International conference on software engineering and knowledge engineering: Session chair

The Thirtieth International Conference on Software Engineering and Knowledge Engineering (SEKE 2018) will be held at the Hotel Pullman, San Francisco Bay, USA, from July 1 to July 3, 2018. SEKE2018 will also be dedicated in memory of Professor Lofti Zadeh, a great scholar, pioneer and leader in fuzzy sets theory and soft computing. The conference aims at bringing together experts in software engineering and knowledge engineering to discuss on relevant results in either software engineering or knowledge engineering or both. Special emphasis will be put on the transference of methods between both domains. The theme this year is soft computing in software engineering & knowledge engineering. Submission of papers and demos are both welcome

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

Driving examiners’ views on data-driven assessment of test candidates:An interview study

Vehicles are increasingly equipped with sensors that capture the state of the driver, the vehicle, and the environment. These developments are relevant to formal driver testing, but little is known about the extent to which driving examiners would support the use of sensor data in their job. This semi-structured interview study examined the opinions of 37 driving examiners about datadriven assessment of test candidates. The results showed that the examiners were supportive of using data to explain their pass/fail verdict to the candidate. According to the examiners, data in an easily accessible form such as graphs of eye movements, headway, speed, or braking behaviour, and colour-coded scores, supplemented with camera images, would allow them to eliminate doubt or help them convince disagreeing test-takers. The examiners were sceptical about higher levels of decision support, noting that forming an overall picture of the candidate’s abilities requires integrating multiple context-dependent sources of information. The interviews yielded other possible applications of data collection and sharing, such as selecting optimal routes, improving standardization, and training and pre-selecting candidates before they are allowed to take the driving test. Finally, the interviews focused on an increasingly viable form of data collection: simulator-based driver testing. This yielded a divided picture, with about half of the examiners being positive and half negative about using simulators in driver testing. In conclusion, this study has provided important insights regarding the use of data as an explanation aid for examiners. Future research should consider the views of test candidates and experimentally evaluate different forms of data-driven support in the driving test

Using telematics digital traces to predict individual differences in ecological driving

Engineering innovations in transport are insufficient alone to combat its effects on the climate crisis. ‘Driving style’ – the way a driver prefers to or habitually drives their vehicle – significantly impacts fuel consumption and exhaust emissions. However, changes from an ‘aggressive’ to a more refined style – ‘eco-driving’ – offers overlooked opportunities for emissions savings. In this thesis, I explore how individual differences including personality, wellbeing and aspects of demography are related to objective eco-driving behaviours in a sample of monitored drivers. By adopting an interdisciplinary approach, this thesis incorporates methods from psychology and computer science to consider both theoretical and methodological implications. Substantially, findings across the research point to an emerging and central role of emotion dysfunction as a key influence in drivers’ inefficient operational driving behaviours. Moreover, a clear intention – behaviour gap is identified between drivers’ self-report intentions to eco-drive and their objective eco-driving behaviours. Recommendations illustrate how these insights can be translated into digital behaviour change interventions (DBCI) to encourage sustained changes in drivers’ ecological driving efficiency