Automated driving needs unprecedented levels of reliably and safety before marked deployment. The average human driver fatal accident rate is 1 every 100 million miles. Automated vehicles will have to provably best these figures. This paper introduces the notion of dream-like mechanisms as a simulation technology to produce a large number of hypothetical design and test scenarios — especially focusing on variations of more frequent dangerous and near miss events. Grounded in the simulation hypothesis of cognition, we show here some principles for effective simulation mechanisms and an artificial cognitive system architecture that can learn from the simulated situations.

The EU 6th Framework Programme Integrated Project AIDE (Adaptive Integrated Driver-vehicle interfacE), was a 50 month project, with 31 partners, including all major European vehicle manufacturers, the main suppliers and a range of leading research institutes and universities. The general objective of the AIDE Integrated Project has been the generation of the knowledge and the development of methodologies and human-machine interface technologies required for safe and efficient integration of ADAS, IVIS and nomad devices into the driving environment. The third sub-project of AIDE aimed at the design, development and demonstration of the innovative adaptive and integrated driver-vehicle interface concept. This entails a unified human-machine interface that resolves conflicts and exploits synergies between different in-vehicle systems. The paper focuses on the presentation of the work emanating from the third sub-project of AIDE presenting the general features of the innovative human-machine interface realized within AIDE, including the results achieved with the demonstration of the system in three prototype vehicles.

The Adaptive Integrated Driver-vehicle interfacE (AIDE) is an integrated project funded by the European Commission in the Sixth Framework Programme. The project, which involves 31 partners from the European automotive industry and academia, deals with behavioral and technical issues related to automotive human-machine interface (HMI) design, with a particular focus on integration and adaptation. The project involves tightly integrated empirical research, driver-behavior modeling, and methodological and technological development. This paper provides an overview of the AIDE Sub-Project 3 results dealing with the design, development, and integration of the AIDE system in three prototype vehicles, together with the evaluation results of the trials.

Car evolution The car was born around a century ago and its evolution has been incredibly fast, both in technology and in style. We have to move through different social and cultural evolutions to arrive to the present state of the art. The technical and social acceleration of the 20th century is well visible looking at the different worldwide research programs. Nowadays digital content and ubiquitous computing are changing us and our life style. New concepts involving the full society are emerging and the term “personal mobility” becomes more and more used together with “co-operative driving” and “environmental compatibility”. HMI evolution Human Machine Interaction (HMI), initially limited only to the primary in-vehicle commands, has been a major issue since the beginning. In which direction is it moving? Which technological efforts will be key factors to face the challenges of the future? We are in the middle of a transition phase where the world has to cope with and to solve big problems as energy and climate change that can strongly influence the future of the automotive industry and not only.

Path prediction is the only way that an active safety system can predict a driver's intention. In this paper, a model-based description of the traffic environment is presented - both vehicles and infrastructure - in order to provide, in real time, sufficient information for an accurate prediction of the ego-vehicle's path. The proposed approach is a hierarchical-structured algorithm that fuses traffic environment data with car dynamics in order to accurately predict the trajectory of the ego-vehicle, allowing the active safety system to inform, warn the driver, or intervene when critical situations occur. The algorithms are tested with real data, under normal conditions, for collision warning (CW) and vision-enhancement applications. The results clearly show that this approach allows a dynamic situation and threat assessment and can enhance the capabilities of adaptive cruise control and CW functions by reducing the false alarm rate.

WATCH-OVER is a European Specific Targeted project co-funded by the European Commission Information Society and Media within the initiatives of the cooperative systems for traffic safety and efficiency based on communication and sensor technologies. The project, supported by EUCAR and coordinated by Centro Ricerche Fiat, includes in its consortium vehicle and motorcycle makers, technology, automotive suppliers and research centres for the design, development and testing phase. The main goal of the WATCH-OVER project is to avoid road accidents that involve vulnerable road users such as pedestrians, cyclists and motorcyclists. The innovative system concept, presented in this paper, will be represented by the cooperation of an on-board platform and a vulnerable user module. It is based on the interaction between an in-vehicle unit and users’ devices that will allow all road users to take an active part in traffic in urban and extra-urban areas. For that reason the WATCH-OVER project carries out research and development activities in order to design and develop an efficient system for accident prevention.

The European Specific Targeted Project WATCH-OVER is co-funded by the European Commission Information Society and media within the initiatives of the cooperative systems for traffic safety and efficiency based on communication and sensor technologies. The project, supported by EUCAR, is coordinated by Centro Richerche Fiat and includes in its consortium vehicle and motorcycle makers, technology, automotive suppliers and research centres for the design, development and testing phase. The core concept of the project is to enable the future availability of a modular cooperative system that will bring together sensor and communication technologies permitting all road users (the vehicles, the motorcycles, the bicycles and the pedestrians) to take an active part in the reduction of the number of accidents that involve vulnerable road users. The paper also gives a highlight of the definition of the relevant case of use and anticipates the architectural approach. For the covering abstract see ITRD E140665.

AIDE is an integrated project funded by the EC in the 6th Framework Programme. The project, which involves 30 partners including all major European vehicle manufacturers, deals with behavioural and technical issues related to automotive human-machine interface (HMI) design, with a particular focus on HMI integration and adaptation. The project involves tightly integrated empirical research, driver behaviour modelling and methodological- as well technological development. This paper provides an overview of the mid-term results achieved about half-way through the four-year project.

Nowadays, drivers have to cope with a growing amount of information coming from on-board information messages, telematics and advanced driver assistance systems. The interaction between the driver and these systems is critical, since they may distract the driver from the primary task of driving. The paper, addressing this problem, aims at presenting the methodological framework for the optimization of human machine interfaces (HMI) in the automotive research area; thus, the proper communication and interaction strategies are designed, in order to deliver to the driver a message or a warning in the optimal way in terms of driver safety. The proposed methodology is adopted in the COMUNICAR project and relevant results are presented. Last but not the least, the AIDE integrated project and its vision is also proposed as the roadmap for future activities in the HMI sector.

ABSTRACT The WATCH-OVER project, coordinated by Centro Ricerche Fiat, starting its activity in 2006, is aEuropean,project co-funded by the ,European Commission ,Information Society and Media within the initiatives of the ,cooperative systems for traffic safety and efficiency based on communication and sensor technologies. The core concept, presented in this paper, is to avoid road accidents that involve vulnerable users such as pedestrians, cyclists and motorcyclists in

AIDE is an integrated project funded by the EC in the 6th Framework Programme. The project, which involves 30 partners including all major European vehicle manufacturers, deals with behavioural and technical issues related to automotive human-machine interface (HMI) design, with a particular focus on HMI integration and adaptation. The project involves tightly integrated empirical research, driver behaviour modelling and methodological- as well as technological development. This paper provides an overview of the results achieved about half-way through the four-year project (A). For the covering abstract of the conference see ITRD E212343.

The SAFESPOT European Integrated Project is co-funded by the European Commission Information Society Technologies and starts its activities on the design and development of cooperative systems for road safety in 2006. The project, promoted by EUCAR (the research association of the Car Manufacturers), will last four years, it is coordinated by Centro Ricerche Fiat, it includes 50 partners from 12 different European countries (Italy, Germany, France, UK, Spain, Sweden, the Netherlands, Finland, Belgium, Greece, Poland, Hungary) among car makers, suppliers, road operators, service providers and research centres. The main aim of the project is to understand and assess, trough test in real condition, the potential of the cooperative approach in term of road transport safety improvement. This paper is an overall description of the project aims and objectives and addresses the first phase of the SAFESPOT project activities, namely the definition of the relevant use cases and scenarios of applications (A). For the covering abstract of the conference see ITRD E212343.

Automotive forward collision warning systems are based on range finders to detect the obstacles ahead and warn or intervene when a dangerous situation occur. However, the radar information by itself is not adequate to predict the future path of vehicles in collision avoidance systems due to the poor estimation of their lateral attribute. In order to face this problem, this paper proposes the utilization of a new Kalman based filter, whose measurement space includes data from a radar and a vision system. Given the superiority of vision systems in estimating azimuth and lateral velocity, the filter proves to be robust in vehicle maneuvers and curves. Results from simulated and real data are presented, providing comparative results with stand alone tracking systems and the cross-covariance technique in multisensor architectures.

The increasing in-vehicle information and safety systems tend to confuse and distract the driver from his/her primary driving task. This paper develops algorithms for the real-time supervision of the traffic and environmental scenario around the vehicle for the optimization of the Human Machine Interaction. The proposed algorithms reconstruct the scenario using stochastic motion models and Kalman filters, predict the intention of the driver using Demspter-Shafer decision fusion and calculate the level of risk in a deterministic way. The algorithms will be part of the Driver – Environment – vehicle state estimation in AIDE Integrated project.

This paper presents the principle of the design of the “intelligent core” of next generation driver vehicle interaction systems towards the objective to obtain a safe and sustainable mobility. Mobility in the future has to be characterised by a reduction both in number and in severity of accidents, has to facilitate the movement of every user and should be promoted towards “intermodality” to reduce traffic congestion and optimise travel planning. This causes an increasing demand for on board information systems. These needs together with the demand for new in-vehicle support and services and the users’ expectation to be connected to their own personal information systems is increasing the amount of interaction of the driver with the systems inside the vehicle thus raising the potential risk of driver's distraction and fatigue which are among the main causes of road accidents.

The increasing in-vehicle information and safety systems tend to confuse and distract the driver from his/her primary driving task. This paper develops algorithms for the real-time supervision of the traffic and environmental scenario around the vehicle for the optimization of the Human Machine Interaction. The proposed algorithms reconstruct the scenario using stochastic motion models and Kalman filters, predict the intention of the driver using Demspter-Shafer decision fusion and calculate the level of risk in using fuzzy logic. The algorithms will be part of the Driver - Environment - vehicle state estimation in AIDE Integrated project.

This paper presents the sub-project 3 of the AIDE (Adaptive Integrated Driver-vehicle Interface) Integrated Project; AIDE is a pan European project co-funded by the European Commission, coordinated by Volvo Technology and managed by a core group with the participation of both the industry (Bosch, CRF, PSA, and BMW) and the academia (ICCS, TNO, Joint Research Centre). The main objective of the SP3 and the paper is the design and development of an innovative adaptive integrated human-machine interface for driver assistance, information and nomad systems. To address this objective different modules are described which monitor in real time the driver, the environment and the vehicle and to which the HMI is adapted. The information data flow, the communications and the interaction is ensured by a dedicated centralized module, namely the Interaction and Communication Assistant (ICA), which is considered as the main innovation and is described in details in the paper.

The European Project EDEL “Enhanced driver's perception in poor visibility is a three years project co-funded by the European Commission INFSO. The project's aim is to develop a fully integrated driver support system for night vision application based on newly developed technologies. This paper presents the results of the first project phase related to the concept of driver's interaction with the system.