A LARGE SCALE METHOD FOR EXTRACTING GEOGRAPHICAL FEATURES ON BUS ROUTES FROM OPENSTREETMAP AND ASSESSMENT OF THEIR IMPACT ON BUS SPEED AND RELIABILITY
| Autor: | L. Dunne, G. McArdle |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2022 |
| Předmět: | |
| Zdroj: | The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XLVIII-4-W5-2022, Pp 37-44 (2022) |
| Druh dokumentu: | article |
| ISSN: | 1682-1750 2194-9034 |
| DOI: | 10.5194/isprs-archives-XLVIII-4-W5-2022-37-2022 |
| Popis: | Geographical features on bus routes impact a bus’s performance, and as a consequence affect human mobility through cities. Analysis of these geographical features is non-trivial because they often must be manually recorded, limiting the ability to extract these features on a large scale. This paper proposes a novel method of extracting features from crowd-sourced OpenStreetMap (OSM) data and compares this method to the ground truth data for 539 stop pair segments in Dublin, Ireland. This paper also proposes algorithms to detect turns and the direction taken by buses at roundabouts, using the angle between points on the segment lines. Statistical analysis was performed, and elastic net linear regression models were developed with a subset of the route features to show their effect. The results show over 97% accurate identification of most individual features using the novel technique, with most errors resulting from OSM quality issues. The features that most negatively affected the average speed and reliability of the bus with statistical significance (p |
| Databáze: | Directory of Open Access Journals |
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