The study aims to understand the city centre living characteristics from a sustainable travel behaviour perspective. Three datasets have been utilised; the UK Trip Rate and Information Computer System (TRICS), the Scottish Household Survey and an original household travel survey which has been conducted in Manchester city centre. An array of univariate and multivariate statistical techniques have been utilised to conduct the required travel analysis and modelling. Using Trics 2012a, exploratory analysis has shown a significant variation in the urban form characteristics between residential neighbourhoods located in central locations and those located in other areas. Households in the central locations generally travel less than others; in particular, town centre households walk more and drive less than others in out-of centre areas. In contrast, the inferential analysis showed evidence of a mediation effect whereby neighbourhood features such as the ratio of flats, parking density and transit provisions explain some of the differences in trip frequency. The mediation analysis also revealed that built environment features only partially account for these differences. The Scottish Household Survey and the Manchester city centre survey datasets have been utilised in order to investigate the potential impacts of several socio-spatial and attitudinal attributes on the city centre residents’ personal mobility. Whereas the review process disclosed the notable increase in the residents of the UK city centre and a revival of its housing sector over the past decade, the descriptive analysis revealed some distinct characteristics of those residents such as they are typically young adults, modern and well-qualified and living in single person households or as couples. Walking is their common mode for commuting, shopping and leisure. In Manchester city centre, 42% of the residents’ journeys were found to be within the city centre catchment area. In contrast, the travel behaviour models indicated the potential impacts of socio-spatial attributes such as car ownership, income and parking on mobility measures such as car ownership, mode choice and vehicular mileage. Finally, some attitudinal factors were found to be influential even after controlling for the socio-spatial effects.