{"title":"Why Is Network Reselection an Issue for Cross-Border Vehicular Applications?","authors":"Marco Centenaro, Riccardo Fedrizzi, L. Vangelista","doi":"10.23919/AEITAUTOMOTIVE50086.2020.9307403","DOIUrl":"https://doi.org/10.23919/AEITAUTOMOTIVE50086.2020.9307403","url":null,"abstract":"Safety-critical advanced driver-assistance systems (ADAS) are expected to benefit from cellular vehicle-to-everything communication, providing both short-range and long-range wireless connectivity between vehicles and road/network infrastructure equipment. However, upon switching between adjacent coverage areas belonging to different network operators, the wireless connectivity may be discontinued. This issue prevents network service continuity and causes interruption of ADAS service availability. In this paper, we aim at assessing the average duration of service interruption due to such network reselection procedures. We provide performance evaluation results highlighting that there is a wide gap between the best case scenario and the worst case scenario. Moreover, we propose a simple heuristic to limit the downside of the lack of cooperation between network operators; our heuristic algorithm, which does not require a tight integration between the operators, performs much better than the worst case and it is fairly comparable with the best case scenario. Nevertheless the present work highlights the importance of a tighter integration between network operators to reduce the delay to the minimum.","PeriodicalId":104806,"journal":{"name":"2020 AEIT International Conference of Electrical and Electronic Technologies for Automotive (AEIT AUTOMOTIVE)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129714684","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Performance assessment of the IEEE 802.1Qch in an automotive scenario","authors":"Luca Leonardi, L. L. Bello, Gaetano Patti","doi":"10.23919/AEITAUTOMOTIVE50086.2020.9307422","DOIUrl":"https://doi.org/10.23919/AEITAUTOMOTIVE50086.2020.9307422","url":null,"abstract":"Technological advancements in automotive require networks able to support multiple communication requirements, such as reliability, real-time, low jitter, and strict delay bounds. Switched Ethernet with Time-Sensitive Networking (TSN) standards is boosting its popularity in the automotive field, thanks to its ability to offer high bandwidth, real-time support and significant reduction of cabling costs. This paper provides a performance assessment of the Cyclic Queuing and Forwarding protocol defined in the IEEE 802.1Q-2018 standard through OMNeT++ simulations in an automotive scenario that includes Advanced Driver Assistance (ADAS) and Infotainment applications on a single Switched Ethernet network.","PeriodicalId":104806,"journal":{"name":"2020 AEIT International Conference of Electrical and Electronic Technologies for Automotive (AEIT AUTOMOTIVE)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122781834","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pavlos Kosmides, K. Demestichas, Konstantinos Avgerinakis, Eleni Trouva, Stefano Bianchi, A. Barisone, Konstantinos Risvas, K. Moustakas, Aleksandra Rodak, M. Kruszewski, Malgorzata Pedzierska
{"title":"Bringing Trust to Autonomous Mobility","authors":"Pavlos Kosmides, K. Demestichas, Konstantinos Avgerinakis, Eleni Trouva, Stefano Bianchi, A. Barisone, Konstantinos Risvas, K. Moustakas, Aleksandra Rodak, M. Kruszewski, Malgorzata Pedzierska","doi":"10.23919/AEITAUTOMOTIVE50086.2020.9307432","DOIUrl":"https://doi.org/10.23919/AEITAUTOMOTIVE50086.2020.9307432","url":null,"abstract":"Last decade has been characterized by a huge advancement in the field of automated and connected transport. However, fully autonomous systems still need a lot of effort in order to be applied in transportation. Meanwhile, mixed traffic environments with semi-autonomous vehicles is becoming a norm. In such conditions, vehicles are passing the dynamic driving task back to the human by sending to drivers Requests to Intervene (RtI). At the same time, there is a need to evolve driver’s training in order to be able to safely use semi-automated vehicles, whereas driver intervention performance has to be made an integral part of both driver and technology assessment. Furthermore, the ethical implications of automated decision-making need to be properly assessed, giving rise to novel risk and liability analysis models. In this conceptual paper we present our vision to maximise the safety, trust and acceptance of automated vehicles. To achieve that, we propose an assessment framework to evaluate different technologies involved in Automated Driving Systems (ADS).","PeriodicalId":104806,"journal":{"name":"2020 AEIT International Conference of Electrical and Electronic Technologies for Automotive (AEIT AUTOMOTIVE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115703084","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
F. Rundo, S. Conoci, S. Battiato, F. Trenta, C. Spampinato
{"title":"Innovative Saliency based Deep Driving Scene Understanding System for Automatic Safety Assessment in Next-Generation Cars","authors":"F. Rundo, S. Conoci, S. Battiato, F. Trenta, C. Spampinato","doi":"10.23919/AEITAUTOMOTIVE50086.2020.9307425","DOIUrl":"https://doi.org/10.23919/AEITAUTOMOTIVE50086.2020.9307425","url":null,"abstract":"Visual saliency is the human attention mechanism that encodes such visio-sensing information to extract features from the observation scene. In the last few years, visual saliency estimation has received significant research interests in the automotive field. While driving the vehicle, the car driver focuses on specific objects rather than others by deterministic brain-driven saliency mechanisms inherent perceptual activity. In this study, we propose an intelligent system that combines a driver’s drowsiness detector with a saliency-based scene understanding pipeline. Specifically, we implemented ad-hoc 3D pre-trained Semantic Segmentation Deep Network to process the frames captured by automotive-grade camera device placed outside the car. We used an embedded platform based on the STA1295 core (ARM A7 Dual-Cores) with a hardware accelerator for hosting the proposed pipeline. Besides, we monitor the car driver’s drowsiness by using an innovative bio-sensor installed on the steering wheel, to collect the PhotoPlethysmoGraphy (PPG) signal. Ad-hoc 1D Temporal Deep Convolutional Network has been designed to classify the collected PPG time-series in order to assess the driver’s attention level. Finally, we compare the detected car driver’s attention level with corresponding saliency-based scene classification in order to assess the overall safety level. Experimental results confirm the effectiveness of the proposed pipeline.","PeriodicalId":104806,"journal":{"name":"2020 AEIT International Conference of Electrical and Electronic Technologies for Automotive (AEIT AUTOMOTIVE)","volume":"66 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115881395","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
R. Letor, F. Scrimizzi, G. Longo, F. Iucolano, M. Moschetti
{"title":"Compact design of DC/DC converter with new STi2GaN solution","authors":"R. Letor, F. Scrimizzi, G. Longo, F. Iucolano, M. Moschetti","doi":"10.23919/AEITAUTOMOTIVE50086.2020.9307412","DOIUrl":"https://doi.org/10.23919/AEITAUTOMOTIVE50086.2020.9307412","url":null,"abstract":"ST, following its historical leadership position in Smart Power Technologies, is introducing the new STi2GaN Product Family for both 100V and 650V Voltage clusters: System in package with Si controller and Monolithic approach integrating the power stage with driver and protections will produce two main product clusters that, combined with proper packaging, will allow best ever application performances including a significant improvement for high efficiency and low emission rates. Using the example of a new monolithic H-Bridge designed for automotive 48V-12V DC/DC converter, this paper illustrates how STi2GaN technology aids the design of high-density power converter.","PeriodicalId":104806,"journal":{"name":"2020 AEIT International Conference of Electrical and Electronic Technologies for Automotive (AEIT AUTOMOTIVE)","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132595145","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
L. Abbatelli, M. Cacciato, Domenico Paternostro, S. Rizzo, G. Scarcella, G. Scelba
{"title":"Performance Assessment of an Automotive-grade TO-247 IGBT copacked with SiC diode in a bidirectional buck converter","authors":"L. Abbatelli, M. Cacciato, Domenico Paternostro, S. Rizzo, G. Scarcella, G. Scelba","doi":"10.23919/AEITAUTOMOTIVE50086.2020.9307374","DOIUrl":"https://doi.org/10.23919/AEITAUTOMOTIVE50086.2020.9307374","url":null,"abstract":"Various sustainable mobility applications adopt bidirectional dc-dc converters to optimally manage the power flow among the power supply, the load and the battery. In this context, the use of Silicon Carbide (SiC) technologies leads many advantages from efficiency and reliability point of view. Copacking the discrete IGBT with SiC diode enables to operate at switching frequency higher than the standard devices. In this work, an automotive-grade TO-247 IGBT copacked with SiC diode has been compared with a standard one, in a bidirectional buck-converter. The experimental results have highlighted that, under the same switching frequency and temperature conditions, the former can handle an extra load with respect to the IGBTs copacked with Si diodes, or a better efficiency being equal the load. The main merit of the work is to highlight the advantages of adopting antiparallel SiC diode in an actual device recently available in the market instead of using the prototypes adopted by previous papers. Moreover, it is also worth to note that these prototypes are not automotive grade.","PeriodicalId":104806,"journal":{"name":"2020 AEIT International Conference of Electrical and Electronic Technologies for Automotive (AEIT AUTOMOTIVE)","volume":"56 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126457291","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Hafeez Husain Cholakkal, S. Mentasti, M. Bersani, S. Arrigoni, M. Matteucci, F. Cheli
{"title":"LiDAR - Stereo Camera Fusion for Accurate Depth Estimation","authors":"Hafeez Husain Cholakkal, S. Mentasti, M. Bersani, S. Arrigoni, M. Matteucci, F. Cheli","doi":"10.23919/AEITAUTOMOTIVE50086.2020.9307398","DOIUrl":"https://doi.org/10.23919/AEITAUTOMOTIVE50086.2020.9307398","url":null,"abstract":"Dense 3D reconstruction of the surrounding environment is one the fundamental way of perception for Advanced Driver-Assistance Systems (ADAS). In this field, accurate 3D modeling finds applications in many areas like obstacle detection, object tracking, and remote driving. This task can be performed with different sensors like cameras, LiDARs, and radars. Each one presents some advantages and disadvantages based on the precision of the depth, the sensor cost, and the accuracy in adverse weather conditions. For this reason, many researchers have explored the fusion of multiple sources to overcome each sensor limit and provide an accurate representation of the vehicle’s surroundings. This paper proposes a novel post-processing method for accurate depth estimation, based on a patch-wise depth correction approach, to fuse data from LiDAR and stereo camera. This solution allows for accurate edges and object boundaries preservation in multiple challenging scenarios.","PeriodicalId":104806,"journal":{"name":"2020 AEIT International Conference of Electrical and Electronic Technologies for Automotive (AEIT AUTOMOTIVE)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114125772","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A Multi Battery EREV: an Innovative Structure to Improve Flexibility and Performances","authors":"S. Brofferio, E. Marazzi","doi":"10.23919/AEITAUTOMOTIVE50086.2020.9307419","DOIUrl":"https://doi.org/10.23919/AEITAUTOMOTIVE50086.2020.9307419","url":null,"abstract":"Several features and issues of internal combustion, electric and hybrid vehicles are reviewed. The series hybrid vehicle is motivated for a large diffusion of the electric mobility not requiring a capillary distribution of public recharging stations. An innovative structure of extended range electric vehicle based on a few battery modules and four electric traction motors is suggested to enhance the performances of the current electric vehicles. Two examples of the proposed multi battery structure with three or two battery modules are defined, analyzed and evaluated; their main performances are compared to the up to date similar structures.","PeriodicalId":104806,"journal":{"name":"2020 AEIT International Conference of Electrical and Electronic Technologies for Automotive (AEIT AUTOMOTIVE)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123999290","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Multi-State End-to-End Learning for Autonomous Vehicle Lateral Control","authors":"S. Mentasti, M. Bersani, M. Matteucci, F. Cheli","doi":"10.23919/AEITAUTOMOTIVE50086.2020.9307428","DOIUrl":"https://doi.org/10.23919/AEITAUTOMOTIVE50086.2020.9307428","url":null,"abstract":"Lateral control is one of the primary requirements of an autonomous vehicle. This task is generally performed using complex pipelines, which include line detection trough neural network processing, vehicle state estimation, and planning. What we propose in this paper is an alternative end-to-end approach to the problem. Images acquired by a camera mounted on the vehicle are processed by two convolutional neural networks to directly retrieve the steering command. In particular, we propose an architecture built using two connected neural networks, one to predict the scenario the vehicle is facing and one, conditioned on possible situations, to predict the steering command. In our work, we also analyze the potential of a computer-generated dataset for a demanding task like end-to-end learning, where the image quality is fundamental. All the training is then performed on synthetic images, while the testing is done on real data acquired by an experimental vehicle.","PeriodicalId":104806,"journal":{"name":"2020 AEIT International Conference of Electrical and Electronic Technologies for Automotive (AEIT AUTOMOTIVE)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127685223","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Design of a High-Speed Electric Propulsion System for Electric Vehicles","authors":"Andrea Floris, M. Porru, A. Damiano, A. Serpi","doi":"10.23919/AEITAUTOMOTIVE50086.2020.9307376","DOIUrl":"https://doi.org/10.23919/AEITAUTOMOTIVE50086.2020.9307376","url":null,"abstract":"A novel high-speed electric propulsion system for automotive applications is presented in this paper. It consists of a high-speed ferrite-based permanent magnet synchronous machine with a wide constant-power speed range, which is coupled to the vehicle wheels through a double-stage magnetic gear transmission system. Both the electrical machine and the magnetic gear have been designed based on advanced mechanical and electromagnetic modelling in order to comply with all design targets and constraints. The proposed solution has been evaluated by means of a simulation study, which is performed in MATLAB-Simulink. Particularly, a performance assessment has been carried out by referring to different driving cycles and case studies, namely a conventional low-speed electric propulsion system equipped with a mechanical single-gear transmission system and the proposed high-speed electric propulsion system driven by two different control strategies for comparison purposes.","PeriodicalId":104806,"journal":{"name":"2020 AEIT International Conference of Electrical and Electronic Technologies for Automotive (AEIT AUTOMOTIVE)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127873409","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}