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

Dynamic fuzzy logic elevator group control system for energy optimization

High-rise buildings with a considerable number of elevators represent a major logistic problem concerning saving space and time due to economic reasons. For this reason, complex Elevator Group Control Systems are developed in order to manage the elevators properly. Furthermore, the subject of energy is acquiring more and more industrial relevance every day as far as sustainable development is concerned. In this paper, the first entirely dynamic Fuzzy Logic Elevator Group Control System to dispatch landing calls so as to minimize energy consumption, especially during interfloor traffic, is proposed. The fuzzy logic design described here constitutes not only an innovative solution that outperforms usual dispatchers but also an easy, cheap, feasible and reliable solution, which is possible to be implemented in real industry controllers

A particle swarm optimization algorithm for optimal car-call allocation in elevator group control systems

High-rise buildings require the installation of complex elevator group control systems (EGCS). In vertical transportation, when a passenger makes a hall call by pressing a landing call button installed at the floor and located near the cars of the elevator group, the EGCS must allocate one of the cars of the group to the hall call. We develop a Particle Swarm Optimization (PSO) algorithm to deal with this car-call allocation problem. The PSO algorithm is compared to other soft computing techniques such as genetic algorithm and tabu search approaches that have been proved as efficient algorithms for this problem. The proposed PSO algorithm was tested in high-rise buildings from 10 to 24 floors, and several car configurations from 2 to 6 cars. Results from trials show that the proposed PSO algorithm results in better average journey times and computational times compared to genetic and tabu search approaches

A review of multi-car elevator system

This paper presents a review of a new generation of elevator system, the Multi-Car Elevator System. It is an elevator system which contains more than one elevator car in the elevator shaft. In the introduction, it explains why the Multi-Car Elevator System is a new trend elevator system based on its structural design, cost saving and efficiency in elevator system. Different types of Multi-Car Elevator System such as circulation or loop-type, non-circulation and bifurcate circulation are described in section 2. In section 3, researches on dispatch strategies, control strategies and avoidance of car collision strategies of Multi-Car Elevator System since 2002 are reviewed. In the discussion section, it reveals some drawbacks of the Multi-Car Elevator System in transport capability and the risk of car collision. There are recommendations to the future work as well

Design and analysis of a tool for planning and simulating dynamic vertical transport

Nowadays, most of the main companies in the vertical transport industry are researching tools capable of providing support for the design process of elevator systems. Numerous decisions have to be taken to obtain an accurate, comfortable, and high-quality service. Effectively, the optimization algorithm is a key factor in the design process, but so are the number of cars being installed, their technical characteristics, the kinematics of the elevator group, and some other design parameters, which cause the selection task of the elevator system to be a complex one. In this context, the design of decision support tools is becoming a real necessity that most important companies are including as part of their strategic plans. In this article, the authors present a user-friendly planning and simulating tool for dynamic vertical traffic. The tool is conceptualized for giving support in the planning and design stage of the elevator system, in order to collaborate in the selection of the type of elevator (number, type of dynamic, capacity, etc.) and the optimization algorithm

Cyber-Physical Embedded Systems with Transient Supervisory Command and Control: A Framework for Validating Safety Response in Automated Collision Avoidance Systems

The ability to design and engineer complex and dynamical Cyber-Physical Systems (CPS) requires a systematic view that requires a definition of level of automation intent for the system. Since CPS covers a diverse range of systemized implementations of smart and intelligent technologies networked within a system of systems (SoS), the terms “smart” and “intelligent” is frequently used in describing systems that perform complex operations with a reduced need of a human-agent. The difference between this research and most papers in publication on CPS is that most other research focuses on the performance of the CPS rather than on the correctness of its design. However, by using both human and machine agency at different levels of automation, or autonomy, the levels of automation have profound implications and affects to the reliability and safety of the CPS. The human-agent and the machine-agent are in a tidal lock of decision-making using both feedforward and feedback information flows in similar processes, where a transient shift within the level of automation when the CPS is operating can have undesired consequences. As CPS systems become more common, and higher levels of autonomy are embedded within them, the relationship between human-agent and machine-agent also becomes more complex, and the testing methodologies for verification and validation of performance and correctness also become more complex and less clear. A framework then is developed to help the practitioner to understand the difficulties and pitfalls of CPS designs and provides guidance to test engineering design of soft computational systems using combinations of modeling, simulation, and prototyping

The area wide real-time traffic control (ARTC) system : the logical structure and computational algorithms

With the high development of Chinese economy, the number of automobiles rises sharply. In order to let more vehicles pass the limited roads successfully, The Aerawide Real-Time Traffic Control CARTC) System cornes up. Although ARTC has been studied for many years in foreign countries, its study is still in the embryonic stage in China. After investigating, we discovered that system just recently. Only some simple Intelligent transport control has been realized in quite a few cities However, in many large and middle cities, Intelligent transport control is still in a research period. \ud We had been thinking about this research from juniors. We spent one year doing large quantity of social examination, investigating some roads personally and inquiring a lot of material from Internet and library. On the basis of this, we made the road sate model. Several typical states are represented on this model, so it is definitely representative. We chose the comparatively simple and easily operated green wave control. One computer controls six PLC. Long-range control is realized by dialing online the modulator-demodulator. We adopted some basic vague control thought, meanwhile, combined with actual circumstances, and designed a set of practical control algorithm. We mainly used VB6.0 and PLC programmed software from OMRON Company. In the end, we completed the control program of both the upper and lower bit machine. Of course, there are many immature and imperfect aspects in our design, I hope to get guidance and help from all people. \ud ______________________________________________________________________________ \ud MOTS-CLÉS DE L’AUTEUR : ARTC (Aerawide Real-Time Traffic Control), PLC (Programmable Logic Contrllor), ITS (Intelligent Traffic System

CNN-enabled Visual Data Analytics and Intelligent Reasoning for Real-time Optimization and Simulation: An Application to Occupancy-aware Elevator Dispatching Optimization

For most operational systems, the optimization problem is a combinatorial optimization problem, and the optimization performance largely determines the solution quality. Moreover, there exists a trade-off between the computing time of the decision-making process and the optimization performance, which is particularly evident in a system that conducts real-time operations. To obtain better solutions to the decision-making problem in a shorter time, many optimization algorithms are proposed to improve the searching efficiency in the search space. However, information extraction from the environment is also essential for problem-solving. The environment information not only includes the optimization model inputs, but also contains details of the current situation that may change the problem formulation and optimization algorithm parameter values. Due to the time constraint and the computation time of visual processing algorithms, most conventional operational systems collect environment data from sensor platforms but do not analyze image data, which contains situational information that can assist with the decision-making process. To address this issue, this thesis proposes CNN-enabled visual data analytics and intelligent reasoning for real-time optimization, and a closed-loop optimization structure with discrete event simulation to fit the use of situational information in the optimization model. In the proposed operational system, CNNs are used to extract context information from image data, like the type and the number of objects at the scene. Then reasoning techniques and methodologies are applied to deduct knowledge about the current situation to adjust problem formulation and parameter settings. Discrete event simulation is conducted to test the optimization performance of the system, and adjustments can be made to better fit situational information in the optimization process. To validate the feasibility and effectiveness, an application to occupancy-aware elevator dispatching optimization is presented.M.S