Embedded open source applications for future electric vehicles
Urbanisation, growth of cities and their population bring serious changes into our lives. That includes increasing numbers of cars on the road and traffic complexity. Since the very early stages of car and traffic development the very first concern of the designers and engineers was safety on the ro...
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| Format: | Final Year Project (FYP) |
| Language: | English |
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2012
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| Online Access: | http://hdl.handle.net/10356/48597 |
| _version_ | 1811688777517629440 |
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| author | Mazhyn Azamat. |
| author2 | Ian Vince McLoughlin |
| author_facet | Ian Vince McLoughlin Mazhyn Azamat. |
| author_sort | Mazhyn Azamat. |
| collection | NTU |
| description | Urbanisation, growth of cities and their population bring serious changes into our lives. That includes increasing numbers of cars on the road and traffic complexity. Since the very early stages of car and traffic development the very first concern of the designers and engineers was safety on the road. Most commonly it depends on the drivers and pedestrians directly. Attentiveness or inattentiveness of the traffic participants is one of the reasons why accidents can happen. This project was developed to drag attention of the drivers on the most dangerous situation on the road, traffic lights. Traffic lights are dangerous because they are places where most of the traffic participants might gather at the same time. The purpose of having traffic lights is to provide safety, however most accidents still happen on the intersections and pedestrian crossings. During the past year, this student of NTU has been working on traffic light detection via video camera and signalling to the driver when a traffic light ahead turns red. To make the application simpler, cheaper and more flexible for other purposes image analysis and image processing is used. Since, all of the procedures run on the software it requires simpler hardware with lower cost and it can be used for other applications like complex black box or traffic condition analyzer. Traffic light detection uses simple colour analysis. Looking at the objects on the images, the task is to find red, green or yellow circles. Then to identify the background of the circles and their positioning. To find objects on the image colour difference was used to find edges in the image and simple geometrical formulas used to identify object shapes. As a result, an application has been developed that works on computer or smartphone and identifies traffic lights within the image. This project is one of the pioneers in this area. Similar projects are currently being developed by Mercedes – Benz and Opel. Also, since there has not been much similar work done before, there is only one article about this particular application. |
| first_indexed | 2024-10-01T05:37:36Z |
| format | Final Year Project (FYP) |
| id | ntu-10356/48597 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T05:37:36Z |
| publishDate | 2012 |
| record_format | dspace |
| spelling | ntu-10356/485972023-03-03T20:46:17Z Embedded open source applications for future electric vehicles Mazhyn Azamat. Ian Vince McLoughlin School of Computer Engineering DRNTU::Engineering::Computer science and engineering::Computing methodologies::Image processing and computer vision DRNTU::Engineering::Computer science and engineering::Computer applications::Physical sciences and engineering Urbanisation, growth of cities and their population bring serious changes into our lives. That includes increasing numbers of cars on the road and traffic complexity. Since the very early stages of car and traffic development the very first concern of the designers and engineers was safety on the road. Most commonly it depends on the drivers and pedestrians directly. Attentiveness or inattentiveness of the traffic participants is one of the reasons why accidents can happen. This project was developed to drag attention of the drivers on the most dangerous situation on the road, traffic lights. Traffic lights are dangerous because they are places where most of the traffic participants might gather at the same time. The purpose of having traffic lights is to provide safety, however most accidents still happen on the intersections and pedestrian crossings. During the past year, this student of NTU has been working on traffic light detection via video camera and signalling to the driver when a traffic light ahead turns red. To make the application simpler, cheaper and more flexible for other purposes image analysis and image processing is used. Since, all of the procedures run on the software it requires simpler hardware with lower cost and it can be used for other applications like complex black box or traffic condition analyzer. Traffic light detection uses simple colour analysis. Looking at the objects on the images, the task is to find red, green or yellow circles. Then to identify the background of the circles and their positioning. To find objects on the image colour difference was used to find edges in the image and simple geometrical formulas used to identify object shapes. As a result, an application has been developed that works on computer or smartphone and identifies traffic lights within the image. This project is one of the pioneers in this area. Similar projects are currently being developed by Mercedes – Benz and Opel. Also, since there has not been much similar work done before, there is only one article about this particular application. Bachelor of Engineering (Computer Engineering) 2012-04-27T02:49:58Z 2012-04-27T02:49:58Z 2012 2012 Final Year Project (FYP) http://hdl.handle.net/10356/48597 en Nanyang Technological University 44 p. application/pdf |
| spellingShingle | DRNTU::Engineering::Computer science and engineering::Computing methodologies::Image processing and computer vision DRNTU::Engineering::Computer science and engineering::Computer applications::Physical sciences and engineering Mazhyn Azamat. Embedded open source applications for future electric vehicles |
| title | Embedded open source applications for future electric vehicles |
| title_full | Embedded open source applications for future electric vehicles |
| title_fullStr | Embedded open source applications for future electric vehicles |
| title_full_unstemmed | Embedded open source applications for future electric vehicles |
| title_short | Embedded open source applications for future electric vehicles |
| title_sort | embedded open source applications for future electric vehicles |
| topic | DRNTU::Engineering::Computer science and engineering::Computing methodologies::Image processing and computer vision DRNTU::Engineering::Computer science and engineering::Computer applications::Physical sciences and engineering |
| url | http://hdl.handle.net/10356/48597 |
| work_keys_str_mv | AT mazhynazamat embeddedopensourceapplicationsforfutureelectricvehicles |