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Abstract: Climate change is a global problem and across the world the transport sector is finding it difficult to break projected increases in carbon dioxide (CO2) emissions; there are very few contexts where deep reductions in transport CO2 emissions are being made. A number of research studies are now examining the potential for future lower CO2 emissions in the transport sector. This paper develops this work to consider some of the wider sustainability impacts (economic, social and local environmental) as well as the lower CO2 transport impacts of different policy trajectories. Hence the central argument made is for an integrated approach to transport policy making over the longer term – incorporating scenario analysis and multi-criteria assessment (MCA) – to help assess likely progress against a range of objectives. The analysis is based on work carried out in Oxfordshire, UK. Different packages of measures are selected and two scenarios developed which satisfy lower CO2 aspirations, one of which also provides wider positive sustainability impacts. A simulation model has been produced to help explore the strategic policy choices and tensions evident for decision-makers involved in local transport planning. The paper argues for a ‘strategic conversation’ () at the sub-regional and city level, based upon future scenario analysis and MCA, discussing the priorities for intervention. Such an approach will help us examine the scale of change and trade-offs required in moving towards sustainable transport futures. [Copyright &y& Elsevier]

Abstract: This paper develops a new agent-based simulation model to improve discrete choice analysis as well as to analyse the effects of a road user charging scheme for the Upper Derwent Valley in the Peak District National Park. The advantages of discrete choice analysis are well known. However, results with these conventional methods can be biased if interaction effects are significant. The combined approach of the Minority Game, in which agents try to choose the option of the minority side, and discrete choice analysis is appropriate to deal with the problem. The main data was collected by stated preference survey. The agent-based model has four sub-modules: (1) multinomial mixed logit model for mode choice, (2) binary logit model for parking location choice, (3) Markov queue model for parking network, and (4) the Minority Game for parking congestion and learning. The results show that the road user charging scheme reduces car demand in the Upper Derwent Valley. The model also shows that an exemption will increase the utility of elderly visitors. In conclusion, the simulation model demonstrated that oversimplification in conventional discrete choice analysis gave significant biases when real world problems were analysed. [Copyright &y& Elsevier]