.qualcomm.com/content/dam/qco mm-martech/dm-assets/documents/powerpoint_ messaging_-_3gpp_release_17_completing_the _first_phase_of_5g_evolution.pdf)custom:[[[https://www.qualcomm.com/content/dam/qcomm-martech/dm-assets/documents/powerpoint_messaging_-_3gpp_release_17_completing_the_first_phase_of_5g_evolution.pdf)]]]
  • 12 B. An, J. Lee, S. Jang, K. Lim, and S. Yoon, "Overview of 5G-NR-V2X system and analysis methodology of communication performance," 2023 14th Int. Conf. Inf. and Commun. Technol. Convergence (ICTC), pp. 1137-1142, Jeju Island, Korea, 2023. (http://doi.org/doi:%2010.1109/ICTC58733.202 3.10393411)doi:[[[doi:%2010.1109/ICTC58733.2023.10393411]]]
  • 13 B. An, S. Jang, S. Yoon, and K. Lim, "Scalable service oriented V2X data format over 5G-NR-V2X," 2023 IEEE ICCE-Asia, pp. 1-4, Busan, Korea, 2023. (http://doi.org/doi:%2010.1109/ICCE-Asia5996 6.2023.10326408)doi:[[[doi:%2010.1109/ICCE-Asia59966.2023.10326408]]]
  • 14 ATHENA Framework Github, 2024. (https://github.com/KETI-A/athena)custom:[[[https://github.com/KETI-A/athena)]]]
  • 15 5GAA, "C-V2X Use CasesService Lv. Requirements Vol. III," 2023. (https://5gaa.org/content/uploads/2023/01/5gaatr-c-v2x-use-cases-and-service-level-requireme nts-vol-iii.pdf)custom:[[[https://5gaa.org/content/uploads/2023/01/5gaatr-c-v2x-use-cases-and-service-level-requirements-vol-iii.pdf)]]]
  • 16 Open 5G-NR-V2X DB FTP, 2022-2025. (sftp://221.140.137.186)custom:[[[-]]]

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Cite this article

IEEE Style
B. An, J. Lee, S. Jang, K. Lim, D. Shin, S. Jang, J. Jang, S. Yoon, "Experimental Assessment of 5G-NR-V2X in a Real-life Highway," The Journal of Korean Institute of Communications and Information Sciences, vol. 49, no. 11, pp. 1658-1670, 2024. DOI: 10.7840/kics.2024.49.11.1658.


ACM Style
Byoungman An, Jimin Lee, Seonghyun Jang, Kitage Lim, Daekyo Shin, Soohyun Jang, Junhyek Jang, and Sanghun Yoon. 2024. Experimental Assessment of 5G-NR-V2X in a Real-life Highway. The Journal of Korean Institute of Communications and Information Sciences, 49, 11, (2024), 1658-1670. DOI: 10.7840/kics.2024.49.11.1658.


KICS Style
Byoungman An, Jimin Lee, Seonghyun Jang, Kitage Lim, Daekyo Shin, Soohyun Jang, Junhyek Jang, Sanghun Yoon, "Experimental Assessment of 5G-NR-V2X in a Real-life Highway," The Journal of Korean Institute of Communications and Information Sciences, vol. 49, no. 11, pp. 1658-1670, 11. 2024. (https://doi.org/10.7840/kics.2024.49.11.1658)