V2X Communications for Infrastructure-Assisted Automated Driving

Rondinone, Michele; Walter, Thomas; Blokpoel, Robbin; Schindler, Julian

doi:10.1109/wowmom.2018.8449775

Cited by 17 publications

(13 citation statements)

References 2 publications

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“…However, the impact of the vehicle awareness ratio on the vehicle capability to correctly assess its collision risk based on its environmental model has not been assessed to date. Collective perception is investigated in several European collaborative research projects, such as TransAID [ 15 ], AutoNet2030 [ 16 ], IMAGinE [ 17 ] and MAVEN [ 18 ].…”

Section: Collective Perceptionmentioning

confidence: 99%

Collective Perception: A Safety Perspective

Schiegg

Llátser

Bischoff³

et al. 2020

Sensors

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Vehicle-to-everything (V2X) communication is seen as one of the main enabling technologies for automated vehicles. Collective perception is especially promising, as it allows connected traffic participants to “see through the eyes of others” by sharing sensor-detected objects via V2X communication. Its benefit is typically assessed in terms of the increased object update rate, redundancy, and awareness. To determine the safety improvement thanks to collective perception, the authors introduce new metrics, which quantify the environmental risk awareness of the traffic participants. The performance of the V2X service is then analyzed with the help of the test platform TEPLITS, using real traffic traces from German highways, amounting to over 100 h of total driving time. The results in the considered scenarios clearly show that collective perception not only contributes to the accuracy and integrity of the vehicles’ environmental perception, but also that a V2X market penetration of at least 25% is necessary to increase traffic safety from a “risk of serious traffic accidents” to a “residual hypothetical risk of collisions without minor injuries” for traffic participants equipped with non-redundant 360° sensor systems. These results support the ongoing worldwide standardization efforts of the collective perception service.

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Section: Collective Perceptionmentioning

confidence: 99%

Collective Perception: A Safety Perspective

Schiegg

Llátser

Bischoff³

et al. 2020

Sensors

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“…The authors of [ 35 ] discuss the security threats in CP and propose possible countermeasures in V2X network protocols, while the work in [ 36 ] focuses on using CP for detecting vehicle misbehaviour due to adversarial attacks in V2X communication. Most of the CP related use cases studied in the literature are safety related, including cooperative driving [ 5 , 16 ], cooperative advisory warnings [ 37 , 38 ], cooperative collision avoidance [ 4 , 13 , 39 ], intersection assistance [ 17 , 40 ], and vehicle misbehaviour detection [ 41 ], to name a few. It is presented in [ 42 ] quantitative comparison of V2V and V2I connectivity on improving sensing redundancy and collaborative sensing coverage for CAV applications.…”

Section: Related Workmentioning

confidence: 99%

“…Recent work in [ 44 ] demonstrates the IRSU assisted CP for extending perception of CAVs on open roads. Infrastructure-assisted CP is also part of the scope of Managing Automated Vehicles Enhances Network (MAVEN) [ 45 ], an EU funded project targeting traffic management solutions where CAVs are guided at signalised cooperative intersections in urban traffic environments [ 40 ]. Other CP related joint research projects include TransAID [ 46 ] and IMAGinE [ 47 ].…”

Section: Related Workmentioning

confidence: 99%

Demonstrations of Cooperative Perception: Safety and Robustness in Connected and Automated Vehicle Operations

Shan

Narula

Wong³

et al. 2020

Sensors

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Cooperative perception, or collective perception (CP), is an emerging and promising technology for intelligent transportation systems (ITS). It enables an ITS station (ITS-S) to share its local perception information with others by means of vehicle-to-X (V2X) communication, thereby achieving improved efficiency and safety in road transportation. In this paper, we present our recent progress on the development of a connected and automated vehicle (CAV) and intelligent roadside unit (IRSU). The main contribution of the work lies in investigating and demonstrating the use of CP service within intelligent infrastructure to improve awareness of vulnerable road users (VRU) and thus safety for CAVs in various traffic scenarios. We demonstrate in experiments that a connected vehicle (CV) can “see” a pedestrian around the corners. More importantly, we demonstrate how CAVs can autonomously and safely interact with walking and running pedestrians, relying only on the CP information from the IRSU through vehicle-to-infrastructure (V2I) communication. This is one of the first demonstrations of urban vehicle automation using only CP information. We also address in the paper the handling of collective perception messages (CPMs) received from the IRSU, and passing them through a pipeline of CP information coordinate transformation with uncertainty, multiple road user tracking, and eventually path planning/decision-making within the CAV. The experimental results were obtained with manually driven CV, fully autonomous CAV, and an IRSU retrofitted with vision and laser sensors and a road user tracking system.

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“…Yet messages such as ETSI-DENM [8], CAM [9] and others merely support information sharing, without any means for harmonization of intentions. The project MAVEN [10] proposed an extension of the CAmessage in order to carry information for platoon forming and control. In the GCDC i-Game 2016 a Cooperative Lane Change Message or iCLCM was proposed [11].…”

Section: State Of the Artmentioning

confidence: 99%

Negotiation of Cooperative Maneuvers for Automated Vehicles: Experimental Results

Hes

Lattarulo

Pérez

et al. 2019

2019 IEEE Intelligent Transportation Systems Conference (ITSC)

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When the number of automated vehicles deployed in public traffic reaches a significant level, their form of interaction with other automated vehicles, human controlled vehicles and non-motorized participants will impact traffic overall safety and efficiency. While many studies have approached impact analysis on the side of efficiency and via simulation, we here elaborate on practically applicable methods for safe cooperation of automated vehicles from the perspective of life-size experimental platforms. The EU project UnCoVerCPS investigates on-line verification based safety analysis and control of cyberphysical system, applying the developed techniques to cooperation of automated vehicles. In a previous publication, a message set for negotiation of such a cooperation has been proposed, (STRP), which is compatible with the investigated verification approach. This publication follows up by providing results and analysis of test drives with two cooperating, automated vehicles with differing software and hardware architectures. The STRP messages are employed to negotiate a cooperative lane change via Car-to-Car radio in an urban scenario with non-trivial road-geometry. The applicability of the distributed cooperation scheme to real-world conditions is demonstrated.

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V2X Communications for Infrastructure-Assisted Automated Driving

Cited by 17 publications

References 2 publications

Collective Perception: A Safety Perspective

Collective Perception: A Safety Perspective

Demonstrations of Cooperative Perception: Safety and Robustness in Connected and Automated Vehicle Operations

Negotiation of Cooperative Maneuvers for Automated Vehicles: Experimental Results

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