Roadside acoustic sensors to support vulnerable pedestrians via their smartphones
This paper proposes a smartphone-based warning system to evaluate the risk of a motor vehicle for vulnerable pedestrians (VP). The acoustic sensors are embedded in the roadside to receive vehicle sounds and they are classified into heavy vehicles, light vehicles with low speed, light vehicles with h...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Amirkabir University of Technology
2020-09-01
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| Series: | AUT Journal of Mathematics and Computing |
| Subjects: | |
| Online Access: | https://ajmc.aut.ac.ir/article_3312_7ee4eab5afed0ebc3e4224291966c8e6.pdf |
| _version_ | 1827350041072762880 |
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| author | Mehdi Ghatee Masoomeh Khalili Mehdi Teimouri Mohammad Mahdi Bejani |
| author_facet | Mehdi Ghatee Masoomeh Khalili Mehdi Teimouri Mohammad Mahdi Bejani |
| author_sort | Mehdi Ghatee |
| collection | DOAJ |
| description | This paper proposes a smartphone-based warning system to evaluate the risk of a motor vehicle for vulnerable pedestrians (VP). The acoustic sensors are embedded in the roadside to receive vehicle sounds and they are classified into heavy vehicles, light vehicles with low speed, light vehicles with high speed, and no vehicle classes. For this aim, we extract new features by Mel-frequency Cepstrum Coefficients (MFCC) and Linear Predictive Coefficients (LPC) algorithms. We use different classification algorithms and show that MLP neural network achieves at least $96.77$% accuracy criterion. To install this system, directional microphones are embedded on the roadside and the risk is classified. Then, for every microphone, a danger area is defined and the warning alarms have been sent to every VPs’ smartphones covered in this danger area. |
| first_indexed | 2024-03-08T00:51:57Z |
| format | Article |
| id | doaj.art-6dde3fcc714947aa83e93eb8cee2c9aa |
| institution | Directory Open Access Journal |
| issn | 2783-2449 2783-2287 |
| language | English |
| last_indexed | 2024-03-08T00:51:57Z |
| publishDate | 2020-09-01 |
| publisher | Amirkabir University of Technology |
| record_format | Article |
| series | AUT Journal of Mathematics and Computing |
| spelling | doaj.art-6dde3fcc714947aa83e93eb8cee2c9aa2024-02-14T19:35:59ZengAmirkabir University of TechnologyAUT Journal of Mathematics and Computing2783-24492783-22872020-09-011213514310.22060/ajmc.2019.15479.10173312Roadside acoustic sensors to support vulnerable pedestrians via their smartphonesMehdi Ghatee0Masoomeh Khalili1Mehdi Teimouri2Mohammad Mahdi Bejani3Department of Mathematics and Computer Science, Amirkabir University of Technology, Tehran, IranDepartment of Mathematics and Computer Science, Amirkabir University of Technology, Tehran, IranFaculty of New Sciences and Technologies, University of Tehran, Tehran, IranDepartment of Mathematics and Computer Science, Amirkabir University of Technology, Tehran, IranThis paper proposes a smartphone-based warning system to evaluate the risk of a motor vehicle for vulnerable pedestrians (VP). The acoustic sensors are embedded in the roadside to receive vehicle sounds and they are classified into heavy vehicles, light vehicles with low speed, light vehicles with high speed, and no vehicle classes. For this aim, we extract new features by Mel-frequency Cepstrum Coefficients (MFCC) and Linear Predictive Coefficients (LPC) algorithms. We use different classification algorithms and show that MLP neural network achieves at least $96.77$% accuracy criterion. To install this system, directional microphones are embedded on the roadside and the risk is classified. Then, for every microphone, a danger area is defined and the warning alarms have been sent to every VPs’ smartphones covered in this danger area.https://ajmc.aut.ac.ir/article_3312_7ee4eab5afed0ebc3e4224291966c8e6.pdfintelligent transportation systemsacoustic signal analysissmartphoneroad traffic sensorsroad safetyrisk analysisvulnerable pedestrians |
| spellingShingle | Mehdi Ghatee Masoomeh Khalili Mehdi Teimouri Mohammad Mahdi Bejani Roadside acoustic sensors to support vulnerable pedestrians via their smartphones AUT Journal of Mathematics and Computing intelligent transportation systems acoustic signal analysis smartphone road traffic sensors road safety risk analysis vulnerable pedestrians |
| title | Roadside acoustic sensors to support vulnerable pedestrians via their smartphones |
| title_full | Roadside acoustic sensors to support vulnerable pedestrians via their smartphones |
| title_fullStr | Roadside acoustic sensors to support vulnerable pedestrians via their smartphones |
| title_full_unstemmed | Roadside acoustic sensors to support vulnerable pedestrians via their smartphones |
| title_short | Roadside acoustic sensors to support vulnerable pedestrians via their smartphones |
| title_sort | roadside acoustic sensors to support vulnerable pedestrians via their smartphones |
| topic | intelligent transportation systems acoustic signal analysis smartphone road traffic sensors road safety risk analysis vulnerable pedestrians |
| url | https://ajmc.aut.ac.ir/article_3312_7ee4eab5afed0ebc3e4224291966c8e6.pdf |
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