Abstract
The main objective of a semaphore is to provide a correct and fluent vehicular mobility. Many countries around the world are using such devices in urban areas. However, the traditional semaphore operative ways are outdated. We report in a previous contribution the development of a methodology capable of improving the vehicular mobility by proposing a new green light interval based on road conditions with a CBR approach. However, this proposal should include whether it is needed to modify such light duration. To do this, the paper proposes the adaptation of an inductive decision tree helping to decide when the semaphore should try to fix the green light interval according to specific road requirements. Some experiments are conducted in a simulated environment to evaluate the pertinence of implementing a decision-making before the CBR methodology. For example, using the ID3 approach the decisions of the system improve almost 8% in a set of 10,000 experiments. Finally, some conclusions are drawn to emphasize the benefits of including this technique in a methodology to implement intelligent semaphores.
Highlights
The decision-making process of human beings is quite complex
We report in a previous contribution the development of a methodology capable of improving the vehicular mobility by proposing a new green light interval based on road conditions with a CBR approach
The results are compared against the performance obtained from the system when it modifies the green light time at all turns of the semaphore cycle
Summary
The decision-making process of human beings is quite complex. Such complexity increases as the amount of information to be considered grows as well as the. Reference [4] proposes a random search through the whole space of attributes in tree building, and they call the resulting model randomly selected decision tree (RSDT). Reference [6] proposes an attribute selection method for nodes on the basis of the concept model of decision trees in purpose of avoiding the heuristic bias of attribute measurement and improving the performance of decision trees. The main conclusion of these works aims to continue the evaluation of studies on three specific subjects: 1) the interaction among autonomous semaphores; 2) the capability of the system to be robust under uncertain data; and 3) the reliability on the semaphore decisions About such statement, the paper argues that the implementation of the support decision technique studied appears to be a suitable and robust way to decide when a semaphore must attempt to change the duration of a green light.
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