Mixed Reality (MR) is a hybrid technology that blends digital elements with the physical world, enabling interaction across both worlds. The integration of typical video games into MR headsets can be challenging due to device limitations, user comfort, limited hardware capability, and interaction modalities. This research investigates two types of MR games, with a focus on spatial aspects, player experience, and players’ brain activity analysis. We analyzed design considerations and interaction patterns suitable for MR environments. For our study, we developed two games: a high-intensity action game and a low-intensity puzzle-solving game, and deployed them on Microsoft HoloLens 2. We conducted user studies with 14 participants using objective and subjective data collection methods. Objective data was gathered through an electroencephalogram (EEG) device, measuring players’ brain activity and emotional states. Subjective data was collected from post-test surveys that evaluated user experience, cognitive load, and emotional responses.

The low-cost electroencephalogram (EEG) devices are widely used by researchers in human-computer interaction, video games, and software systems to evaluate the impact of interaction design on user emotions. However, the performance metrics of emotion states provided by a low-cost EEG device suffer several reliability and accuracy issues, which can mislead the design decisions of the developers. In this research, we combined the EEG device with three virtual reality games to investigate the reliability of performance metrics extracted from the EEG data. We conducted the experiment with 14 players using virtual reality games with ranging levels of in-game actions. Our analysis shows that there is a significant difference between performance metrics provided by the EEG device and the actual players' experience. Finally, we used ad-hoc linear models to estimate the level of players' emotion states directly from the raw EEG. We also show the different brain activity maps for individual emotions, which reveal the commonly known relation between brain activity and specific emotions.

Player engagement and task effectiveness are crucial factors in human computation games. However, collecting data and making design changes towards these goals can be time-consuming. In this work, we incorporate rapid crowdsourced playtesting via the ARAPID (As Rapid As Possible Iterative Design) system to iterate on the design of a human computation platformer game. For each level in the game, the player’s goal is to collect items relevant to a given scenario while avoiding irrelevant items. We extended the visualization modules in the existing ARAPID system to include a multi-level data visualization and item collection task effectiveness plot. A designer from the project team used the system to iterate on the game’s level design, with the goal of increasing relevant and decreasing irrelevant items collected by players. A large-scale test with the game versions created during the iterative analysis found that the designer was able to use ARAPID to improve the specified goal parameters.

Pervasive games are an emerging genre combining reality and computing. This paper presents a suite of simple pervasive serious games we have developed to explore the concept of “reality-enhanced gaming”, a pattern to tie game play mechanics to the outcomes/measurements of real-world activities. The prototype games were realized in the context of TEAM, an industrial research project aimed at developing apps for flexible and collaborative mobility. The proposed games are examples of different UIs we considered useful to meet various significant scenarios, goals and user typologies, especially for improving car driving styles. Given the variety of information sources, contexts of use, and target users, we abstracted a gameoriented framework (namely REAL, Reality-Enhanced AppLied games), in order to support re-use and scalability. Through a set of RESTful APIs, the REAL framework separates sensor data from actual game implementations, so as to provide different experiences to users, according to their specific needs and preferences. This concept – which allows serious game developers to focus on their specific game logic while seamlessly exploiting a variety of field sensors - is general and may be applied to a variety of domains. We validated REAL developing and field testing five typologies of serious games. Subjective evaluation results show a good level of satisfaction and perceived usefulness. More tests are needed, especially in terms of different application contexts, impact on developers, number and variety of users, and exposure time. However, outcomes confirm the significant potential of reality-enhanced game design and the importance of tools for supporting their development.

The tomorrow's elastic adaptive mobility industrial research project developed eleven collaborative mobility apps addressing various traffic issues and scenarios. The apps, involving different aspects and degrees of collaboration (e.g., direct user participation, shared objectives, coordination, etc.), aim at increasing the driver/traveler awareness and support a better behavior. This paper describes the apps and the underlying system architecture shared by the participating car manufacturers. Then, it provides a user acceptance analysis grouping the apps according to the three main types of users and stakeholders: drivers, travelers, and administrators/operators. Data, collected in five European countries, shows that acceptance and expected impact are positive. The actual road-test experience did not diminish the high expectations raised by an initial presentation on paper, showing a good maturity of the prototypes. The Administrator app cluster shows a slightly better assessment, highlighting the importance of considering collaborative mobility as a system, including road, infrastructure, and traffic management.

Present public transport services still suffer from issues such as time deviations from the static timetable, overcrowded buses, increased on board time, and long wait at bus stops. This work studies the experimental implementation of an on-demand public bus transportation service in Trikala, a medium-sized Greek city. With a view to optimize the service from both the operator's and the citizens' point of view, this paper presents an insertion heuristic solving the static multivehicle dial-a-ride problem with time windows and a fixed fleet of vehicles. Since viability of such a service depends on its ability of involving a significant number of users and getting reliable information, we tested a gamification layer, aimed at motivating public transport users to participate and behave correctly with the system. We present and discuss a novel pervasive computing architecture and various types of serious games designed to achieve these goals. We finally report early usability test results and some simulation-based indications on the design of city-scale deployable serious games to enhance public transport-based mobility.

The transportation sector is expanding its trends in accessibility, connectivity, and mobility for making the road travel as safe and convenient. Now with Services like car sharing, car pooling and rides there are new effective ways to reach the desired destination. But due to comfort reasons most of the car owners will use their car to navigate from point A to B, without caring about the pollution they produce. In this paper we describe a game based approach for motivating people to drive in a safe and environment-friendly way. The approach of this paper will allow people to measure their driving behavior within a game. The points earned in the game can not only be used for the comparison with peers but also to obtain monetary benefits in different stores.

We present a technique for dangerous curve monitoring relying on the innovative concept of Safe Driving Map (SDM), a geo-referenced database with data about safe vehicle behavior in the monitored area, also considering different weather conditions. A vehicle's data are compared with the SDM reference and the driver is warned in case of danger. A road-side unit can also be set-up, collecting information from vehicles, thus signaling possible dangers (e.g., a vehicle stopped in the curve). A preliminary evaluation was performed by developing a scenario using the PHABMACS (Physics Aware Behavior Modelling Advanced Car Simulator) driving simulator.