A review of gamified approaches to encouraging eco-driving.

Eco-driving is a style of driving that minimizes energy consumption, while gamification refers to the use of game techniques to motivate user engagement in non-game contexts. This paper comprises a literature review assessing applying gamification to encourage eco-driving. The Web of Science Core Collection and EBSCO Host platforms were searched in February 2022. Qualifying sources included peer review journal articles, conference proceedings papers, academic book chapters and dissertation reports. The final sample comprised 39 unique publications, of which 34 described gamification adjunct systems used during driving. Most were designed as smartphone apps, but some ran on bespoke in-car feedback displays. Alternatively, using game-based learning, 5 studies described videogames designed to encourage eco-driving. Popular gamification elements were: an eco-driving score; self-comparisons or comparisons with others via leader boards; rewards; challenges, missions or levels; and emotive feedback (e.g., emojis). One system aimed to discourage driving at busy times. While 13 studies assessed the efficacy of the various systems, these were generally of poor quality. This developing literature contains many good ideas for applying gamification to promote eco-driving. However, evidence for efficacy is largely absent and researchers are encouraged to continue to evaluate a wide range of gamification approaches to promote eco-driving

The design and implementation of serious games for driving and mobility

The automotive and transportation sectors are showing consistent improvements in trends and standards concerning the safe and convenient travel of the road users. In this growing community of road users, the driver performance is a notable factor as many on-road mishaps emerge out of poor driver performance. In this research work, a case-study and experimental analysis were conducted to improve driver performance through the deployment of serious games. The primary motive of this work is to stimulate the on-road user performance through immediate feedback, driver coaching, and real-time gamification methods. The games exploit the cloud-based architecture to retrieve the driver performance scores based on real-time evaluation of vehicle signals and display the outcomes on game scene by reflecting the game parameters based on real-world user performance (in the context of driving and mobility). The deployment of games in cars is the topic of interest in current state-of-the-art, as there are more factors associated with it, such as safety, usability, and willingness of the users. These aspects were taken into careful consideration while designing the paradigm of gamification model. The user feedback for the real-time games was extracted through pilot tests and field tests in Genova. The gamification and driver coaching aspects were tested on various occasions (plug-in and field tests conducted at 5 European test sites), and the inputs from these field tests enabled to tune the parameters concerning the evaluation and gamification models. The improvement of user behavior was performed through a virtuous cycle with the integration of virtual sensors to the serious gaming framework. As the culmination, the usability tests for the real-time games were conducted with 18 test users to understand the user acceptance criteria and the parameters (ease of use and safety) that would contribute to the deployment of games. Other salient factors such as the impact of games, large-scale deployment, collaborative gaming and exploitation of gaming framework for 3rd party applications were also investigated in this research activity. The analysis of the usability tests states that the user acceptance of the implemented games is good. The report from usability study has addressed the user preferences in games such as duration, strategy and gameplay mechanism; these factors contribute a foundation for future research in implementing the games for mobility

Playing it safe : A literature review and research agenda on motivational technologies in transportation safety

While motivation affects safety-related decision-making and human reliability, technologies to promote it are scarcely used. We have only recently witnessed how motivational technologies, including serious games, gamification, and persuasive technologies have emerged on the palette of methods for enhancing transportation safety. However, the research on these technologies for transportation safety is fragmented, preventing future studies and practical efforts. This paper describes the state-of-the-art through a systematic review to address this issue. Analyzing 62 studies, we perceive that motivational technologies focus on reducing the accident likelihood and mitigating their consequences. While these technologies can induce positive psychological change and improve learning, the evidence of behavioral change is mainly limited to simulation settings, lacking examination of the long-term benefits and potential adverse effects. Our results highlight the importance of aligning motivational design with the cognitive demand of the transportation task and the means for improving safety. Future research should explore how motivational technologies can enhance safety from the system design perspective, cover a broader scope of transportation modes, compare their effects to conventional approaches while considering social aspects in their design and evaluation. Beside providing an overview of the area and future directions, this paper also introduces design recommendations to guide practitioners.publishedVersionPeer reviewe

Comparative analysis of Kinect-based and Oculus-based gaze region estimation methods in a driving simulator

Producción CientíficaDriver’s gaze information can be crucial in driving research because of its relation to driver attention. Particularly, the inclusion of gaze data in driving simulators broadens the scope of research studies as they can relate drivers’ gaze patterns to their features and performance. In this paper, we present two gaze region estimation modules integrated in a driving simulator. One uses the 3D Kinect device and another uses the virtual reality Oculus Rift device. The modules are able to detect the region, out of seven in which the driving scene was divided, where a driver is gazing at in every route processed frame. Four methods were implemented and compared for gaze estimation, which learn the relation between gaze displacement and head movement. Two are simpler and based on points that try to capture this relation and two are based on classifiers such as MLP and SVM. Experiments were carried out with 12 users that drove on the same scenario twice, each one with a different visualization display, first with a big screen and later with Oculus Rift. On the whole, Oculus Rift outperformed Kinect as the best hardware for gaze estimation. The Oculus-based gaze region estimation method with the highest performance achieved an accuracy of 97.94%. The information provided by the Oculus Rift module enriches the driving simulator data and makes it possible a multimodal driving performance analysis apart from the immersion and realism obtained with the virtual reality experience provided by Oculus.Dirección General de Tráfico y Ministerio del Interior - (Proyecto SPIP2015-01801

How to keep drivers engaged while supervising driving automation? A literature survey and categorization of six solution areas

This work aimed to organise recommendations for keeping people engaged during human supervision of driving automation, encouraging a safe and acceptable introduction of automated driving systems. First, heuristic knowledge of human factors, ergonomics, and psychological theory was used to propose solution areas to human supervisory control problems of sustained attention. Driving and non-driving research examples were drawn to substantiate the solution areas. Automotive manufacturers might (1) avoid this supervisory role altogether, (2) reduce it in objective ways or (3) alter its subjective experiences, (4) utilize conditioning learning principles such as with gamification and/or selection/training techniques, (5) support internal driver cognitive processes and mental models and/or (6) leverage externally situated information regarding relations between the driver, the driving task, and the driving environment. Second, a cross-domain literature survey of influential human-automation interaction research was conducted for how to keep engagement/attention in supervisory control. The solution areas (via numeric theme codes) were found to be reliably applied from independent rater categorisations of research recommendations. Areas (5) and (6) were addressed by around 70% or more of the studies, areas (2) and (4) in around 50% of the studies, and areas (3) and (1) in less than around 20% and 5%, respectively. The present contribution offers a guiding organisational framework towards improving human attention while supervising driving automation.submittedVersio

Eco-friendly Naturalistic Vehicular Sensing and Driving Behaviour Profiling

PhD ThesisInternet of Things (IoT) technologies are spurring of serious games that support training directly in the field. This PhD implements field user performance evaluators usable in reality-enhanced serious games (RESGs) for promoting fuel-efficient driving. This work proposes two modules – that have been implemented by processing information related to fuel-efficient driving – to be employed as real-time virtual sensors in RESGS. The first module estimates and assesses instantly fuel consumption, where I compared the performance of three configured machine learning algorithms, support vector regression, random forest and artificial neural networks. The experiments show that the algorithms have similar performance and random forest slightly outperforms the others. The second module provides instant recommendations using fuzzy logic when inefficient driving patterns are detected. For the game design, I resorted to the on-board diagnostics II standard interface to diagnostic circulating information on vehicular buses for a wide diffusion of a game, avoiding sticking to manufacturer proprietary solutions. The approach has been implemented and tested with data from the enviroCar server site. The data is not calibrated for a specific car model and is recorded in different driving environments, which made the work challenging and robust for real-world conditions. The proposed approach to virtual sensor design is general and thus applicable to various application domains other than fuel-efficient driving. An important word of caution concerns users’ privacy, as the modules rely on sensitive data, and provide information that by no means should be misused

Gamification of the crowdsourced delivery service

PiggyBaggy is ride-sharing service. The system applies crowdsourcing model, where participants accomplishing parcel transportation are rewarded with the small amount of money. Through this system, users are able to request different type of delivery and transport it to the necessary destination. Despite the prevalence of crowdsourcing, the number of engaged users is not increasing. The possible drawbacks of PiggyBaggy can be that it is not adapted into delivery environment where delivers can be from walkers to drivers. Moreover, it demands to do additional research to find out other motivators for delivery except the money. One of the suggestion to increase the number of new users and keep current users for a long period is gamified service. The aim of the thesis is reveal the effect of gamification in crowdsourcing model to increase intrinsic motivation to participate in the service voluntarily. The study includes conduction of test sessions, where participants use gamified and non-gamified prototypes and estimate their feeling in survey. Th experiment applies game mechanics on the base of Octalysis framework. Gamification of the delivery service: ● Concept of being hero in the city implemented in the design of user interface ● Each delivery is a mission ● Completed mission is awarded by points, power, and health ● Rating system between other participants based on award

Gamification of telematics data to enhance operators’ behaviour for improvement of machine productivity in loading cycles

Construction industry is suffering from low productivity rate in various projects such as excavation. Although this issue is discussed in literature and several approaches are proposed to address it, productivity rate is still low in construction industry compared to other domains like manufacturing. Three core components directly affect the overall productivity in construction sector, i.e. labour productivity, raw material productivity, and machine or equipment productivity. With a focus on construction machinery, three factors influence productivity at excavation sites; i.e. 1) machine-based productivity and its configuration, 2) site layout and environmental conditions, and 3) operators’ behaviour. Operators’ competence and motivation represent two key parameters that affect their behaviour. On one side, gamification has attracted a growing area of interest both in literature and practice, seeking to place a layer of entertainment and pleasure to the top of serious activities (with a focus on improving the applicant’s motivation and behaviour). On the other side, telematics systems are utilized to collect operational data of the machine, and calculate its productivity rate. Telematics data are presented to operators (via a built-in screen available in the cabin of the machine) to provide real-time feedback about machine performance. In addition, these data can support machine owners to perceive operators’ behaviour on a real-time basis. To conclude, telematics systems are providing real-time data which can be a great input into gamification. A guideline is proposed in this dissertation that helps gamification designers to develop more transparent gamification models. This guideline is utilized to introduce a gamification model that gamifies telematics data with a focus on enhancing operators’ behaviour (machine productivity) in loading and transferring activities. The model was implemented at two sites(one recycling and one mining site) and could encourage operators (who were operating wheel-loaders and dump-trucks) to prevent redundant activities like texting, phoning, and even eating while operating the machine. Subsequently, it enhanced overall machine productivity up to 37% during the site observation. To summarize, a gamified platform in which different operators from different organizations can share their achievements, or can get scored and ranked in a leader-board will potentially lead to a more proper operators’ behaviour at work and subsequently can improve overall productivity rate at construction sites

Gamification of telematics data to enhance operators’ behaviour for improvement of machine productivity in loading cycles

Construction industry is suffering from low productivity rate in various projects such as excavation. Although this issue is discussed in literature and several approaches are proposed to address it, productivity rate is still low in construction industry compared to other domains like manufacturing. A gamified platform in which different operators from different organizations can share their achievements, or can get scored and ranked in a leader-board will potentially address this issue