Residential self-selection (RSS) is the theoretical mechanism that explains that the impact of the built environment on travel behaviour is weaker than bivariate correlations suggest, because mode attitudes influence both the built environment and travel behaviour and therefore at least partially account for the bivariate relationship. Recently, the concept of travel-related reasons for residential choice has been introduced, which reflects the actual extent to which the travel-related characteristics of the built environment were considered during the relocation decision. In this paper, we hypothesize that travel-related location reasons are stronger predictors of the built environment choice than generic mode attitudes. This hypothesis is examined by estimating both a cross-sectional and a longitudinal Structural Equation Model using data gathered in the Netherlands. The results suggest that the travel-related location reasons are indeed stronger predictors for built environment location than travel mode attitudes and that the directions of causality between attitudes, travel-related location reasons, the built environment, and travel behaviour often run in both directions. Substantively, our findings indicate that public transport use is most strongly affected by the built environment (after controlling for both stated reasons and attitudes), while car and bicycle use are hardly affected. From a practical point of view, this suggests that transforming the built environment to be more friendly to public transport may increase the use of public transport, but that, at least in the Netherlands, such a strategy would not work well if the aim were to reduce car use or increase bicycle use.

One of the main aims of introducing automation in transport is to improve safety by reducing or eliminating human errors; it is often argued however that this may induce new types of errors. There is different level of maturity with automation in different transport modes (road, aviation, maritime and rail), however no systematic research has been conducted on the lessons learned in different sectors, so that they can be exploited for the design of safer automated systems. The aim of this paper is to review the impact of key human factors on the safety of automated transport systems, with focus on relevant experiences from different transport sectors. A systematic literature review is carried out on the following topics: the level of trust in automation – in particular the impact of mis-aligned trust, i.e. mistrust vs overreliance, the resulting impact on operator situation awareness (SA), the implications for takeover control from machine to human, and the role of experience and training on using automated transport systems. The results revealed several areas where experiences from the aviation and road domain can be transferable to other sectors. Experiences from maritime and rail transport, although limited, tend to confirm the general patterns. Remarkably, in the road sector where higher levels of automation are only recently introduced, there are clearer and more quantitative approaches to human factors, while other sectors focus only on mental modes. Other sectors could use similar approaches to define their own context-specific metrics. The paper makes a synthesis of key messages on automation safety in different transport sectors, and presents an assessment of their transferability.