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Innovative methodologies for exploring the future of automated vehicle guidance
Author(s) -
Marchau V. A. W. J.,
van der Heijden R. E. C. M.
Publication year - 2003
Publication title -
journal of forecasting
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.543
H-Index - 59
eISSN - 1099-131X
pISSN - 0277-6693
DOI - 10.1002/for.853
Subject(s) - scope (computer science) , implementation , variety (cybernetics) , computer science , backcasting , automation , set (abstract data type) , risk analysis (engineering) , management science , process management , operations research , software engineering , artificial intelligence , business , engineering , mechanical engineering , ecology , sustainability , biology , programming language
In various countries, transport policy makers are increasingly interested in the automation of vehicle driving tasks. Current policy developments regarding Automated Vehicle Guidance (AVG) are complicated by several uncertainties about the development of AVG technologies, whether their implementation will contribute to or conflict with transport policy goals, and the basic societal conditions that are required for AVG implementation. In this article, we present an approach to reduce the uncertainty regarding alternative AVG implementations. In particular, we develop a backcasting approach to limit the scope of policy development and research by eliminating parts of the large variety in possible AVG developments. This approach consists of the following steps: (1) the specification of plausible AVG concepts; (2) the analysis of the conditions for the implementation of these concepts, resulting in a set of promising AVG concepts and (3) the analysis whether stakeholders' decisions and actions related to the implementation of plausible concepts will be fulfilled in time. This approach helps to eliminate non‐plausible, non‐promising and non‐accepted AVG concepts and reduce the scope of policy making to the most viable ones. Copyright © 2003 John Wiley & Sons, Ltd.