Recognition of built-up and non-built-up areas from road scenes
Purpose In many cases, it does not follow from the road design, whether the given scene is within or outside the posted built-up area. The purpose of this paper is to evaluate road scenes, how far they can be considered being of built-up and non-built-up nature, as well as to identify road scenes wh...
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Veröffentlicht in: | European transport research review 2016-06, Vol.8 (2), p.1-9, Article 17 |
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Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | Purpose
In many cases, it does not follow from the road design, whether the given scene is within or outside the posted built-up area. The purpose of this paper is to evaluate road scenes, how far they can be considered being of built-up and non-built-up nature, as well as to identify road scenes which are ambiguous and therefore less safe.
Methods
Two methods were used to assess the degree of unambiguous or ambiguous nature of road scenes. In the first approach, a survey of requested speeds at various road scenes was performed with 500 respondents. Here clearly non-built-up and built-up sites, as well as unclear sites were compared. In the second method, the recognition process of drivers was simulated by an image classification software. The classifier was trained by 100 clearly built-up and 100 non-built-up pictures. Four test runs followed, each using 200 pictures from different roads.
Results
From the speed choice study, results have shown that in unclear situations (e.g. transition between built-up and non-built-up areas) the standard deviation of chosen speeds is higher than in unambiguous situations. In the image classification study the trained classifier worked well for road scenes which are definitely of built-up or non-built-up nature. Furthermore, as expected, for unclear situations, the classifier gave uncertain classifications.
Conclusions
Each of the two methods produces an output indicator, the standard deviation of speeds and the certainty score, respectively. Both indicators can serve to identify road scenes leading to uncertain and therefore risky situations. |
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ISSN: | 1867-0717 1866-8887 |
DOI: | 10.1007/s12544-016-0205-9 |