Fabio Tango | Università degli Studi di Torino (original) (raw)

Papers by Fabio Tango

Knowledge and Information Systems, 2019

There is an accumulating evidence that distracted driving is a leading cause of vehicle crashes a... more There is an accumulating evidence that distracted driving is a leading cause of vehicle crashes and accidents. In order to support safe driving, numerous methods of detecting distraction have been proposed, which are empirically focused on certain driving contexts and gaze behavior. This paper aims at illustrating a method for the non-intrusive and real-time detection of visual distraction based on vehicle dynamics data and environmental data, without using eye-tracker information. Experiments are carried out in the context of the automotive domain of the European project Holides, which addresses development and qualification of Adaptive Cooperative Human-Machine Systems, and is co-funded by ARTEMIS Joint Undertaking and Italian University, Educational and Research Department. The collected data are analised by a single layer feedforward neural network trained through pseudo-inversion methods, characterized by direct determination of output weights given randomly set input weights and biases. One main feature of our work is the convenient setting of input weights by the so called random projections: the presence of a great number of null elements in the involved matrices makes especially parsimonious the use at run time of the trained network. Moreover, we use a genetic approach to better explore the input weights network space. The obtained results show both better performance with respect to classical methods and effective and parsimonious use of memory resources.

International Joint Conference on Artificial Intelligence, 2018

Abstract. The FP7 EU project ISi-PADAS aims at conceiving an intelligent system, called PADAS, to... more Abstract. The FP7 EU project ISi-PADAS aims at conceiving an intelligent system, called PADAS, to support drivers, which intervenes continuously from warning up to automatic braking in the whole longitudinal control of the vehicle. However, such supporting systems can have some unwanted sideeffect: due to the presence of automation in the driving task, less attention and reaction are needed by the drivers to intervene in the longitudinal control of the vehicle. Such a paper aims at investigating the effects of the level of automation on drivers, in particular on their Situation Awareness, when the user is supported by a specific PADAS application, integrated with a driver’s distraction classifier.

IEEE Transactions on Intelligent Transportation Systems

Autonomous vehicles (AVs) must share space with pedestrians, both in carriageway cases such as ca... more Autonomous vehicles (AVs) must share space with pedestrians, both in carriageway cases such as cars at pedestrian crossings and off-carriageway cases such as delivery vehicles navigating through crowds on pedestrianized high-streets. Unlike static and kinematic obstacles, pedestrians are active agents with complex, interactive motions. Planning AV actions in the presence of pedestrians thus requires modelling of their probable future behaviour as well as detecting and tracking them. This narrative review article is Part II of a pair, together surveying the current technology stack involved in this process, organising recent research into a hierarchical taxonomy ranging from lowlevel image detection to high-level psychological models. This selfcontained Part II covers the higher levels of this stack, consisting of models of pedestrian behaviour, from prediction of individual pedestrians' likely destinations and paths, to game-theoretic models of interactions between pedestrians and autonomous vehicles. This survey clearly shows that, although there are good models for optimal walking behaviour, high-level psychological and social modelling of pedestrian behaviour still remains an open research question that requires many conceptual issues to be clarified. Early work has been done on descriptive and qualitative models of behaviour, but much work is still needed to translate them into quantitative algorithms for practical AV control.

IFAC Proceedings Volumes

Abstract The purpose of a Traffic Risk Estimation module is to assess the traffic situation aroun... more Abstract The purpose of a Traffic Risk Estimation module is to assess the traffic situation around the vehicle and the involved risks for the driver and passengers. This paper presents, from the functional point of view, a draft of the specification and the architecture of the TRE module. The use of TRE inside the AWAKE project architecture is proposed; the flow and the content of information inside TRE is outlined.

Intelligent Vehicle Symposium, 2002. IEEE, 2003

This paper is based on the current activities undertaken within the three-year project EUCLIDE [G... more This paper is based on the current activities undertaken within the three-year project EUCLIDE [GRDl-2000-268011 "Enhanced human machine interface for on vehicle integrated driving support system" funded by the European Commission within the 5". Framework Programme " ...

Sensors (Basel, Switzerland), 2021

Interest in autonomous vehicles (AVs) has significantly increased in recent years, but despite th... more Interest in autonomous vehicles (AVs) has significantly increased in recent years, but despite the huge research efforts carried out in the field of intelligent transportation systems (ITSs), several technological challenges must still be addressed before AVs can be extensively deployed in any environment. In this context, one of the key technological enablers is represented by the motion-planning and control system, with the aim of guaranteeing the occupants comfort and safety. In this paper, a trajectory-planning and control algorithm is developed based on a Model Predictive Control (MPC) approach that is able to work in different road scenarios (such as urban areas and motorways). This MPC is designed considering imitation-learning from a specific dataset (from real-world overtaking maneuver data), with the aim of getting human-like behavior. The algorithm is used to generate optimal trajectories and control the vehicle dynamics. Simulations and Hardware-In-the-Loop tests are car...

The ADVISORS project ('Action for advanced Driver assistance and Vehicle control systems Impl... more The ADVISORS project ('Action for advanced Driver assistance and Vehicle control systems Implementation, Standardization, Optimum use of the Road network and Safety') is a joint initiative under the Competitive and Sustainable Growth Program within the fifth Framework of the European Commission (EC). The project is co-funded by DG TREN of the EC. The main objective of the ADVISORS consortium is to promote the assessment, development and implementation of Advanced Driver Assistance Systems (ADAS). Thus, the ADVISORS project aims to contribute to the improvement of road traffic safety, to an efficient utilization of the available road network, and to a reduced environmental loading in Europe. In this context, an important issue is the pilot evaluation of the ADA systems; in particular, the aim of this paper is to present the methodology and the results of the tests performed to evaluate the lateral support system.

Since the last decade, development efforts by academia and industry for automated driving functio... more Since the last decade, development efforts by academia and industry for automated driving functions have increased significantly. Also, the European research project AdaptIVe is looking into this topic. Due to the large operation spaces and various complex situations that are covered by these functions, efforts for evaluation increase also significantly. Within AdaptIVe, a comprehensive evaluation approach for automated driving functions ranging from SAE level 2-4 has been developed [1]. The approach splits the evaluation into technical, user-related, in-traffic and impact assessment addressing safety and environmental effects of automated driving. For each evaluation type appropriate test tools and methods are selected e.g. field test for technical assessment, trials on test track and in real traffic for the user-related assessments and simulations for the in-traffic and impact assessment. Next to the assessment type also the characteristics of the function must be considered when ...

Abschlussbericht fur das AP5 (Empirical Human Factor Analysis Techniques and Tools) des EU-Projek... more Abschlussbericht fur das AP5 (Empirical Human Factor Analysis Techniques and Tools) des EU-Projektes HoliDes.

Applied Sciences, 2021

The “classical” SAE LoA for automated driving can present several drawbacks, and the SAE-L2 and S... more The “classical” SAE LoA for automated driving can present several drawbacks, and the SAE-L2 and SAE-L3, in particular, can lead to the so-called “irony of automation”, where the driver is substituted by the artificial system, but is still regarded as a “supervisor” or as a “fallback mechanism”. To overcome this problem, while taking advantage of the latest technology, we regard both human and machine as members of a unique team that share the driving task. Depending on the available resources (in terms of driver’s status, system state, and environment conditions) and considering that they are very dynamic, an adaptive assignment of authority for each member of the team is needed. This is achieved by designing a technology enabler, constituted by the intelligent and adaptive co-pilot. It comprises (1) a lateral shared controller based on NMPC, which applies the authority, (2) an arbitration module based on FIS, which calculates the authority, and (3) a visual HMI, as an enabler of tr...

This paper describes a holistic preventive safety application named “Continuous Support”, develop... more This paper describes a holistic preventive safety application named “Continuous Support”, developed in the “interactIVe” Framework Programme 7 EU project. The function is implemented following the metaphor of a co-driver. The paper introduces the simulation theory of human cognition and sets out consequent design principles for the co-driver. A second section describes the implementation of these principles in the CRF demonstrator vehicle. The architecture combines a behavioural subsumtive hierarchy with forward and inverse emulators. It is able to infer driver intentions by re-generating observed human behaviours. The system is also able to rectify incorrect behaviours. The last section summarizes the most important lessons learnt.

Proceedings of the 16th International Conference on Information Fusion, 2013

Perceiving the environment is a fundamental task for Advance Driver Assistant Systems. While simu... more Perceiving the environment is a fundamental task for Advance Driver Assistant Systems. While simultaneous localization and mapping represents the static part of the environment, detection and tracking of moving objects aims at identifying the dynamic part. Knowing the class of the moving objects surrounding the vehicle is a very useful information to correctly reason, decide and act according to each class of object, e.g. car, truck, pedestrian, bike, etc. Active and passive sensors provide useful information to classify certain kind of objects, but perform poorly for others. In this paper we present a generic fusion framework based on Dempster-Shafer theory to represent and combine evidence from several sources. We apply the proposed method to the problem of moving object classification. The method combines information from several lists of moving objects provided by different sensor-based object detectors. The fusion approach includes uncertainty from the reliability of the sensor...

2008 11th International Conference on Information Fusion, 2008

The aim of this paper is to present a multiple object tracking data fusion technique, which fuses... more The aim of this paper is to present a multiple object tracking data fusion technique, which fuses radar, image, and ego vehicle odometry. The data are fused at a high level, which leads to reliable and stable tracking results providing also additional features as width estimation and the detection of stationary objects. A ldquorealrdquo application of these algorithms is illustrated on a specific use-case: the SASPENCE system, developed inside the Integrated Project PReVENT. The principle results show that such a data-fusion technique is actually able to improve the SASPENCE performances, especially in terms of extension of operative scenarios, a basic issue for the system functionality.

The IN-ARTE system is a Driver Support System that helps the driver in managing longitudinal cont... more The IN-ARTE system is a Driver Support System that helps the driver in managing longitudinal control tasks through integrated use of front looking radar, digital road maps, and navigation system. Information collected from different sources is combined and then provided to the driver in order to help him/her through visual (icons) and acoustical (voice) messages and, in critical situations, also through automatic intervention on vehicle control. This paper describes the system defined and realised inside the IN-ARTE European project and gives a summary of main results achieved in simulator studies and field tests. For the covering abstract see ITRD E114174.

The Preventive and Active Safety Applications project (PReVENT), contributes to the safety goals ... more The Preventive and Active Safety Applications project (PReVENT), contributes to the safety goals of the European Commission (EC). PReVENT addresses the function fields of safe speed and safe following, lateral support, intersection safety and protection of vulnerable road users and collision mitigation in order to cover the field of active safety. The majority of these functions are characterized by using perception strategies based on multi sensor platforms and multi-sensor data fusion. ProFusion as cross-functional activity has the responsibility to streamline the multi sensor data fusion in the functional field activities. This paper presents several aspects of the research work conducted in ProFusion2 (PF2). For the covering abstract see ITRD E134653.

This paper illustrates the concept of "co-pilot" as an enabling technology for autonomous driving... more This paper illustrates the concept of "co-pilot" as an enabling technology for autonomous driving. A co-pilot system mixes the features of commercial Advanced Driver Assistance Systems (like blind spot, forward-collision warning, lane change assistant, overtaking assistant, and others) with human factors like driver distraction and intention. The copilot can provide a "suggested action" to the human driver through a dedicated Human-Machine Interface (a set of screens on the dashboard) or, alternatively, can be the enabling technology to build effective and user-friendly future intelligent transportation systems (i.e. Autonomous Driving Functions). We illustrate the results achieved by the European projects HoliDes and the next steps foreseen in the EU project AutoMate.

Driving automation is radically changing the role of the driver. The proliferation of driving ass... more Driving automation is radically changing the role of the driver. The proliferation of driving assistance systems is increasingly transforming driver’s tasks from vehicle control operations to supervising activities. However, the process of turning the driver into a passenger is far from being accomplished. This paper describes an innovative interaction approach developed in the framework of EU funded project AutoMate. The overarching aim of AutoMate is to build a “TeamMate System”, in which the human and the automation cooperate with each other to achieve a safe, pleasant and efficient driving. Through an effective interaction, and by sharing perception, decision and action, they can negotiate specific behaviors and maneuvers in order to build a team based on trust. In order to measure the effectiveness of this concept, a driving simulator experiment has been conducted: findings suggest that the concept of Human-Machine Team can increase the trust in automation and improve the effic...