Keeping the vehicle on the road
| Autor: | Gokhan Yenikaya, Ekrem Düven, Sibel Yenikaya |
|---|---|
| Přispěvatelé: | Uludağ Üniversitesi/Mühendislik Fakültesi/Elektrik ve Elektronik Mühendisliği Bölümü., Yeni̇kaya, Sibel, Yenikaya, Gökhan, Düven, Ekrem, AAA-5126-2019 |
| Rok vydání: | 2013 |
| Předmět: |
Computer science
Performance Extraction Advanced driver assistance systems Surveys Vehicle Information and Communication System Lane detection Field (computer science) law.invention Camera Vanishing Point Driver Assistance Vision system Intelligent vehicle highway systems law Computer vision Radar Road following Longitudinal control Computer science theory & methods Tracking Intelligent vehicles Visual information Roads and streets Reliability Obstacle detection Algorithm Tracking (position) Obstacle detectors Obstacle Algorithms Heading (navigation) General Computer Science Context (language use) Optical radar Theoretical Computer Science Relative positions Road detecetion Experimentation Low-power consumption business.industry Verification Vehicles Parallel Heading directions Wireless sensor networks Recognition Driver assistance Artificial intelligence business Wireless sensor network |
| Zdroj: | ACM Computing Surveys. 46:1-43 |
| ISSN: | 1557-7341 0360-0300 |
| Popis: | The development of wireless sensor networks, such as researchers Advanced Driver Assistance Systems (ADAS) requires the ability to analyze the road scene just like a human does. Road scene analysis is an essential, complex, and challenging task and it consists of: road detection (which includes the localization of the road, the determination of the relative position between vehicle and road, and the analysis of the vehicle's heading direction) and obstacle detection (which is mainly based on localizing possible obstacles on the vehicle's path). The detection of the road borders, the estimation of the road geometry, and the localization of the vehicle are essential tasks in this context since they are required for the lateral and longitudinal control of the vehicle. Within this field, on-board vision has been widely used since it has many advantages (higher resolution, low power consumption, low cost, easy aesthetic integration, and nonintrusive nature) over other active sensors such as RADAR or LIDAR. At first glance the problem of detecting the road geometry from visual information seems simple and early works in this field were quickly rewarded with promising results. However, the large variety of scenarios and the high rates of success demanded by the industry have kept the lane detection research work alive. In this article a comprehensive review of vision-based road detection systems vision is presented. |
| Databáze: | OpenAIRE |
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