Steady-State Cornering
Thomas D. Gillespie
- pp 195-236
Reads0
Chats0
About:
The article was published on 1992-01-01 and is currently open access. It has received 1597 citations till now. The article focuses on the topics: Steady state (electronics).read more
Citations
More filters
Journal ArticleDOI
Stanley: The Robot that Won the DARPA Grand Challenge
Sebastian Thrun,Michael Montemerlo,Hendrik Dahlkamp,David Stavens,Andrei Aron,James Diebel,Philip Fong,John Gale,Morgan Halpenny,Gabriel M. Hoffmann,Kenny Lau,Celia M. Oakley,Mark Palatucci,Vaughan R. Pratt,Pascal Stang,Sven Strohband,Cedric Dupont,Lars-Erik Jendrossek,Christian Koelen,Charles Markey,Carlo Rummel,Joe van Niekerk,Eric Jensen,Philippe Alessandrini,Gary Bradski,Bob Davies,Scott M. Ettinger,Adrian Kaehler,Ara V. Nefian,Pamela Mahoney +29 more
TL;DR: The robot Stanley, which won the 2005 DARPA Grand Challenge, was developed for high‐speed desert driving without manual intervention and relied predominately on state‐of‐the‐art artificial intelligence technologies, such as machine learning and probabilistic reasoning.
Proceedings ArticleDOI
Towards fully autonomous driving: Systems and algorithms
Jesse Levinson,Jake Askeland,Jan Becker,Jennifer Dolson,David Held,Soeren Kammel,J. Zico Kolter,Dirk Langer,Oliver Pink,Vaughan R. Pratt,Michael Sokolsky,Ganymed Stanek,David Stavens,Alex Teichman,Moritz Werling,Sebastian Thrun +15 more
TL;DR: In order to achieve autonomous operation of a vehicle in urban situations with unpredictable traffic, several realtime systems must interoperate, including environment perception, localization, planning, and control.
Journal ArticleDOI
Real-Time Motion Planning With Applications to Autonomous Urban Driving
TL;DR: The proposed algorithm was at the core of the planning and control software for Team MIT's entry for the 2007 DARPA Urban Challenge, where the vehicle demonstrated the ability to complete a 60 mile simulated military supply mission, while safely interacting with other autonomous and human driven vehicles.
Journal ArticleDOI
ADVISOR 2.1: a user-friendly advanced powertrain simulation using a combined backward/forward approach
TL;DR: ADVISOR 2.1 as mentioned in this paper is the latest version of the National Renewable Energy Laboratory's advanced vehicle simulator, which is designed to be accurate, fast, flexible, easily sharable, and easy to use.
Journal ArticleDOI
Predictive Cruise Control: Utilizing Upcoming Traffic Signal Information for Improving Fuel Economy and Reducing Trip Time
B Asadi,Ardalan Vahidi +1 more
TL;DR: An optimization-based control algorithm is formulated that uses short range radar and traffic signal information predictively to schedule an optimum velocity trajectory for the vehicle to reduce idle time at stop lights and fuel consumption.