Autonomous Driving Goes Downtown
IEEE Intelligent Systems
The VISTA Project and Its Applications
IEEE Intelligent Systems
Creating a Digital-Vehicle Proving Ground
IEEE Intelligent Systems
Toward Intelligent Driver-Assistance and Safety Warning Systems
IEEE Intelligent Systems
Ohio State University at the 2004 DARPA Grand Challenge: Developing a Completely Autonomous Vehicle
IEEE Intelligent Systems
IEEE Transactions on Intelligent Transportation Systems
Automatic lateral control for unmanned vehicles via genetic algorithms
Applied Soft Computing
Review: Adaptive cruise control look-ahead system for energy management of vehicles
Expert Systems with Applications: An International Journal
Proceedings of the 4th International ICST Conference on Simulation Tools and Techniques
Modeling and simulation of overtaking behavior involving environment
Advances in Engineering Software
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The automatic-driving field has received much attention in recent years, as exemplified by the Darpa's Grand Challenge. Two Spanish research groups have furthered such work by automating two mass-produced vehicles. As input, their system uses a centimetric global positioning system, wireless LAN support, and artificial vision. To control the vehicle, they use fuzzy logic techniques that contend with both complex mathematical models and inaccurate linearization. Fuzzy logic also lets them incorporate human procedural knowledge into their control algorithms. Here, the researchers describe the algorithms for steering and speed control, which together make up the trajectory control. They also describe algorithms for overtaking, adaptive cruise control with stop-and-go functionality, and vision-based vehicle detection, and discuss results from experiments in real-world conditions.