A vehicle driving assistance system based on sensor fusion.

• Grant number: 10/01305-1
• Support Opportunities: Scholarships in Brazil - Doctorate
• Start date: December 01, 2010
• End date: February 28, 2015
• Field of knowledge: Physical Sciences and Mathematics - Computer Science
• Principal Investigator: Denis Fernando Wolf
• Grantee: Patrick Yuri Shinzato
• Host Institution: Instituto de Ciências Matemáticas e de Computação (ICMC). Universidade de São Paulo (USP). São Carlos , SP, Brazil
• Associated scholarship(s): 11/21956-0 - Development of autonomous vehicles: a hybrid method for identifying markings in urban traffic, BE.EP.DR

Abstract

The autonomous navigation is one of the fundamental problems of mobile robotics. This subject has been researched for a long time, however still shown great potential for scientific research. Most of the algorithms and solutions developed are designed to operate in highly structured environments, such as halls and buildings. Another issue also interesting to researchers working in this area is the navigation in outdoor unstructured and, more specifically, the development of intelligent autonomous vehicles.This research project proposes to develop a driving assistance system for vehicles in urban environments through sensor fusion. Aiming at reducing the number of traffic accidents through the use of information from laser sensors and video cameras for the construction of a navigable map of the environment. Based on this map, the vehicle driver can be warned at risk of collision, holes in the track and close the tab.

Scientific publications

(The scientific publications listed on this page originate from the Web of Science or SciELO databases. Their authors have cited FAPESP grant or fellowship project numbers awarded to Principal Investigators or Fellowship Recipients, whether or not they are among the authors. This information is collected automatically and retrieved directly from those bibliometric databases.)

SHINZATO, PATRICK Y.; WOLF, DENIS E.; STILLER, CHRISTOPH; IEEE. Road Terrain Detection: Avoiding Common Obstacle Detection Assumptions Using Sensor Fusion. 2014 IEEE INTELLIGENT VEHICLES SYMPOSIUM PROCEEDINGS, v. N/A, p. 6-pg., 2014-01-01. (10/01305-1, 11/21956-0)

Academic Publications

(References retrieved automatically from State of São Paulo Research Institutions)

SHINZATO, Patrick Yuri. Estimation of obstacles and road area with sparse 3D points. 2015. Doctoral Thesis - Universidade de São Paulo (USP). Instituto de Ciências Matemáticas e de Computação (ICMC/SB) São Carlos.