Collective Perception service for Connected Vehicles and Roadside Infrastructure

Collective Perception Service (CPS) is under standardisation at European Telecommunications Standardisation Institute (ETSI) with the objective of enabling sensor-equipped vehicles and roadside units (RSU) to notify nearby vehicles of the objects detected by their sensors. This service is expected to significantly improve perception of vehicles and, hence, improve road safety. While both vehicles and RSUs can contribute in CPS, they have very different characteristics in terms of mobility, sensor field of view (FOV), communication coverage, processing capacity, and service integration cost. This paper compares CPS provided by vehicles and by RSUs, particularly their impacts on extending vehicles’ perception. We will first develop an analytical model that formulates the number of objects perceived by vehicles and RSUs and the success probability of CPM targeting the IEEE 802.11p technology. The analytical results will then be confirmed by simulation evaluations conducted using the VEINS simulator. The analytical and simulation results reveal that, RSU-assisted CPS significantly outperforms vehicle-assisted CPS, providing up to 8-times higher effective number of perceived objects. The results suggest a great opportunity of optimising radio resource utilisation without degrading collective perception by exploiting roadside infrastructure.

[1]  Sascha Wirges,et al.  Making Bertha Cooperate–Team AnnieWAY’s Entry to the 2016 Grand Cooperative Driving Challenge , 2018, IEEE Transactions on Intelligent Transportation Systems.

[2]  Mahmoud Al-Ayyoub,et al.  Cooperative mobile edge computing system for VANET-based software-defined content delivery , 2018, Comput. Electr. Eng..

[3]  Oyunchimeg Shagdar,et al.  Implementation and Evaluation of Intelligent Roadside Infrastructure for Automated Vehicle with I2V Communication , 2020 .

[4]  Klaus C. J. Dietmayer,et al.  Analysis of V2X communication parameters for the development of a fusion architecture for cooperative perception systems , 2011, 2011 IEEE Intelligent Vehicles Symposium (IV).

[5]  Shaobo Dang,et al.  Data Redundancy Mitigation in V2X Based Collective Perceptions , 2020, IEEE Access.

[6]  Michele Zorzi,et al.  Value-Anticipating V2V Communications for Cooperative Perception , 2019, 2019 IEEE Intelligent Vehicles Symposium (IV).

[7]  Miguel Sepulcre,et al.  Analysis of Message Generation Rules for Collective Perception in Connected and Automated Driving , 2019, 2019 IEEE Intelligent Vehicles Symposium (IV).

[8]  Intelligent Transport Systems (its); Cross Layer Dcc Management Entity for Operation in the Its G5a and Its G5b Medium , 2022 .

[9]  K.C.J. Dietmayer,et al.  Extending Onboard Sensor Information by Wireless Communication , 2007, 2007 IEEE Intelligent Vehicles Symposium.

[10]  Fawzi Nashashibi,et al.  Performance study of CAM over IEEE 802.11p for cooperative adaptive cruise control , 2017, 2017 Wireless Days.

[11]  Mehrdad Dianati,et al.  Performance study of a Green Light Optimized Speed Advisory (GLOSA) application using an integrated cooperative ITS simulation platform , 2011, 2011 7th International Wireless Communications and Mobile Computing Conference.

[12]  Lars C. Wolf,et al.  Generation Rules for the Collective Perception Service , 2019, 2019 IEEE Vehicular Networking Conference (VNC).

[13]  Fernando García,et al.  Towards Autonomous Driving: a Multi-Modal 360° Perception Proposal , 2020, 2020 IEEE 23rd International Conference on Intelligent Transportation Systems (ITSC).

[14]  Michael Anthony Bauer,et al.  V2Eye: Enhancement of visual perception from V2V communication , 2011, 2011 IEEE Consumer Communications and Networking Conference (CCNC).

[15]  Gustavo de Veciana,et al.  Deployment and Performance of Infrastructure to Assist Vehicular Collaborative Sensing , 2018, 2018 IEEE 87th Vehicular Technology Conference (VTC Spring).

[16]  Daniel Krajzewicz,et al.  SUMO (Simulation of Urban MObility) - an open-source traffic simulation , 2002 .

[17]  Miguel Sepulcre,et al.  Redundancy Mitigation in Cooperative Perception for Connected and Automated Vehicles , 2020, 2020 IEEE 91st Vehicular Technology Conference (VTC2020-Spring).

[18]  Lars C. Wolf,et al.  Realizing collective perception in a vehicle , 2016, 2016 IEEE Vehicular Networking Conference (VNC).

[19]  Miguel Sepulcre,et al.  Generation of Cooperative Perception Messages for Connected and Automated Vehicles , 2019, IEEE Transactions on Vehicular Technology.

[20]  Moumena Chaqfeh,et al.  Exploiting Mobile Edge Computing for Enhancing Vehicular Applications in Smart Cities , 2019, Sensors.