Abstract
Problem: The Adaptive Cruise Control is an Advanced Driver Assistance System (ADAS) that allows maintaining given headway and speed, according to settings pre-defined by the users. Despite the potential benefits associated to the utilization of ACC, previous studies warned against negative behavioral adaptations that might occur while driving with the system activated. Unfortunately, up to now, there are no unanimous results about the effects induced by the usage of ACC on speed and time headway to the vehicle in front. Also, few studies were performed including actual users of ACC among the subjects. Objectives: This research aimed to investigate the effect of the experience gained with ACC on speed and time headway for a group of users of the system. In addition, it explored the impact of ACC usage on speed and time headway for ACC users and regular drivers. Method: A matched sample driving simulator study was planned as a two-way (2 x 2) repeated measures mixed design, with the experience with ACC as between-subjects factor and the driving condition (with ACC and manually) as within-subjects factor. Results: The results show that the usage of ACC brought a small but not significant reduction of speed and, especially, the maintenance of safer time headways, being the latter result greater for ACC users, probably as a consequence of their experience in using the system. Summary: The usage of ACC did not cause any negative behavioral adaptations to the system regarding speed and time headway. Practical applications: Based on this research work, the Adaptive Cruise Control showed the potential to improve road safety for what concerns the speed and the time headway maintained by the drivers. The speed of the surrounding traffic and the minimum time headway settable through the ACC seem to have an important effect on the road safety improvement achievable with the system.

Abstract
Search and rescue (SAR) teams often face several complex and dangerous tasks, which could be aided by unmanned robotic vehicles (UV). UV agents can potentially be used to decrease the risk in the loss of lives both of the rescuers and victims and aid in the search and transportation of survivors and in the removal of debris in a catastrophe scenario. Depending on the nature of a catastrophe and its geographical location, there are potentially three types of UVs that can be deployed: aerial, surface and ground. Due to the control and manipulation particularities each type of UV contemplates, their operators need prior training and certification. To train and certify the operators a tool (serious game) is under development. In this paper we will make an overview about our approach in its development. This game uses a typical client-server architecture where all client agents (virtual UVs and operator client interfaces) share the same immersive virtual environment which is generated through the merging of GIS data and a semantic model extracted from 3D laser data. There will be several types of scenarios suitable to several types of catastrophe situations. Each of these scenarios has its own mission plan for the trainees to follow. The game will also provide an interface for mission planning so that each mission plan will be carefully designed to accurately correspond to a matrix of skills. This matrix lists a set of common skills in various different UV operational case studies which will allow the certification of operators.

Abstract
In Portugal the distribution of physicians is considered an appropriate proxy for the distribution of the actual hospital resources and additional information on hospital supply is mostly unavailable, while health care utilization data are also usually absent. A suitable method that can be used to analyze patients' access to hospital health care in countries with such characteristics is the two-step floating catchment area (2SFCA) method, since it requires only the number of physicians to represent supply and the population size to estimate demand. An improved version of the 2SFCA method is the kernel density 2SFCA (KD2SFCA) method. However, this method was not developed to analyze access to health care and it computes scores that express only the spatial access dimensions of proximity and availability. In this paper we present a new method, based on the KD2SFCA method, which improves health care access analysis and better identifies populations that are less empowered to use health care. We adapt the KD2SFCA method for the context of health care access analysis and extend it to capture additional access dimensions. We applied the extended method to the Portuguese hospital health care sector in a case study, and compared its results with those obtained with the KD2SFCA method. Our method was able to improve the identification of the less empowered populations and discovered that they represent 8.1% of the total population, instead of 4.6%, and reside in sixteen of the eighteen Portuguese districts, instead of in thirteen, as identified by the original KD2SFCA method. By improving the KD2SFCA method for the identification of the less empowered populations, our method can be a first step in an endeavor to identify opportunities to increase the health care supply or to redistribute supply resources, with the objective of increasing the access of those deprived populations.

Abstract
The development of Advanced Driver Assistance Systems ( ADAS) is rapidly growing. However, most of the ADAS require field test, which is expensive, unpredictable and time consuming. In this paper we propose a multiagent-based driving simulator which integrates a human factor analysis suite and enables rapid and low-cost experimentation of mobile-device ADAS. Our architecture uses a microscopic simulator and a serious-game-based driving simulator. The latter allows the user to control a vehicle and change the correspondent simulation state in the microscopic simulator. The driving simulator also connects to an Android device and sends several kinds of data, such as current GPS coordinates or transportation network data. One important feature of this architecture is its suitability to serve as an appropriate means to conduct behaviour elicitation through peer-designed agents, so as to improve modelling of various driving styles accounting for different aspects of preferences and perception abilities, as well as other performance measures related to drivers' interaction with ADAS solutions. The potentials of our approach to aid experiments in human factor analysis are still to be tested, but are undoubtedly huge and encouraging.

Abstract
"The Fifth Empire" is a single-player action adventure game in 2D. Centering around an adaptation of the myth the Fifth Empire (Nebuchadnezzar's dream and its interpretation by prophet Daniel) [1] is an epic allegory of the human condition, with a reinterpretation of European and Portuguese history as backdrop. This is a project that is still in process, which main goal is the development of an attractive videogame, with a strong and enriched educational purpose, since the game takes place in a real and historical setting. Moreover, through entertainment, the game should promote curiosity about the Portuguese history and motivate a more detailed study by the target audience.

Abstract
In this paper, a Training and Support system for Search and Rescue operations is described. The system is a component of the ICARUS project (http://www.fp7-icarus.eu) which has a goal to develop sensor, robotic and communication technologies for Human Search And Rescue teams. The support system for planning and managing complex SAR operations is implemented as a command and control component that integrates different sources of spatial information, such as maps of the affected area, satellite images and sensor data coming from the unmanned robots, in order to provide a situation snapshot to the rescue team who will make the necessary decisions. Support issues will include planning of frequency resources needed for given areas, prediction of coverage conditions, location of fixed communication relays, etc. The training system is developed for the ICARUS operators controlling UGVs (Unmanned Ground Vehicles), UAVs (Unmanned Aerial Vehicles) and USVs (Unmanned Surface Vehicles) from a unified Remote Control Station (RC2). The Training and Support system is implemented in SaaS model (Software as a Service). Therefore, its functionality is available over the Ethernet. SAR ICARUS teams from different countries can be trained simultaneously on a shared virtual stage. In this paper we will show the multi-robot 3D mapping component (aerial vehicle and ground vehicles). We will demonstrate that these 3D maps can be used for Training purpose. Finally we demonstrate current approach for ICARUS Urban SAR (USAR) and Marine SAR (MSAR) operation training. © 2014 IEEE.