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Mobility Scenarios for the Year 2030: Implications for Individual Electric Mobility
Abstract
As other mobility innovations individual electric mobility will presumably have a significant market share only in decades from now. Scenario planning technique provides a framework for exploring the mobility market of the future with a long term perspective. Against this background the chapter at hand has a twofold objective: (a) It promotes scenario planning as an alternative approach to explore the distant future of mobility to establish market conditions. (b) The chapter presents results from a scenario planning study for Germany as an example. Three scenarios for the future of mobility emerged from an elaborate scenario planning process: (1) Matured Progress, (2) Global Take-Off, (3) Frantic Standstill. In all three scenarios, the German population ages significantly, concentrates in urban areas and is increasingly aware of environmental issues with consequences for consumer choice. The scenarios differ specifically regarding immigration to Germany, the global and national economies, and the farsightedness of political decision making. Conforming to expectation, these heterogeneous external developments lead to different projections for future travel. Hence, the presented study can assist in identifying future developments that are very likely while others are subject to specific conditional processes. This helps explore the future market for electric mobility among other mobility innovations.
... (1) and (2) Nevertheless, energy consumption of BEVs was considered as a constant measure for electricity demand calculation in transportation sector. Different methods have been implemented for electricity consumption estimation for BEVs and mean value based on different reports was used in this research [44] [45]. Different amounts have been reported for electricity consumption and some of them are mentioned in Fig. 3. ...
... Combined energy consumption of BEVs (KWh/100km)[45] ...
Increasing electric vehicles usage, as a promising solution for environmental issues, might have unexpected implications, since it entails some changes in different sectors and scales in energy system. In this respect, this research aims at investigating the long-term impacts of electric vehicles deployment on Iran's energy system. Accordingly, Iran's energy system was analyzed by LEAP model in demand, supply, and transmission sides for all fuels and two different scenarios. Existing policies with limited optimistic assumptions was investigated as "reference" scenario. Alternatively, the other scenario, "electric cars" scenario, is for gradual substitution of electric vehicles for 15% gasoline cars until 2030 and renewable energy sources have more contribution in electricity production. Finally, carbon dioxide emission was predicted and compared in both scenarios for 25 years later. Results indicate that with "electric cars" scenario at 2030, Iran would have 9.2 % and 1.9% less Carbon Dioxide emissions in comparison to the "reference" scenario in the transportation sector and total system, respectively.
Among the many tools a manager can use for strategic planning, scenario planning stands out for its ability to capture a whole range of possibilities in rich detail. By identifying basic trends and uncertainties, a manager can construct a series of scenarios that will help to compensate for the usual errors in decision making—overconfidence and tunnel vision. Through case studies of Interpublic, an international advertising agency, and Anglo-American Corporation in South Africa, the author describes how to build scenarios in a step-by-step process and how to use the resulting stories to plan a company's future. INSETS: They believed it.;Three scenarios for the advertising industry.. [ABSTRACT FROM AUTHOR]
Current transportation models often do not explicitly address the degree of uncertainty in travel forecasts. Of particular interest in activity-based travel demand models is the model uncertainty that is caused by the statistical distributions of random components, i.e. micro-simulation error. Therefore, the main objective of this paper is to assess the impact of micro-simulation error on two key travel indices, namely the average daily number of trips per person and the average daily distance traveled per person. The effect of micro-simulation error will be investigated by running the activity-based modeling framework FEATHERS 200 times using the same 10% fraction of the population. Results show that micro-simulation errors are limited especially when disaggregation is limited to two levels. Notwithstanding, results indicate that for more elaborate analyses a 10% fraction might not be sufficient. The size of micro-simulation error increases along with complexity. Moreover, more commonly used transport modes such as using the car as driver have a lower error rate. Further research should investigate the impact of the population fraction on the micro-simulation error rates. Besides, one could also investigate other aspects (e.g. the number of activities) involved in the activity-scheduling process.
Findings from various sources of information, such as mobility panels, permanent road traffic recording devices, and model calculation methods, indicate that for the past few years passenger traffic demand in Germany has not been increasing but has shown notable evidence of stagnation. An analysis of various relevant factors clarifies that this has in fact been an emerging tendency. This is true especially with respect to the demographic changes in Germany and the increased probability of more scarce and definitely more expensive oil resources; further stagnation of traffic demand appears imminent That leads to the conclusion that infrastructure development must not be based on the idea of everlasting growth with expansions in areas in which the symptoms of traffic growth have been most obvious. It will rather be necessary to identify accurately specific areas of growth or stagnation and to find a suitable scale for further development. Future planning should concentrate on modification rather than on expansion of infrastructure facilities.
Previously published as an Appendix to the World development report. Incl. users guide, list of acronyms, bibl., index. The Little data book is a pocket edition of WDI
Error propagation in macro transport models
- C De Rham
- R Schwarz
- W Schaufelberger
Modellierung für die Verkehrsplanung. Theoretische, empirische und planungspraktische Rahmenbedingungen
- E Kutter
Plan tomorrow’s scenarios today. Inside Supply Management
- J Yuva
Handbuch Zukunftsmanagement-Werkzeuge der strategischen Planung und Früherkennung. Campus Verlag
- A Fink
- A Siebe
- J Dios Ortúzar de