The Cambridge handbook of multimedia learning

Highly automated vehicles are expected to increase the safety and quality of road transportation, but because of significant changes in the driver’s role, they introduce new human factors challenges and require learning specific skills. Training has been proposed as a potential tactic to alleviate these challenges and improve driver interaction with automated cars. This study evaluated the effects of Simulator Training and Video Training on procedural and higher-order cognitive skills required for Conditionally Automated Driving (CAD), and users’ attitudes as well. Fifty-four people participated in the experiment, 18 in Simulator Training, 18 in Video Training, and 18 in Control groups. Takeover Time (TOT), speed, speed variance, Standard Deviation of Lateral Position (SDLP), Takeover Decision Accuracy (TODA), trust, and acceptance data were collected before and after training sessions. The results showed that both training methods improved TOT, speed variance, and SDLP. Moreover, the participants in Simulator Training outperformed in deciding whether takeover was necessary or not. The results also indicated that self-reported trust was less erratic in Post-Training Driving Assessment in both Simulator and Video Training. These findings imply that training, especially where interactive learning is provided, helped the participants develop a more developed mental model of CAD and better-calibrated trust. Training programs, however, did not create meaningful changes in the number of crashes, speed, nor automation acceptability. Further research is needed to investigate learning transferability to highly automated driving on the real road.

How does training effect users’ attitudes and skills needed for highly automated driving?

Promoting eco-driving with battery electric vehicles (BEVs) can help drivers reduce their average energy consumption and enhance the driving range of a BEV. The present study examined the influence of three persuasive strategies (feedback regarding energy consumption, gamification, and financial rewards) compared to a baseline condition (no feedback or intervention) on the average BEV energy consumption under natural driving conditions. The influence of persuasive strategies on participants’ attitudes towards eco-driving, as well as self-reported eco-driving knowledge were investigated. The persuasive strategies were used over 22 months. 108 participants took part in the field study in Germany and used BEVs for their daily business travel. Energy consumption data was gathered via data loggers. Participants had unlimited access to their post-drive eco-driving feedback via a web application. The use of game design (i.e. gamification) elements and financial rewards significantly reduced energy consumption as compared to baseline or mere feedback regarding energy consumption. Participants showed a habituation to eco-driving after removal of the strategies. Driving experience with BEV and gamification predicted eco-driving knowledge. We found first evidence from a highly naturalistic field trial by providing driving data from a car sharing case study, improving on previous studies that mostly used laboratory settings or instructed driving. We expanded upon persuasion research, supporting the idea that gamification can be strongly relevant for energy saving behaviour.

Can electric vehicle drivers be persuaded to eco-drive? A field study of feedback, gamification and financial rewards in Germany

An over-proportionally large number of car crashes is caused by novice drivers. In a field experiment, we investigated whether and how car drivers who had recently obtained their driving license reacted to app-based feedback on their safety-relevant driving behavior (speeding, phone usage, cornering, acceleration and braking). Participants went through a pre-measurement phase during which they did not receive app-based feedback but driving behavior was recorded, a treatment phase during which they received app-based feedback, and a post-measurement phase during which they did not receive app-based feedback but driving behavior was recorded. Before the start of the treatment phase, we randomly assigned participants to two possible treatment groups. In addition to receiving app-based feedback, the participants of one group received monetary incentives to improve their safety-relevant driving behavior, while the participants of the other group did not. At the beginning and at the end of experiment, each participant had to fill out a questionnaire to elicit socio-economic and attitudinal information.
We conducted regression analyses to identify socio-economic, attitudinal, and driving-behavior-related variables that explain safety-relevant driving behavior during the pre-measurement phase and the self-chosen intensity of app usage during the treatment phase. For the main objective of our study, we applied regression analyses to identify those variables that explain the potential effect of providing app-based feedback during the treatment phase on safety-relevant driving behavior. Last, we applied statistical tests of differences to identify self-selection and attrition biases in our field experiment.
For a sample of 130 novice Austrian drivers, we found moderate improvements in safety-relevant driving skills due to app-based feedback. The improvements were more pronounced under the treatment with monetary incentives, and for participants choosing higher feedback intensities. Moreover, drivers who drove relatively safer before receiving app-based feedback used the app more intensely and, ceteris paribus, higher app use intensity led to improvements in safety-related driving skills. Last, we provide empirical evidence for both self-selection and attrition biases.

App-based feedback on safety to novice drivers: learning and monetary incentives

Battery electric vehicles (BEVs) are a promising form of future mobility. However, current BEV drivers have to interact with quite small ranges because of the relatively small battery sizes and relatively long charging periods. One important coping resource to overcome this barrier is to use the available driving range as efficiently as possible by successfully using several eco-driving strategies. Eco-driving can reduce energy consumption and enhance a BEV’s driving range. Several eco-driving strategies can be adopted from internal combustion engine vehicles, but specific strategies for driving BEVs, such as efficient use of the regenerative braking need to be learnt. We examine the influence of pre-drive theoretical eco-driving training (i.e., consumption related information, eco-driving tips) versus practical BEV driving experience on self-reported eco-driving behaviour, knowledge, knowledge certainty rating and eco-driving acceptance. Experienced BEV drivers (N = 20), untrained non-BEV (N = 23), and a third group consisting of non-BEV drivers who received pre-drive theoretical eco-driving training (N = 20) undertook a BEV test drive in a critical range situation. First time experience of a critical range situation and the pre-drive theoretical eco-driving training both had positive effects on non-BEV drivers’ self-reported eco-driving knowledge, knowledge certainty rating and acceptance. Compared to untrained non-BEV drivers, both experienced BEV drivers and trained non-BEV drivers reported enhanced eco-driving behaviour in the critical range situation.

How driving experience and consumption related information influences eco-driving with battery electric vehicles – Results from a field study

The present paper deals with how to design and test an eco-driving training tool in the form of a digital educational game, including a specific guidance system interface to each eco-driving rules. We tested whether learners could reproduce the eco-driving behaviour and implement the rules once they were autonomous. We also aimed to validate the method as a relevant eco-driving teaching tool that does not distract drivers or affect safety behaviour. We examined the contribution of the guidance system to teach procedural skills compared with traditional teaching methods such as video instruction. Results reveal that both methods lead to reduced CO2 emissions, but that the reduction is greater with the interactive guidance system. Further analysis and an eye-movement study revealed no increase in driving time or effect on safety.

https://hal.archives-ouvertes.fr/hal-01779632/document

Learning eco-driving behaviour in a driving simulator: Contribution of instructional videos and interactive guidance system

Serious games present a promising approach to training and learning The player is engaged in a virtual environment for a purpose beyond pure entertainment, all while having fun In this paper, we investigate the effects of the use of serious game in eco-driving training An approach has been developed in order to improve players’ practical skills in term of eco driving This approach is based on the development of driving simulation based on serious game, integrating a multisensorial guidance system with metaphors including visual messages (information on fuel consumption, ideal speed area, gearbox management…) and sounds (spatialized sounds, voice messages…) The results demonstrate that the serious game influence positively the behavior of inexperienced drivers in ecological driving, leading to a significant reduction (up to 10%) of their CO2 emission This work brings also some guidelines for the design process The experiences lead to a determination of the best eco-driving rules allowing a significant reduction of CO2 emission

/pdf/the-effects-of-the-use-of-serious-game-in-eco-driving-2alz7wthg4.pdf

The Effects of the Use of Serious Game in Eco-Driving Training

Dans le cadre le cadre du projet GeDriver, cette etude a teste experimentalement l’efficacite de guidages attentionnels externes, associes a une lecon multimedia prealable, sur l’apprentissage de regles d’eco-conduite. L’apprentissage des regles etait effectue sur un simulateur de conduite de voiture eco² dans lequel a ete integre un serious game, avec des parcours realistes. Trois types de guidage, visuels, auditifs et haptique ont ete concus. Trois groupes de participants avec ou sans guidage et lecon ont conduit sur 4 parcours (i) initial (pre-test), (ii) entrainement aux regle 1, (iii) entrainement aux regles 2, (iv) final (post-test). Le mouvement des yeux des participants etait enregistre (systeme Face-Lab synchronise aux actions de conduite). Des scores d’eco-conduite, comme la quantite de CO² emise, etaient calcules. Les principaux resultats ont montre l’efficacite de ce court apprentissage pour l’acquisition de regles d’eco-conduite. Apres deux sessions d’entrainement de 8 et 10 minutes, les emissions de CO² ont diminue de plus de 10% pour le groupe avec lecon et guidage externes.

https://hal.archives-ouvertes.fr/hal-01200457/document

Fabrice Cauchard

Papers

Learning eco-driving behaviour in a driving simulator: Contribution of instructional videos and interactive guidance system

The Effects of the Use of Serious Game in Eco-Driving Training

Apprendre le règles d'éco-conduite sur simulateur de voiture: Effet de guidages attentionnels, visuel et auditifs