Development of Automated Incident Detection System Using Existing ATMS CCTV
| dc.contributor.author | Chien, Stanley | |
| dc.contributor.author | Chen, Yaobin | |
| dc.contributor.author | Yi, Qiang | |
| dc.contributor.author | Ding, Zhengming | |
| dc.contributor.department | Electrical and Computer Engineering, School of Engineering and Technology | en_US |
| dc.date.accessioned | 2022-02-16T21:10:35Z | |
| dc.date.available | 2022-02-16T21:10:35Z | |
| dc.date.issued | 2019 | |
| dc.description.abstract | Indiana Department of Transportation (INDOT) has over 300 digital cameras along highways in populated areas in Indiana. These cameras are used to monitor traffic conditions around the clock, all year round. Currently, the videos from these cameras are observed by human operators. The main objective of this research is to develop an automatic real-time system to monitor traffic conditions using the INDOT CCTV video feeds by a collaborative research team of the Transportation Active Safety Institute (TASI) at Indiana University-Purdue University Indianapolis (IUPUI) and the Traffic Management Center (TMC) of INDOT. | en_US |
| dc.eprint.version | Final published version | en_US |
| dc.identifier.citation | Chien, S., Chen, Y., Yi, Q., & Ding, Z. (2019). Development of Automated Incident Detection System Using Existing ATMS CCTV. JTRP Technical Reports. https://doi.org/10.5703/1288284317101 | en_US |
| dc.identifier.uri | https://hdl.handle.net/1805/27822 | |
| dc.language.iso | en | en_US |
| dc.publisher | Purdue University | en_US |
| dc.relation.isversionof | 10.5703/1288284317101 | en_US |
| dc.relation.journal | JTRP Technical Reports | en_US |
| dc.rights | Publisher Policy | en_US |
| dc.source | Publisher | en_US |
| dc.subject | traffic incident detection | en_US |
| dc.subject | vehicle classification | en_US |
| dc.subject | deep learning | en_US |
| dc.title | Development of Automated Incident Detection System Using Existing ATMS CCTV | en_US |
| dc.type | Article | en_US |