VAP2: IoT and V2X Technologies
Wednesday, 9 June 2021, 16:00-17:30, Zoom Room
Session Chair: Frank Y. Li (Univ. Agder, Norway)
Valentina Rossi, Paolo Testolina, Marco Giordani and Michele Zorzi (University of Padova, Italy)
Fully autonomous driving systems require fast detection and recognition of sensitive objects in the environment. In this context, intelligent vehicles should share their sensor data with computing platforms and/or other vehicles, to detect objects beyond their own sensors’ fields of view. However, the resulting huge volumes of data to be exchanged can be challenging to handle for standard communication technologies. In this paper, we evaluate how using a combination of different sensors affects the detection of the environment in which the vehicles move and operate. The final objective is to identify the optimal setup that would minimize the amount of data to be distributed over the channel, with negligible degradation in terms of object detection accuracy. To this aim, we extend an already available object detection algorithm so that it can consider, as an input, camera images, LiDAR point clouds, or a combination of the two, and compare the accuracy performance of the different approaches using two realistic datasets. Our results show that, although sensor fusion always achieves more accurate detections, LiDAR only inputs can obtain similar results for large objects while mitigating the burden on the channel.
Sandaruwan Gayantha Jayaweera, Nandana Rajatheva and Matti Latva-aho (University of Oulu, Finland); Kapuruhamy Badalge Shashika Manosha (Keysight Technologies, Finland)
High mobility, low latency and high throughput requirements in intelligent transport systems (ITS) have paved the way for the development of new wireless communication technologies. Therefore, the 5.9 GHz band has been assigned to ITS applications under two main technologies. Europe’s ITS-G5 is one such technology, which is based on IEEE 802.11p. The other alternative technology is 3GPP’s cellular vehicle-to-everything (C-V2X). Both of these technologies have their inherent advantages and disadvantages due to dissimilarities in their physical (PHY) and media access control (MAC) layer architectures. Therefore, the applicability of each technology will vary depending on the situation. While previous work has been mainly focused on the comparison of two technologies, in this paper, we investigate the benefit of the co-existence of both of these technologies for a V2I downlink scenario in a road-side unit (RSU) placed at the center of an urban road intersection. We propose an optimization scheme to achieve the best minimum signal-to-interference-plus-noise ratio (SINR) performance for the RSU while providing connectivity to the maximum possible number of vehicles. Our analysis shows that ITS-G5 should be given priority when communicating with larger number of vehicles while C-V2X should be given priority when less number of vehicles are requesting to connect with the RSU.
Nuno M. Paulino and Luis M. Pessoa (INESC TEC & Faculty of Engineering, University of Porto, Portugal); André Branquinho and Edgar Gonçalves (Wavecom, Portugal)
The recent Bluetooth 5.1 specification introduced the use of Angle-of-Arrival (AoA) information which enables the design of novel low-cost indoor positioning systems. Existing approaches rely on multiple fixed gateways equipped with antenna arrays, in order to determine the location of an arbitrary number of simple mobile omni-directional emitters. In this paper, we instead present an approach where mobile receivers are equipped with antenna arrays, and the fixed infrastructure is composed of battery-powered beacons. We implement a simulator to evaluate the solution using a real-world data set of AoA measurements. We evaluated the solution as a function of the number of beacons, their transmission period, and algorithmic parameters of the position estimation. Sub-meter accuracy is achievable using 1.6 beacons per 10m2 and a beacon transmission period of 500 ms.
Filipe Conceição (InterDigital Europe, United Kingdom (Great Britain)); Carlos Guimarães (Universidad Carlos III de Madrid, Spain); Luca Cominardi (ADLINK Technology, France); Samer T. Talat (Industrial Technology Research Institute, Taiwan); Muhammad Febrian Ardiansyah (National Chiao Tung University, Taiwan); Chao Zhang (Ericsson, United Kingdom (Great Britain)); Milan Groshev (Universidad Carlos III de Madrid, Spain); Timothy William (National Chiao Tung University, Taiwan); Gyanesh Patra (Ericsson Research, Sweden); Ibrahim Hemadeh (InterDigital, United Kingdom (Great Britain)); Chenguang Lu (Ericsson Research, Sweden); Alain Abdel-Majid Mourad (InterDigital, United Kingdom (Great Britain))
The 5G Edge Intelligence for Vertical Experimentation (5G-DIVE) project aims at demonstrating the technical merits and business value proposition of 5G technologies in two vertical pilots, namely the Industry 4.0 (I4.0) and Autonomous Drones Scout (ADS) pilots. This paper presents an overview of the overall 5G-DIVE solution and reports the results of the initial validation campaign of the selected use case, featuring 5G connectivity, distributed Edge computing, and artificial intelligence. The initial results for the I4.0 provide a baseline for next step validation campaign targeting a broader scale 5G implementation, while the ADS results provides promising results for enhancing the autonomous navigation in real-time.