Generation Rules for the Collective Perception Service

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.

Section: Collective Perceptionmentioning

confidence: 99%

Section: Evaluation Metricsmentioning

confidence: 99%

Collective Perception: A Safety Perspective

Schiegg

Llátser

Bischoff³

et al. 2020

“…Considering the limited communication bandwidth and avoiding congestion in the wireless channel, more recent studies in the CP area tend to focus on the communication aspect of the technology, weighing up provided CP service quality and the V2X network resources. The work in [ 25 ] investigates ETSI CPM generation rules that balance provided service quality and the V2X channel load. It is provided in [ 26 ] an in-depth study on the impact of different CPM generation rules from the perspectives of V2X communication performance and perception capabilities in low and high density traffic scenarios.…”

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

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.

“…However, there is a risk of message flooding under heavy traffic. [ 16 , 17 ] proposed generation rules for mitigation. Some message filtering algorithms [ 18 , 19 ] reduce the number of messages while maintaining perception performance.…”

Section: State Of the Artmentioning

confidence: 99%

Networked Roadside Perception Units for Autonomous Driving

Tsukada

Kitazawa

et al. 2020

Vehicle-to-Everything (V2X) communication enhances the capability of autonomous driving through better safety, efficiency, and comfort. In particular, sensor data sharing, known as cooperative perception, is a crucial technique to accommodate vulnerable road users in a cooperative intelligent transport system (ITS). In this paper, we describe a roadside perception unit (RSPU) that combines sensors and roadside units (RSUs) for infrastructure-based cooperative perception. We propose a software called AutoC2X that we designed to realize cooperative perception for RSPUs and vehicles. We also propose the concept of networked RSPUs, which is the inter-connection of RSPUs along a road over a wired network, and helps realize broader cooperative perception. We evaluated the RSPU system and the networked RSPUs through a field test, numerical analysis, and simulation experiments. Field evaluation showed that, even in the worst case, our RSPU system can deliver messages to an autonomous vehicle within 100 ms. The simulation result shows that the proposed priority algorithm achieves a wide perception range with a high delivery ratio and low latency, especially under heavy road traffic conditions.