Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Multiagent Traffic Management: A Reservation-Based Intersection Control Mechanism
AAMAS '04 Proceedings of the Third International Joint Conference on Autonomous Agents and Multiagent Systems - Volume 2
A behavioral multi-agent model for road traffic simulation
Engineering Applications of Artificial Intelligence
A multiagent approach to autonomous intersection management
Journal of Artificial Intelligence Research
Crossroad cooperative driving based on GPS and wireless communications
EUROCAST'07 Proceedings of the 11th international conference on Computer aided systems theory
IEEE Transactions on Intelligent Transportation Systems
Controller for urban intersections based on wireless communications and fuzzy logic
IEEE Transactions on Intelligent Transportation Systems
Genetic fuzzy self-tuning PID controllers for antilock braking systems
Engineering Applications of Artificial Intelligence
Real-time driving danger-level prediction
Engineering Applications of Artificial Intelligence
An adaptive approach to enhanced traffic signal optimization by using soft-computing techniques
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Traffic lights control with adaptive group formation based on swarm intelligence
ANTS'06 Proceedings of the 5th international conference on Ant Colony Optimization and Swarm Intelligence
Cascade Architecture for Lateral Control in Autonomous Vehicles
IEEE Transactions on Intelligent Transportation Systems
Fuzzy decision support system for ship lock control
Expert Systems with Applications: An International Journal
Calibration of microsimulation traffic model using neural network approach
Expert Systems with Applications: An International Journal
Novel Adaptive Charged System Search algorithm for optimal tuning of fuzzy controllers
Expert Systems with Applications: An International Journal
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This paper presents a case study in which an autonomous vehicle must cooperate with a supposedly manually driven one to carry out a cross-roads manoeuvre without risk. The main difference with other intersection systems is that the manual vehicle is driven without paying attention to the controlled one, so a cooperative coordination between vehicles is not possible. In this case is the autonomous vehicle the responsible of adapting its speed to the state of the manually driven, for finalizing the manoeuvre both in a safe and efficient way. For this purpose, a three layer hierarchical fuzzy rule-based system (FRBS) is developed with the aim of dealing with such a situation: the first layer is in charge of detecting the kind of manoeuvre that will be necessary; the second, in the case that an intersection is going to be crossed, is in charge of determining the suitable speed to do so without risk; and the third acts on the vehicle's real speed. The first two layers are implemented by means of fuzzy decision systems, with the second being optimized by a genetic algorithm (GA). The GA evaluates candidates in random simulated scenarios taking into account different factors to calculate the fitness. These factors are: implementing a free collision policy, avoiding unnecessary stops, and terminating the manoeuvre as rapidly as possible.