| 1. |
- Ehsani, Johnathon P., et al.
(författare)
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Naturalistic Driving Studies: An Overview and International Perspective
- 2021
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Ingår i: International Encyclopedia of Transportation: Volume 1-7. ; , s. 20-38
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Bokkapitel (övrigt vetenskapligt/konstnärligt)abstract
- Naturalistic driving studies (NDS) are a method in transportation research that is increasingly used to bridge the gap between epidemiological research (e.g., using population crash databases) and individual level or experimental research (e.g., self-reported surveys or driving simulators). This article begins with defining NDS and providing a brief overview of NDS methods, including the strengths, limits and the unique ethical issues involved in conducting NDS. Following this, five case studies from Australia, Canada, China, the European Union, and the United States are presented, along with a synthesis of the lessons they have learned. The article concludes with a discussion of what the future of NDS may look like.
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| 2. |
- Senserrick, Teresa M
(författare)
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Identifying subgroups of road users for countermeasure development : two Australian examples
- 2001
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Ingår i: Proceedings of the conference Traffic Safety on Three Continents. - Linköping : Statens väg- och transportforskningsinstitut. ; , s. 516-528
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Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
- Cluster analysis is a statistical classification technique that can identify subgroups of people with similar profiles on a research measure or measures. Given its exploratory nature, cluster analysis has a somewhat controversial history in traffic safety research. It has been argued that the ability to produce different solutions using different methods reduces the credibility of cluster analysis as a useful measure for traffic safety research. Part of the problem has been the inconsistent selection of clustering techniques by researchers. This is true even though studies of biological data with known structures have identified and recommended particular methods to apply to particular types of data. In addition, many validation techniques have been developed to test selected solutions. This paper presents an overview of these issues, including two recent Australian studies that have included cluster analyses; one relating to seat belt use and the other to speeding behavior. In each case profiles of road user subgroups were identified based on differences in self-reported road safety attitudes and behaviors. The studies also used factor analysis to first reduce the amount of variables entered into the cluster analysis. In this way multiple measures could be included. It is argued that this combination, factor analysis followed by cluster analysis, can provide a powerful exploratory tool for traffic safety research.
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