Traffic Regulator Detection and Identification from Crowdsourced Data—A Systematic Literature Review

Download statistics - Document (COUNTER):

Zourlidou, S.; Sester, M.: Traffic Regulator Detection and Identification from Crowdsourced Data—A Systematic Literature Review. In: ISPRS International Journal of Geo-Information 8 (2019), Nr. 11, 491. DOI:

Repository version

To cite the version in the repository, please use this identifier:

Selected time period:


Sum total of downloads: 120

Mapping with surveying equipment is a time-consuming and cost-intensive procedure thatmakes the frequent map updating unaffordable. In the last few years, much research has focused oneliminating such problems by counting on crowdsourced data, such as GPS traces. An importantsource of information in maps, especially under the consideration of forthcoming self-driving vehicles,is the traffic regulators. This information is largely lacking in maps like OpenstreetMap (OSM) andthis article is motivated by this fact. The topic of this systematic literature review (SLR) is the detectionand recognition of traffic regulators such as traffic lights (signals), stop-, yield-, priority-signs, right ofway priority rules and turning restrictions at intersections, by leveraging non imagery crowdsourceddata. More particularly, the aim of this study is (1) to identify the range of detected and recognisedregulatory types bycrowdsensingmeans, (2) to indicate the different classification techniques thatcan be used for these two tasks, (3) to assess the performance of different methods, as well as (4)to identify important aspects of the applicability of these methods. The two largest databases ofpeer-reviewed literature were used to locate relevant research studies and after different screeningsteps eleven articles were selected for review. Two major findings were concluded—(a) most regulatortypes can be identified with over 80% accuracy, even using heuristic-driven approaches and (b) underthe current progress on the field, no study can be reproduced for comparative purposes nor can solelyrely on open data sources due to lack of publicly available datasets and ground truth maps. Futureresearch directions are highlighted as possible extensions of the reviewed studies.
License of this version: CC BY 4.0 Unported
Document Type: Article
Publishing status: publishedVersion
Issue Date: 2019
Appears in Collections:Fakultät für Bauingenieurwesen und Geodäsie

distribution of downloads over the selected time period:

downloads by country:

pos. country downloads
total perc.
1 image of flag of Germany Germany 44 36.67%
2 image of flag of United States United States 27 22.50%
3 image of flag of India India 6 5.00%
4 image of flag of No geo information available No geo information available 5 4.17%
5 image of flag of Russian Federation Russian Federation 5 4.17%
6 image of flag of Iran, Islamic Republic of Iran, Islamic Republic of 5 4.17%
7 image of flag of China China 5 4.17%
8 image of flag of Philippines Philippines 3 2.50%
9 image of flag of Netherlands Netherlands 3 2.50%
10 image of flag of Lithuania Lithuania 2 1.67%
    other countries 15 12.50%

Further download figures and rankings:


Zur Erhebung der Downloadstatistiken kommen entsprechend dem „COUNTER Code of Practice for e-Resources“ international anerkannte Regeln und Normen zur Anwendung. COUNTER ist eine internationale Non-Profit-Organisation, in der Bibliotheksverbände, Datenbankanbieter und Verlage gemeinsam an Standards zur Erhebung, Speicherung und Verarbeitung von Nutzungsdaten elektronischer Ressourcen arbeiten, welche so Objektivität und Vergleichbarkeit gewährleisten sollen. Es werden hierbei ausschließlich Zugriffe auf die entsprechenden Volltexte ausgewertet, keine Aufrufe der Website an sich.

Search the repository