Classification of traffic signal system anomalies for environment tests of autonomous vehicles
In the future there will be a lot of changes and development concerning autonomous transport that will affect all participants of transport. There are still difficulties in organizing transport, but with the introduction of autonomous vehicles more challenges can be expected. Recognizing and trackin...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Sciendo
2018-06-01
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| Series: | Production Engineering Archives |
| Subjects: | |
| Online Access: | https://doi.org/10.30657/pea.2018.19.09 |
| _version_ | 1818754786995994624 |
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| author | Lengyel Henrietta Szalay Zsolt |
| author_facet | Lengyel Henrietta Szalay Zsolt |
| author_sort | Lengyel Henrietta |
| collection | DOAJ |
| description | In the future there will be a lot of changes and development concerning autonomous transport that will affect all participants of transport. There are still difficulties in organizing transport, but with the introduction of autonomous vehicles more challenges can be expected. Recognizing and tracking horizontal and vertical signs can cause a difficulties for drivers and, later, for autonomous systems. Environmental conditions, deformity and quality affect the perception of signals. The correct recognition results in safe travelling for everyone on the roads. Traffic signs are designed for people that is why the recognition process is harder for the machines. However, nowadays some developers try to create a traffic sign that autonomous vehicles can use. Computer identification needs further development, as it is necessary to consider cases where traffic signs are deformed or not properly placed. In the following investigation, the advantages and disadvantages of the different perception methods and their possibilities were gathered. A methodology for the classification of horizontal and vertical traffic signs anomalies that may help in designing better testing and validation environments for traffic sign recognition systems in the future was also proposed. |
| first_indexed | 2024-12-18T05:28:48Z |
| format | Article |
| id | doaj.art-83d99968bc26448ea7c727a06de3fd65 |
| institution | Directory Open Access Journal |
| issn | 2353-7779 |
| language | English |
| last_indexed | 2024-12-18T05:28:48Z |
| publishDate | 2018-06-01 |
| publisher | Sciendo |
| record_format | Article |
| series | Production Engineering Archives |
| spelling | doaj.art-83d99968bc26448ea7c727a06de3fd652022-12-21T21:19:29ZengSciendoProduction Engineering Archives2353-77792018-06-011919434710.30657/pea.2018.19.09Classification of traffic signal system anomalies for environment tests of autonomous vehiclesLengyel Henrietta0Szalay Zsolt1Budapest University of Technology and Economics, Hungary, 1111Budapest Stoczek Street 6.Budapest University of Technology and Economics, Hungary, 1111Budapest Stoczek Street 6.In the future there will be a lot of changes and development concerning autonomous transport that will affect all participants of transport. There are still difficulties in organizing transport, but with the introduction of autonomous vehicles more challenges can be expected. Recognizing and tracking horizontal and vertical signs can cause a difficulties for drivers and, later, for autonomous systems. Environmental conditions, deformity and quality affect the perception of signals. The correct recognition results in safe travelling for everyone on the roads. Traffic signs are designed for people that is why the recognition process is harder for the machines. However, nowadays some developers try to create a traffic sign that autonomous vehicles can use. Computer identification needs further development, as it is necessary to consider cases where traffic signs are deformed or not properly placed. In the following investigation, the advantages and disadvantages of the different perception methods and their possibilities were gathered. A methodology for the classification of horizontal and vertical traffic signs anomalies that may help in designing better testing and validation environments for traffic sign recognition systems in the future was also proposed.https://doi.org/10.30657/pea.2018.19.09classificationtraffic signal systemanomaliesautonomous vehiclestest environmentl91m11 |
| spellingShingle | Lengyel Henrietta Szalay Zsolt Classification of traffic signal system anomalies for environment tests of autonomous vehicles Production Engineering Archives classification traffic signal system anomalies autonomous vehicles test environment l91 m11 |
| title | Classification of traffic signal system anomalies for environment tests of autonomous vehicles |
| title_full | Classification of traffic signal system anomalies for environment tests of autonomous vehicles |
| title_fullStr | Classification of traffic signal system anomalies for environment tests of autonomous vehicles |
| title_full_unstemmed | Classification of traffic signal system anomalies for environment tests of autonomous vehicles |
| title_short | Classification of traffic signal system anomalies for environment tests of autonomous vehicles |
| title_sort | classification of traffic signal system anomalies for environment tests of autonomous vehicles |
| topic | classification traffic signal system anomalies autonomous vehicles test environment l91 m11 |
| url | https://doi.org/10.30657/pea.2018.19.09 |
| work_keys_str_mv | AT lengyelhenrietta classificationoftrafficsignalsystemanomaliesforenvironmenttestsofautonomousvehicles AT szalayzsolt classificationoftrafficsignalsystemanomaliesforenvironmenttestsofautonomousvehicles |