A Fuzzy Logic Inference Approach for the Estimation of the Passengers Flow Demand

This paper presents a new approach that designs the flow of passengers in mass transportation systems in presence of uncertainties. One of the techniques used for the prediction of passenger demand is the origin- destination matrices. However, this method is limited to urban areas and rarely to explicit stations. Otherwise, the gravity models based on friction functions can be another alternative; however, it is difficult to fit into practical achievements. Another solution might be the application of artificial intelligence techniques so as to include some intuitive knowledge provided by an expert to predict the flow demand of passengers’ trips in explicit stations. This paper proposes to combine a matrix of origin-destination trips of travel zones, with the intuitive knowledge, applying a fuzzy logic inference approach.This paper presents a new approach that designs the flow of passengers in mass transportation systems in presence of uncertainties. One of the techniques used for the prediction of passenger demand is the origin- destination matrices. However, this method is limited to urban areas and rarely to explicit stations. Otherwise, the gravity models based on friction functions can be another alternative; however, it is difficult to fit into practical achievements. Another solution might be the application of artificial intelligence techniques so as to include some intuitive knowledge provided by an expert to predict the flow demand of passengers’ trips in explicit stations. This paper proposes to combine a matrix of origin-destination trips of travel zones, with the intuitive knowledge, applying a fuzzy logic inference approach

A Fuzzy Logic-Based Approach for Estimation of Dwelling Times of Panama Metro Stations

Passenger flow modeling and station dwelling time estimation are significant elements for railway mass transit planning, but system operators usually have limited information to model the passenger flow. In this paper, an artificial-intelligence technique known as fuzzy logic is applied for the estimation of the elements of the origin-destination matrix and the dwelling time of stations in a railway transport system. The fuzzy inference engine used in the algorithm is based in the principle of maximum entropy. The approach considers passengers’ preferences to assign a level of congestion in each car of the train in function of the properties of the station platforms. This approach is implemented to estimate the passenger flow and dwelling times of the recently opened Line 1 of the Panama Metro. The dwelling times obtained from the simulation are compared to real measurements to validate the approach.The authors of this paper want to express their gratitude to the National Secretary of Science and Technology (SENACYT) of the Government of the Republic of Panama for funding this study through the R & D project (MDEPRB09-001). Additionally, they want to thank the support received from Technological University of Panama (UTP), the University of Granada, the Fundación Carolina and the Secretaría del Metro de Panamá (SMP)

Improving the Efficiencies of Elevator Systems Using Fuzzy Logic

This research presents the application of fuzzy logic in elevators. This analyzes the features of elevators and how fuzzy logiccould be used to minimize the waiting time, detect when the temperature is high for the car, and determine which floor hashighest number of people waiting for the car. High rising building is a common sight in most of the cities today. Fast andefficient elevator transportation is a key feature when creating these kinds of buildings. As the complexity of a systemincreases, it becomes more difficult and eventually impossible to make a precise statement about its behaviour. Many of thesystems build before fuzzy logic use trial and error and effort had to be done over and over to arrive at effective control.Fuzzy logic concepts are used to enable the elevator control system to make decisions. The design criteria include ofoptimizing movement of elevators with regard to several factors such as waiting time, riding time, energy, load, etc.Software simulation is done in order to capture the performance of the proposed system which is compared to conventionalapproaches.Keywords: Fuzzy logic (FL), Elevator. Car, Software simulation

Vertical transportation in buildings

Nowadays, the building industry and its associated technologies are experiencing a period of rapid growth, which requires an equivalent growth regarding technologies in the field of vertical transportation. Therefore, the installation of synchronised elevator groups in modern buildings is a common practice in order to govern the dispatching, allocation and movement of the cars shaping the group. So, elevator control and management has become a major field of application for Artificial Intelligence approaches. Methodologies such as fuzzy logic, artificial neural networks, genetic algorithms, ant colonies, or multiagent systems are being successfully proposed in the scientific literature, and are being adopted by the leading elevator companies as elements that differentiate them from their competitors. In this sense, the most relevant companies are adopting strategies based on the protection of their discoveries and inventions as registered patents in different countries throughout the world. This paper presents a comprehensive state of the art of the most relevant recent patents on computer science applied to vertical transportationConsejería de Innovación, Ciencia y Empresa, Junta de Andalucía P07-TEP-02832, Spain