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Front Cover -- Autonomous Vehicles and Future Mobility -- Copyright -- Contents -- Contributors -- Introduction -- 1: Autonomous vehicles and future mobility solutions -- 1 Introduction -- 2 Background -- 2.1 Socio-economic trends -- 2.2 Vehicle technological innovations -- 3 Connected and automated vehicles deployment -- 3.1 Evolutionary and revolutionary paths -- 4 Future mobility scenarios -- 4.1 Mobility as a service -- 5 Conclusions and perspectives -- References -- 2: Where will self-driving vehicles take us? Scenarios for the development of automated vehicles with Sweden as a case study -- 1 Introduction -- 1.1 Background -- 1.2 Definitions -- 1.3 Contribution -- 2 Related work -- 2.1 Simulation studies -- 2.2 Future scenarios for SDVs -- 3 Method -- 3.1 The scenario planning method -- 3.2 The scenario development process -- 3.3 Consequence analysis -- 4 Results -- 4.1 The certain development: Where Sweden is going -- 4.2 Strategic uncertainties -- 4.3 The scenarios -- 4.3.1 Same, same, but different -- 4.3.2 Sharing is the new black -- 4.3.3 Follow the path -- 4.3.4 What you need is what you get -- 4.4 The development of SDVs -- 5 Conclusions and future work -- 6 Notes -- Acknowledgments -- References -- 3: Traffic flow with autonomous vehicles in real-life traffic situations -- 1 Introduction -- 1.1 Previous studies -- 1.2 Scope of study -- 2 Method -- 3 Results -- 3.1 The dataset -- 3.2 Headway settings influence saturation flow rates -- 4 Discussion -- 5 Conclusion -- References -- 4: Demand-oriented mobility solutions for rural areas using autonomous vehicles -- 1 Introduction -- 2 Background -- 2.1 Definition and characteristics of rural areas in Germany -- 2.2 Autonomous driving -- 2.3 Trends on transport demand and supply -- 3 Model scope and structure -- 4 Data utilized.

Empirical evidence supports the hypothesis that greater accessibility to opportunities can have a positive impact on real estate values. However, this capitalisation of the benefits of accessibility could vary between different study areas. This research estimates hedonic and spatial hedonic models in two urban areas to compare if differences can be found in the impact accessibility using public transport has on residential property values. The two study areas chosen for comparison are a medium sized city without any major mobility problems (Santander, Spain) and a very large city with major congestion problems (Rome, Italy). The estimated hedonic models have considered the possible presence of spatial effects, a common occurrence with real estate data which may generate dependency in the residuals of hedonic models. Accessibility has been measured using two types of indicators: relative and gravity based. The results confirm that accessibility was a positive factor on property prices in both cities, although in Santander this was only true using the relative indicator to the city centre. These results are relevant for supporting the introduction of value capture policies which provide finance for new projects to extend and encourage greater use of public transport. ; This research was made possible through the projects PARK-INFO (TRA2013-48116-R) and REALTIMEQUALITY (TRA2015-69903-R) financed by the Government of Spain.