CARLOS HERNANDO HIGUERA SANDOVAL

RESEARCH INTERESTS

Diseño de estructuras de pavimentos, Evaluación y Rehabilitación de estructuras de pavimentos, Mezclas asfálticas, Caracterización de asfalto, Materiales para carreteras, Mecánica de pavimentos, Modelos de fatiga y ahuellamiento de mezclas asfálticas, Construcción y mantenimiento de carreteras.

Scopus Publications

Multiagent Reinforcement Learning Applied to Traffic Light Signal Control
Carolina Higuera, Fernando Lozano, Edgar Camilo Camacho, and Carlos Hernando Higuera
Springer International Publishing
We present the application of multiagent reinforcement learning to the problem of traffic light signal control to decrease travel time. We model roads as a collection of agents for each signalized junction. Agents learn to set phases that jointly maximize a reward function that encourages short vehicle queuing delays and queue lengths at all junctions. The first approach that we tested exploits the fact that the reward function can be splitted into contributions per agent. Junctions are modeled as vertices in a coordination graph and the joint action is found with the variable elimination algorithm. The second method exploits the principle of locality to compute the best action for an agent as its best response for a two player game with each member of its neighborhood. We apply the learning methods to a simulated network of 6 intersections, using data from the Transit Department of Bogota, Colombia. These methods obtained significant reductions in queuing delay with respect to the fixed time control, and in general achieve shorter travel times across the network than some other reinforcement learning based methods found in the literature.


Demonstration of Multiagent Reinforcement Learning Applied to Traffic Light Signal Control
Carolina Higuera, Fernando Lozano, Edgar Camilo Camacho, and Carlos Hernando Higuera
Springer International Publishing
We present a demonstration of two coordination methods for the application of multiagent reinforcement learning to the problem of traffic light signal control to decrease travel time. The first approach that we tested exploits the fact that the reward function can be splitted into contributions per agent. The second method computes the best response for a two player game with each member of its neighborhood. We apply both learning methods through SUMO traffic simulator, using data from the Transit Department of Bogota, Colombia.


Effect of aging on the properties of asphalt and asphalt mixtures
Carlos Hernando Higuera Sandoval, Xiomara Vanessa Camargo Amaya, and Edwin Alexander Suárez Molano
Editorial Pontificia Universidad Javeriana
This article presents the results of the analysis of the effect of aging on the properties of asphalt and asphalt mixtures. The objective of this study was to compare the properties of the original asphalt and aged asphalt and the dynamic modulus of asphalt mixtures. The long-term aging was simulated by using Pressure Asphalt Vessel (PAV). Marshall and RAMCODES methodologies were used to determine the formula of work; values of dynamic modulus of designed mixtures were obtained by the indirect tensile test, using the Nottingham Asphalt Tester (NAT). The results showed an increase in the rigidity of the aged asphalt. Also, an increase of the stability and a decreased flow in the mixtures made with this type of binder was found. The dynamic modulus values of the mixtures containing aged asphalt showed an increase up to three times compared with those elaborated with original asphalt mixtures.