From Simulation to Real World Maneuver Execution using Deep Reinforcement Learning

Deep Reinforcement Learning has proved to be able to solve many control tasks in different fields, but the behavior of these systems is not always as expected when deployed in real-world scenarios. This is mainly due to the lack of domain adaptation between simulated and real-world data together with the absence of distinction between train and test datasets. In this work, we investigate these problems in the autonomous driving field, especially for a maneuver planning module for roundabout insertions. In particular, we present a system based on multiple environments in which agents are trained simultaneously, evaluating the behavior of the model in different scenarios. Finally, we analyze techniques aimed at reducing the gap between simulated and real-world data showing that this increased the generalization capabilities of the system both on unseen and real-world scenarios.Comment: Intelligent Vehicle Symposium 2020 (IV2020

Partial stellar tidal disruption events and their rates

Tidal disruption events (TDEs) of stars operated by massive black holes (MBHs) will be detected in thousands by upcoming facilities such as the Vera Rubin Observatory. In this work, we assess the rates of standard total TDEs, destroying the entire star, and partial TDEs, in which a stellar remnant survives the interaction, by solving 1-D Fokker-Planck equations. Our rate estimates are based on a novel definition of the loss cone whose size is commensurate to the largest radius at which partial disruptions can occur, as motivated by relativistic hydrodynamical simulations. Our novel approach unveils two important results. First, partial TDEs can be more abundant than total disruptions by a factor of a few to a few tens. Second, the rates of complete stellar disruptions can be overestimated by a factor of a few to a few tens if one neglects partial TDEs, as we find that many of the events classified at total disruptions in the standard framework are in fact partial TDEs. Accounting for partial TDEs is particularly relevant for galaxies harbouring a nuclear stellar cluster featuring many events coming from the empty loss cone. Based on these findings, we stress that partial disruptions should be considered when constraining the luminosity function of TDE flares; accounting for this may reconcile the theoretically estimated TDE rates with the observed ones.Comment: 12 pages + Appendix, MNRAS, accepte

Scenario-Driven Search for Pedestrians aimed at Triggering Non-Reversible Systems

Abstract-This paper presents the results of an innovative approach to pedestrian detection for automotive applications in which a non-reversible system is used; therefore the aim is to reach a very low false detection rate, ideally zero, by searching for pedestrians in specific areas only. The great advantages of such an approach are that pedestrian recognition is performed on limited image areas-therefore boosting its timing performance- and no assessment on the danger level is finally required before providing the result to either the driver or an on-board computer for automatic manoeuvres. This system has been extensively tested on two prototype vehicles equipped with one laserscanner, one camera, and brakeby-wire technology both in Italy and Korea; this paper describes the extensive tests and shows performance measurements. I

Stereo obstacle detection in challenging environments: The VIAC experience

experienc

Vision-only fully automated driving in dynamic mixed-traffic scenarios

In this work an overview of the local motion planning and dynamic perception framework within the V-Charge project is presented. This framework enables the V-Charge car to autonomously navigate in dynamic mixed-traffic scenarios. Other traffic participants are detected, classified and tracked from a combination of stereo and wide-angle monocular cameras. Predictions of their future movements are generated utilizing infrastructure information. Safe motion plans are acquired with a system-compliant sampling-based local motion planner. We show the navigation performance of this vision-only autonomous vehicle in both simulation and real-world experiments

Intelligent Vehicles

International audience; This chapter describes the emerging robotics application field of intelligent vehicles motor vehicles that have autonomous functions and capabilities. The chapter is organized as follows:- Section 62.1 provides a motivation for why the development of intelligent vehicles is important, a brief history of the field, and the potential benefits of the technology.- Section 62.2 describes the technologies that enable intelligent vehicles to sense vehicle, environment, and driver state, work with digital maps and satellite navigation, and communicate with intelligent transportation infrastructure.- Section 62.3 describes the challenges and solutions associated with road scene understanding a key capability for all intelligent vehicles.- Section 62.4 describes advanced driver assistance systems, which use the robotics and sensing technologies described earlier to create new safety and convenience systems for motor vehicles, such as collision avoidance, lane keeping, and parking assistance.- Section 62.5 describes driver monitoring technologies that are being developed to mitigate driver fatigue, inattention, and impairment.- Section 62.6 describes fully autonomous intelligent vehicles systems that have been developed and deployed.- Sections 62.7 and 62.8 conclude the chapter with a discussion of future prospects, and provide references to further reading and additional resources. Document type: Part of book or chapter of boo

H3 K27M mutation in rosette-forming glioneuronal tumors: a potential diagnostic pitfall

According to the fifth edition of the World Health Organization (WHO) classification of tumors of the central nervous system (CNS), diffuse midline glioma H3 K27-altered is a grade 4 infiltrative glioma that arises from midline anatomical structures and is characterized by the loss of H3 K27me3 and co-occurring H3 K27M mutation or EZHIP overexpression. However, the H3 K27M mutation has also been observed in circumscribed gliomas and glioneuronal tumors arising in midline anatomical structures, which may result in diagnostic pitfalls.Rosette-forming glioneuronal tumor (RGNT) is a CNS WHO grade 1 neoplasm that histologically features neurocytic and glial components and originates in midline anatomical structures.This study aimed to assess whether RGNTs, similar to other midline tumors, may exhibit immunohistochemical loss of H3 K27me3 and harbor the H3 K27M mutation.All seven analyzed RGNTs displayed immunohistochemical loss of H3 K27me3 in all tumor cells or H3 K27me3 mosaic immunostaining. In one case, H3 K27me3 loss was associated with the H3 K27M mutation, whereas the other six cases did not exhibit any H3 mutations or EZHIP overexpression. During a follow-up period of 23 months, the H3 K27M-mutant case remained unchanged in size despite partial resection, indicating that the H3 mutation may not confer higher biological aggressiveness to RGNT.The immunohistochemical loss of H3 K27me3 co-occurring with the H3 K27M mutation may result in the potential misdiagnosis of RGNT, especially in cases of small biopsy specimens consisting of only the glial component

Système de stéréovision pour la détection d'obstacles et de véhicule en temps réel

Dans le cadre de l'aide à la conduite automobile, nous présentons deux méthodes de détection d'obstacles et de détection de véhicule à partir de notre système embarquable de stéréovision. Ces deux tâches sont effectuées en temps réel en segmentant des cartes éparses de profondeur par sélection de segments 3D. Pour la détection d'obstacles, la sélection des segments 3D s'effectue à partir du calcul de leur angle d'inclinaison. La détection de véhicule s'effectue à partir des données fournies par ARGO, le véhicule expérimental autonome développé à l'Université de Parme