Human, Organisational and Societal Factors in Robotic Rail Infrastructure Maintenance

Robotics are set to play a significant role in the maintenance of rail infrastructure. However, the introduction of robotics in this environment requires new ways of working for individuals, teams and organisations and needs to reflect societal attitudes if it is to achieve sustainable goals. The following paper presents a qualitative analysis of interviews with 25 experts from rail and robotics to outline the human and organisational issues of robotics in the rail infrastructure environment. Themes were structured around user, team, organisational and societal issues. While the results point to many of the expected issues of robotics (trust, acceptance, business change), a number of issues were identified that were specific to rail. Examples include the importance of considering the whole maintenance task lifecycle, conceptualizing robotic teamworking within the structures of rail maintenance worksites, the complex upstream (robotics suppliers) and downstream (third-party maintenance contractors) supply chain implications of robotic deployment and the public acceptance of robotics in an environment that often comes into direct contact with passenger and people around the railways. Recommendations are made in the paper for successful, human-centric rail robotics deployment

Introduction of emerging mobility services in rural areas through the use of mobile network data combined with activity‐based travel demand modelling

Abstract Whilst urban areas are thriving in trialling new mobility services (NMS), rural environments, often perceived as areas of low demand for travel, struggle to attract investments for creating more mobility solutions alongside traditional public transport (PT) services, making residents more reliant on private cars. This paper describes how policy interventions for introducing NMS in rural areas should be guided by big data to capture real and accurate travel behaviours, therefore avoiding perceived biases and potentially underestimating demand. In the UK, the provision of transport in rural areas is solely linked to population density and does not consider differences between places and residents’ travel habits. The proposed data‐driven decision‐making process used trip‐chains from mobile network data (MND) to derive recent and accurate travel patterns from residents and provide the right mix of on‐demand mobility services alongside existing fixed scheduled public transport (PT). The manuscript describes the steps carried out to study three rural areas at low, medium and high population density in the UK: a data landscape to select study areas; the development of an activity‐based model, which uses anonymised mobile network data (MND) aggregated at trip‐chains level to derive travel patterns; and the development of an on‐line questionnaire and focus groups with rural communities to co‐designing solutions based on attitudes towards NMS. Results demonstrated that a data‐driven decision making process to introduce NMS is a viable solution for updating demand for travel in rural areas, offering a broad understanding of mobility needs and the relationship of interdependency with nearby areas, therefore allowing policy makers to create users‐centric transport solutions. The study concludes by drawing recommendations for NMS for passengers and goods for the NMS proposed for a rural areas [Demand Responsive Transport (DRT), Micro‐mobility and delivery drones]

The effect of question expectedness and experience on lying about intentions

In recent years researchers have started to focus on lying about intentions (Granhag, 2010). In the present experiment participants were interviewed about their forthcoming trip. We tested the hypothesis that liars (N = 43) compared to truth tellers (N = 43) would give fewer details to unexpected questions about planning, transportation and the core event, but an equal amount or more detail to expected questions about the purpose of the trip. We also tested the hypothesis that participants who had previously experienced the intention (i.e., they had made such a trip before) would give more detail than those who had never experienced the intended action. The unexpected question hypothesis was supported, whereas the previous experience effect only emerged in interactions. The benefit of using different types of questions for lie detection purposes is discusse

Who should I look at?:eye contact during collective interviewing as a cue to deceit

Pairs of liars and pairs of truth tellers were interviewed and the amount of eye contact they made with the interviewer and each other was coded. Given that liars take their credibility less for granted than truth tellers, we expected liars to monitor the interviewer to see whether they were being believed, and to try harder to convince the interviewer that they were telling the truth. It was hypothesised that this monitoring would manifest itself through more eye contact with the interviewer and less eye contact with each other than in the case of truth tellers. A total of 43 pairs of participants took part in the experiment. Truth tellers had lunch in a nearby restaurant. Liars took some money from a purse, and were asked to pretend that instead of taking the money, they had been to a nearby restaurant together for lunch. Pairs of liars looked less at each other and displayed more eye contact with the interviewer than pairs of truth tellers. The implications of these findings are discussed