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Detection and Classification of Obstacles apply to Path Planning for Passenger Vehicles in Urban Environment

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Author(s):
Poliane Torres Megda
Total Authors: 1
Document type: Master's Dissertation
Press: São Carlos.
Institution: Universidade de São Paulo (USP). Escola de Engenharia de São Carlos (EESC/SBD)
Defense date:
Examining board members:
Marcelo Becker; Daniel Varela Magalhães; Roseli Aparecida Francelin Romero
Advisor: Marcelo Becker
Abstract

Every day the number of vehicles on the roads around the world is increasing. This growth combined with the negligence of drivers and some external factors such as poorly maintained roads and adverse weather conditions resulted in a huge increase in the number of accidents and hence casualties. Currently many research groups and automotive companies are developing and adapting technologies that can be incorporated into vehicles to reduce these numbers. An interesting example of these technologies is the detection and classification of moving obstacles (vehicles, people, etc.) in urban environments. This dissertation presents the development of algorithms which main objective are identify, track and predict moving obstacles, determine prohibited directions of traffic and calculate collision free trajectories. In order to accomplish with such task, data from the laser sensor SICK LMS 291-S05 later treated using computational resources such as the Trackers technique was used to monitor the environment ahead of the test vehicle (a modified passenger car). The Trackers technique was used to classify all the hurdles identified in two main classes: static and mobile obstacles. Once the obstacle was identified, this still been followed even if they leave the field of vision sensor. After classification of obstacles in the environment, their positions are analyzed and prohibited for traffic directions are determined by the algorithm Velocity Obstacle Approach. Finally the technique is applied to calculate trajectories of E* that generates a smooth path and free of collisions. If any obstacle block, or create a risk of collision through the generated path, the trajectory can be recalculated without the need to fully re-analyze de environment map. The results demonstrated the applicability of the methodology used. The Trackers algorithm has detected pedestrians and vehicles determining their dynamic characteristics. The algorithm Velocity Obstacle Approach keep up with the obstacles and was able to determine the prohibited directions and, finally, E* the algorithm was able to generate obstacle-free paths in unknown environments. (AU)

FAPESP's process: 09/04787-0 - SENA - Autonomous Embedded Navigation System: navigator for urban-like environments
Grantee:Poliane Torres Megda
Support Opportunities: Scholarships in Brazil - Master