The Effect of Decentralized Congestion Control on Collective Perception in Dense Traffic Scenarios

Günther, Hendrik-Jörn; Riebl, Raphael; Wolf, Lars; Facchi, Christian

doi:10.1016/j.comcom.2018.03.009

Cited by 26 publications

(14 citation statements)

References 5 publications

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“…At the same time, it receives the target information from other vehicles to expand the vision and reduce false alarms. Günther et al [103], [104] put forward the concept of collective perception, which means sharing local sensor data with other vehicles within the communication range. The feasibility of realizing group perception in V2X communication under different traffic densities is analyzed.…”

Section: Research On Traffic Conflict Based On Intelligent Vehiclmentioning

confidence: 99%

A Review of Research on Traffic Conflicts Based on Intelligent Vehicles

Huang

et al. 2020

IEEE Access

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The traffic situation at an urban intersection is complicated, due to the numerous internal conflicts and all kinds of traffic accidents. With the objective of improving road safety, the automotive industry is moving toward intelligent vehicles. The major challenges are accurately perceiving the road traffic environment, detecting the potential traffic conflicts, and proposing the alternative driving strategies. This paper summarizes the existing researches on traffic conflicts from the perspective of intelligent vehicles. The intelligent vehicles can perceive the surrounding environment, extract road condition information, and detect obstacles for avoiding collisions or mitigating accidents. It expounds that the perception technology of intelligent vehicles can be divided into three main categories, namely, the perception technology, the communication technology, and the fusion of perception-communication technology. At the same time, the existing technical problems are analyzed. Finally, future development trends in this field are discussed. INDEX TERMS Intelligent vehicles, traffic conflicts, V2X communications, environment perception. I. INTRODUCTION

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Section: Research On Traffic Conflict Based On Intelligent Vehiclmentioning

confidence: 99%

A Review of Research on Traffic Conflicts Based on Intelligent Vehicles

Huang

et al. 2020

IEEE Access

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“…Concept and functional benefit of collective perception have been studied with the Artery simulation framework [ 10 , 13 , 14 ], based on the network simulator OMNeT++. These works found that the vehicle awareness ratio, i.e., how many vehicles it can see around itself, increases significantly when vehicles exchange CPMs in addition to CAMs.…”

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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“…Following a similar concept of CP, Proxy CAM is presented in [ 17 , 18 , 19 ], where intelligent infrastructure generates standard CAMs for those perceived road users, while the work in [ 20 ] proposes a CPM comprised of a collection of CAMs, each describing a perceived object. The work in [ 21 , 22 ] evaluates different EPM dissemination variants under low and high traffic densities and proposes to attach the CP relevant DFs in EPM to CAM to minimise communication overhead. The CPM currently being specified at ETSI, as in [ 23 ], is derived from optimising the EPM and combining it with CAM.…”

Section: Related Workmentioning

confidence: 99%

“…Another commonly used network and mobility simulator is Veins (Vehicles in Network Simulation) [ 49 , 50 ], which integrates SUMO and a discrete-event simulator OMNeT++ (Open Modular Network Testbed in C++) [ 51 ] for modelling realistic communication patterns. The authors of [ 21 , 22 , 25 , 30 , 32 , 52 ] conduct work in Artery [ 53 , 54 ] framework, which wraps SUMO and OMNet++, and enables V2X simulations based on ETSI ITS G5 protocol stack. There are also simulators for advanced driving assistance systems (ADASs) and autonomous driving systems, which provide more realistic sensory level perception information.…”

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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The Effect of Decentralized Congestion Control on Collective Perception in Dense Traffic Scenarios

Cited by 26 publications

References 5 publications

A Review of Research on Traffic Conflicts Based on Intelligent Vehicles

A Review of Research on Traffic Conflicts Based on Intelligent Vehicles

Collective Perception: A Safety Perspective

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

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