Improving the capabilities and use of strategic decision making tools.

Recent research has shown that a substantial proportion of local authorities do not use models for strategy formulation or scheme design and appraisal. Models were perceived to be unable to reflect the range of policy instruments which local authorities now use; and were seen as too complex for local authority staff and stakeholders to use themselves. To overcome these issues the MARS model has been enhanced to provide a transparent and easy to use tool with a flight simulator front-end. This paper describes the model along with improvements to the representation of public transport by inclusion of quality and crowding factors and the incorporation of urban heavy rail

A Systemic Analysis of Impacts of Individual and Shared Automated Mobility in Austria

Rationale: Increasing digitalization and automation is expected to significantly change the transport system, mobility and settlement structures. A decade ago automated, self-driving vehicles were nothing more than an unrealistic (boyhood) dream. But today the concept of highly and fully automated vehicles is rapidly becoming a reality, with a series of real-world trial applications underway. Government plans and industry predictions expect automation to be introduced from the early 2020s onwards. Nevertheless, there is still a high level of uncertainty in which form and to what extent automated vehicles will enter the market. Furthermore, there are ongoing discussions concerning net effects of positive and negative aspects of automation. Background: The authors have been involved in several research projects analyzing potential impacts of automated driving. The EU funded project CityMobil (Towards Advanced Road Transport for the Urban Environment) was one of first to address automated driving on a large scale. As part of this project the System Dynamics based model MARS (Metropolitan Activity Relocation Simulator) was adapted to assess scenarios of automated driving in four European cities. Simulations demonstrated that automated vehicles integrated into public transport have a potential to reduce car kilometers travelled and improve carbon footprint. On the contrary, privately owned automated vehicles lead to an increase in car kilometers travelled and carbon footprint, unless propulsion technology is changed. While the focus of CityMobil was on the urban scale, the nationally funded Austrian project Shared Autonomy (Potential Effects of the Take-up of Automated Vehicles in Rural Areas – own translation) focused on rural areas. The findings of Shared Autonomy show potential contributions of automated cars to improve the environmental situation and social inclusion in rural areas. Finally, the nationally funded Austrian project SAFiP (System Scenarios Automated Driving in Personal Mobility) takes a look at the national territory of Austria. Method: The relationship between vehicle automation, travel demand and environmental effects consists of a multitude of complex cause-effect-chains. The toolbox of System Dynamics offers appropriate methods to tackle such complexities. Causal Loop Diagrams are used to analyze and discuss relevant cause-effect-chains and are used to adapt an existing Stock-Flow-Model of the Austrian land use and transport demand system. The modified Stock-Flow-Model is used for a quantitative impact assessment. Sensitivity analysis in form of Monte-Carlo-Simulations is employed to tackle the high level of uncertainty concerning key factors. Findings, results: The key factors, influencing mode choice and travel demand, are generalized costs of travel time, weighted costs of use and availability. The automation of driving, expressed as the share of highly and fully automated vehicles in the fleet, is influencing all three key factors via different cause-effect-chains and feedback loops. In SAFiP we identified four key impact sources: automated and remote parking, road capacity and travel speed, value of in-vehicle time and widening the range of users. Sensitivity tests for each of the impact sources have been carried out. Widening the range of users has the highest impact on a national level, potentially increasing car kilometers by about 17 percent in 2050. Remote parking increases car kilometers by about 5 percent in total, ranging from about 1 percent in peripheral districts to about 17 percent in Vienna

The integrated dynamic land use and transport model MARS

Cities worldwide face problems like congestion or outward migration of businesses. The involved transport and land use interactions require innovative tools. The dynamic Land Use and Transport Interaction model MARS (Metropolitan Activity Relocation Simulator) is part of a structured decision making process. Cities are seen as self organizing systems. MARS uses Causal Loop Diagrams from Systems Dynamics to explain cause and effect relations. MARS has been benchmarked against other published models. A user friendly interface has been developed to support decision makers. Its usefulness was tested through workshops in Asia. This paper describes the basis, capabilities and uses of MARS

Assessment of energy efficiency and sustainability scenarios in the transport system

Background Energy Policy is one of the main drivers of Transport Policy. A number of strategies to reduce current energy consumption trends in the transport sector have been designed over the last decades. They include fuel taxes, more efficient technologies and changing travel behavior through demand regulation. But energy market has a high degree of uncertainty and the effectiveness of those policy options should be assessed. Methods A scenario based assessment methodology has been developed in the frame of the EU project STEPS. It provides an integrated view of Energy efficiency, environment, social and competitiveness impacts of the different strategies. It has been applied at European level and to five specific Regions. Concluding remarks The results are quite site specific dependent. However they show that regulation measures appear to be more effective than new technology investments. Higher energy prices could produce on their turn a deterioration of competitiveness and a threat for social goals

Optimal and Long-Term Dynamic Transport Policy Design: Seeking Maximum Social Welfare through a Pricing Scheme.

This article presents an alternative approach to the decision-making process in transport strategy design. The study explores the possibility of integrating forecasting, assessment and optimization procedures in support of a decision-making process designed to reach the best achievable scenario through mobility policies. Long-term evaluation, as required by a dynamic system such as a city, is provided by a strategic Land-Use and Transport Interaction (LUTI) model. The social welfare achieved by implementing mobility LUTI model policies is measured through a cost-benefit analysis and maximized through an optimization process throughout the evaluation period. The method is tested by optimizing a pricing policy scheme in Madrid on a cordon toll in a context requiring system efficiency, social equity and environmental quality. The optimized scheme yields an appreciable increase in social surplus through a relatively low rate compared to other similar pricing toll schemes. The results highlight the different considerations regarding mobility impacts on the case study area, as well as the major contributors to social welfare surplus. This leads the authors to reconsider the cost-analysis approach, as defined in the study, as the best option for formulating sustainability measures

Are European cities becoming similar?

The paper discusses city specific development patterns to overcome todays transport problems. The results are based on recent andongoing research activities at TUW-IVV and ITS. At previous CORP-conferences, we presented the basics and the development of aplanning support tool to find optimal policy packages in urban transport and land use (Emberger, 1998), (Pfaffenbichler, Emberger, 2001). The core of this planning support tool is a dynamic land use and transport interaction model. This model, which we refer to as Sketch Planning Model (SPM), is embedded into an appraisal and optimisation framework. The SPM and this framework were developed in the recently finished European Union funded research project PROSPECTS1. Case studies with this planning supporttool were performed within PROSPECTS for the cities Edinburgh, Helsinki, Madrid, Oslo, Stockholm and Vienna. These cities are principally comparable in regards of their status (capitals and major business and education centres), but different in their size, population density, transport system etc. A set of policy instruments like public transport improvements, car traffic restrictions, and infrastructure provision was available to formulate strategies to reduce negative impacts of transport and to increase welfare. The overall objective was a sustainable development of the city. Although the instruments and the goals are similar in all investigatedcites, different solutions were adequate. The solutions vary in regard of spatial implementation, implementation time and level of implementation. The paper will highlight some reasons for the different development paths of the cities. As well the comparison of the do nothing scenario as the comparison of the most feasible policy strategies shows that European cities are different, need different solutions for their problems and will stay different in the future