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— This paper presents our approach to TORCS Car Racing Competition 2009, it is based on a complete modular architecture capable of driving automatically a car along a track with or without oppents. The architecture is composed of five simple modules being each one responsible for a basic aspect of car driving. The modules control gear shiftings, steer(More)
−Reducing the number of traffic accidents is a declared target of most governments. Since dependence on driver reaction is the main cause of road accidents, it would be advisable to replace the human factor in some driving-related tasks with automated solutions. In order to automate a vehicle it is necessary to control the actuators of a car, i.e., the(More)
First, we describe the competition regulations and the software framework. Then, the five best teams describe the methods of computational intelligence they used to develop their drivers and the lessons they learned from the participation in the championship. The organizers provide short summaries of the other competitors. Finally, we summarize the(More)
—Research on intelligent transport systems (ITSs) is steadily leading to safer and more comfortable control for vehicles. Systems that permit longitudinal control have already been implemented in commercial vehicles, acting on throttle and brake. Nevertheless, lateral control applications are less common in the market. Since a too-sudden turn of the(More)
— Computer systems to carry out control algorithms on autonomous vehicles have been developed in recent years. However, the advances in peripheral devices allow connecting the actuator controllers to the control system by means of standard communication links (USB, CAN, Ethernet…).The goal is to permit the use of standard computers. In this paper, we(More)
In this paper, a new multiple population based meta-heuristic to solve combinatorial optimization problems is introduced. This meta-heuristic is called Golden Ball (GB), and it is based on soccer concepts. To prove the quality of our technique, we compare its results with the results obtained by two different Genetic Algorithms (GA), and two Distributed(More)
We propose a multi-crossover and adaptive island based population algorithm (MAIPA). This technique divides the entire population into subpopulations, or demes, each with a different crossover function, which can be switched according to the efficiency. In addition, MAIPA reverses the philosophy of conventional genetic algorithms. It gives priority to the(More)