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Please use this identifier to cite or link to this item: http://hdl.handle.net/11375/29905
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dc.contributor.advisorvon Mohrenschildt, Martin-
dc.contributor.advisorHabibi, Saeid-
dc.contributor.authorSochaniwsky, Adrian-
dc.date.accessioned2024-06-27T14:17:55Z-
dc.date.available2024-06-27T14:17:55Z-
dc.date.issued2024-
dc.identifier.urihttp://hdl.handle.net/11375/29905-
dc.description.abstractIntelligent Transportation Systems are advanced technologies used to reduce traffic and increase road safety for vulnerable road users. Real-time traffic monitoring is an important technology for collecting and reporting the information required to achieve these goals through the detection and tracking of road users inside an intersection. To be effective, these systems must be robust to all environmental conditions. This thesis explores the fusion of camera and Light Detection and Ranging (LiDAR) sensors to create an accurate and real-time traffic monitoring system. Sensor fusion leverages complimentary characteristics of the sensors to increase system performance in low- light and inclement weather conditions. To achieve this, three primary components are developed: a 3D LiDAR detection pipeline, a camera detection pipeline, and a decision-level sensor fusion module. The proposed pipeline is lightweight, running at 46 Hz on modest computer hardware, and accurate, scoring 3% higher than the camera-only pipeline based on the Higher Order Tracking Accuracy metric. The camera-LiDAR fusion system is built on the ROS 2 framework, which provides a well-defined and modular interface for developing and evaluated new detection and tracking algorithms. Overall, the fusion of camera and LiDAR sensors will enable future traffic monitoring systems to provide cities with real-time information critical for increasing safety and convenience for all road-users.en_US
dc.language.isoenen_US
dc.subjectcomputer visionen_US
dc.subjectLiDARen_US
dc.subjectobject detectionen_US
dc.subjectmulti-object trackingen_US
dc.subjectintelligent transportation systemsen_US
dc.subjectsensor fusionen_US
dc.titleA LIGHTWEIGHT CAMERA-LIDAR FUSION FRAMEWORK FOR TRAFFIC MONITORING APPLICATIONSen_US
dc.title.alternativeA CAMERA-LIDAR FUSION FRAMEWORKen_US
dc.typeThesisen_US
dc.contributor.departmentComputing and Softwareen_US
dc.description.degreetypeThesisen_US
dc.description.degreeMaster of Applied Science (MASc)en_US
dc.description.layabstractAccurate traffic monitoring systems are needed to improve the safety of road users. These systems allow the intersection to “see” vehicles and pedestrians, providing near instant information to assist future autonomous vehicles, and provide data to city planers and officials to enable reductions in traffic, emissions, and travel times. This thesis aims to design, build, and test a traffic monitoring system that uses a camera and 3D laser-scanner to find and track road users in an intersection. By combining a camera and 3D laser scanner, this system aims to perform better than either sensor alone. Furthermore, this thesis will collect test data to prove it is accurate and able to see vehicles and pedestrians during the day and night, and test if runs fast enough for “live” use.en_US
Appears in Collections:Open Access Dissertations and Theses

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