With connected and autonomous vehicles, no optimal standard or framework currently exists, outlining the right level of information sharing for cooperative autonomous driving. Cooperative Perception is proposed among vehicles, where every vehicle is transformed into a moving sensor platform that is capable of sharing information collected using its on-board sensors. This helps extend the line of sight and field of view of autonomous vehicles, which otherwise suffer from blind spots and occlusions. This increase in situational awareness promotes safe driving over a short range and improves traffic flow efficiency over a long range.
This thesis proposes a methodology for cooperative perception for autonomous vehicles over a short range. The problem of cooperative perception is broken down into sub-tasks of cooperative relative localization and map merging. Cooperative relative localization is achieved using visual and inertial sensors, where a computer-vision based camera relative pose estimation technique, augmented with position information, is used to provide a pose-fix that is subsequently updated by dead reckoning using an inertial sensor. Prior to map merging, a technique for object localization using a monocular camera is proposed that is based on the Inverse Perspective Mapping technique. A mobile multi-robot testbed was developed to emulate autonomous vehicles and the proposed method was implemented on the testbed to detect pedestrians and also to respond to the perceived hazard. Potential traffic scenarios where cooperative perception could prove crucial were tested and the results are presented in this thesis. / MS / Perception in Autonomous Vehicles is limited to the field of view of the vehicles’ onboard sensors and the environment may not be fully perceivable due to the presence of blind spots and occlusions. To overcome this limitation, Vehicle-to-Vehicle wireless communication could be leveraged to exchange locally sensed information among vehicles within the vicinity. Vehicles may share information about their own position, heading and velocity or go one step further and share information about their surroundings as well. This latter form of cooperative perception extends each vehicle’s field of view and line of sight, and helps increase situational awareness. The result is an increase in safety over a short range whereas communication over a long range could help improve traffic flow efficiency. This thesis proposes one such technique for cooperative perception over a short range. The system uses visual and inertial sensors to perform cooperative localization between two vehicles sharing a common field of view, which allows one vehicle to locate the other vehicle in its frame of reference. Subsequently, information about objects in the surroundings of one vehicle, localized using a visual sensor is relayed to the other vehicle through communication. A mobile multi-robot testbed was developed to emulate autonomous vehicles and to experimentally evaluate the proposed method through a series of driving scenario test cases in which cooperative perception could be effective and crucial to the safety and comfort of driving.
| Identifer | oai:union.ndltd.org:VTETD/oai:vtechworks.lib.vt.edu:10919/88742 |
| Date | 03 October 2017 |
| Creators | Sridhar, Srivatsan |
| Contributors | Mechanical Engineering, Eskandarian, Azim, Taheri, Saied, Ferris, John B. |
| Publisher | Virginia Tech |
| Source Sets | Virginia Tech Theses and Dissertation |
| Detected Language | English |
| Type | Thesis |
| Format | ETD, application/pdf |
| Rights | In Copyright, http://rightsstatements.org/vocab/InC/1.0/ |
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