Vehicle Safety Communications - Applications: Multiple On-Board Equipment Testing

Ahmed-Zaid, F.; Krishnan, Hariharan; Maile, Michael; Caminiti, L; Bai, Sue; Stinnett, J; VanSickle, S; Cunningham, D

doi:10.4271/2011-01-0586

Cited by 10 publications

(10 citation statements)

References 1 publication

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“…Figure 1 presents a CVS system architecture [13, 14]. The modules include the services modules, WSU software API, sensors and wireless data handler, the TC, and safety applications.…”

Section: Literature Reviewmentioning

confidence: 99%

“…CVS architectures separate the design of applications from the communication system allowing flexibility and simpler adoption of different communication technologies. Figure 1 shows a CVS system that consists of a communication and sensor layer, a Target Classification (TC) layer, and a safety application layer [13, 14]. TC classifies the neighboring RVs based on their relative locations with respect to the HV.…”

Section: Introductionmentioning

confidence: 99%

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Context‐aware target classification with hybrid Gaussian process prediction for cooperative vehicle safety systems

Valiente

Raftari

Mahjoub

et al. 2023

IET Intelligent Trans Sys

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Vehicle-to-Everything (V2X) communication has been proposed as a potential solution to improve the robustness and safety of autonomous vehicles by improving coordination and removing the barrier of non-line-of-sight sensing. Cooperative Vehicle Safety (CVS) applications are tightly dependent on the reliability of the underneath data system, which can suffer from loss of information due to the inherent issues of their different components, such as sensors' failures or the poor performance of V2X technologies under dense communication channel load. Particularly, information loss affects the target classification module and, subsequently, the safety application performance. To enable reliable and robust CVS systems that mitigate the effect of information loss, a Context-Aware Target Classification (CA-TC) module coupled with a hybrid learning-based predictive modeling technique for CVS systems is proposed. The CA-TC consists of two modules: a Context-Aware Map (CAM), and a Hybrid Gaussian Process (HGP) prediction system. Consequently, the vehicle safety applications use the information from the CA-TC, making them more robust and reliable. The CAM leverages vehicles' path history, road geometry, tracking, and prediction; and the HGP is utilized to provide accurate vehicles' trajectory predictions to compensate for data loss (due to communication congestion) or sensor measurements' inaccuracies. Based on offline real-world data, a finite bank of driver models that represent the joint dynamics of the vehicle and the drivers' behavior is learned. Offline training and online model updates are combined with on-the-fly forecasting to account for new possible driver behaviors. Finally, the framework is validated using simulation and realistic driving scenarios to confirm its potential in enhancing the robustness and reliability of CVS systems.

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“…Figure 1 presents a CVS system architecture [13, 14]. The modules include the services modules, WSU software API, sensors and wireless data handler, the TC, and safety applications.…”

Section: Literature Reviewmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Context‐aware target classification with hybrid Gaussian process prediction for cooperative vehicle safety systems

Valiente

Raftari

Mahjoub

et al. 2023

IET Intelligent Trans Sys

View full text Add to dashboard Cite

show abstract

“…Based on the time-to-collision (TTC) estimate, four different collision warning messages are provided. Following the collision warning stages discussed in [ 69 ], the warning messages provided by the proposed system include “no threat” for no possible collision, “threat detected” for

, “inform driver” for

, and “warn driver” for

. The description for each warning message is described in Table 5 .…”

Section: State Estimation and Predictionmentioning

confidence: 99%

Driving Environment Perception Based on the Fusion of Vehicular Wireless Communications and Automotive Remote Sensors

Baek

Mun

Kim

et al. 2021

Sensors

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Driving environment perception for automated vehicles is typically achieved by the use of automotive remote sensors such as radars and cameras. A vehicular wireless communication system can be viewed as a new type of remote sensor that plays a central role in connected and automated vehicles (CAVs), which are capable of sharing information with each other and also with the surrounding infrastructure. In this paper, we present the design and implementation of driving environment perception based on the fusion of vehicular wireless communications and automotive remote sensors. A track-to-track fusion of high-level sensor data and vehicular wireless communication data was performed to accurately and reliably locate the remote target in the vehicle surroundings and predict the future trajectory. The proposed approach was implemented and evaluated in vehicle tests conducted at a proving ground. The experimental results demonstrate that using vehicular wireless communications in conjunction with the on-board sensors enables improved perception of the surrounding vehicle located at varying longitudinal and lateral distances. The results also indicate that vehicle future trajectory and potential crash involvement can be reliably predicted with the proposed system in different cut-in driving scenarios.

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“…In [ 26 ], the VSC-A project evaluated the IEEE 1609.2 standard in a testbed implemented on a PC platform and showed that the signature generation time and verification time based on ECC-256 is 6.6 ms and 28.5 ms, respectively. Their experimental analysis indicates that the IEEE 1609.2 standard based on ECDSA is highly demanding in the resource.…”

Section: Related Workmentioning

confidence: 99%

Comparative Experiments of V2X Security Protocol Based on Hash Chain Cryptography

Hakeem

El-Gawad

Kim

2020

Sensors

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Vehicle-to-everything (V2X) is the communication technology designed to support road safety for drivers and autonomous driving. The light-weight security solution is crucial to meet the real-time needs of on-board V2X applications. However, most of the recently proposed V2X security protocols—based on the Elliptic Curve Digital Signature Algorithm (ECDSA)—are not efficient enough to support fast processing and reduce the communication overhead between vehicles. ECDSA provides a high-security level at the cost of excessive communication and computation overhead, which motivates us to propose a light-weight message authentication and privacy preservation protocol for V2X communications. The proposed protocol achieves highly secure message authentication at a substantially lower cost by introducing a hash chain of secret keys for a Message Authentication Code (MAC). We implemented the proposed protocol using commercial V2X devices to prove its performance advantages over the standard and non-standard protocols. We constructed real V2X networks using commercial V2X devices that run our implemented protocol. Our extensive experiments with real networks demonstrate that the proposed protocol reduces the communication overhead by 6 times and computation overhead by more than 100 times compared with the IEEE1609.2 standard. Moreover, the proposed protocol reduces the communication overhead by 4 times and the computation overhead by up to 100 times compared with a non-standard security protocol, TESLA. The proposed protocol substantially reduces the average end-to-end delay to 2.5 ms, which is a 24- and 28-fold reduction, respectively, compared with the IEEE1609 and TESLA protocols.

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Vehicle Safety Communications - Applications: Multiple On-Board Equipment Testing

Cited by 10 publications

References 1 publication

Context‐aware target classification with hybrid Gaussian process prediction for cooperative vehicle safety systems

Context‐aware target classification with hybrid Gaussian process prediction for cooperative vehicle safety systems

Driving Environment Perception Based on the Fusion of Vehicular Wireless Communications and Automotive Remote Sensors

Comparative Experiments of V2X Security Protocol Based on Hash Chain Cryptography

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