Evaluating the HERO Ramp-Metering Algorithm with San Diego’s Integrated Corridor Management System Model

2019 ◽  
Vol 2673 (12) ◽  
pp. 354-366
Author(s):  
François Bélisle ◽  
Laura Torres ◽  
Pascal Volet ◽  
David K. Hale ◽  
Anjana Avr
Keyword(s):  
Management System ◽  
Ramp Metering ◽  
System Model ◽  
Peak Period ◽  
Original Algorithm ◽  
Average Travel Time ◽  
Base Scenario ◽  
Freeway Bottlenecks ◽  
Alternative Designs ◽  
Measures Of Performance

The FHWA project “Alternative Designs to Alleviate Freeway Bottlenecks at Merge/Diverge and Weaving Areas” aims at evaluating six different methods to mitigate merge impacts. In this paper, the following ramp-metering algorithms were tested: HEuristic Ramp metering coOrdination (HERO), Asservissement Linéaire d’entrée sur Autoroute (ALINEA), and San Diego Ramp Meter System (SDRMS). These were compared with a “do-nothing” base scenario. The algorithms were tested during a 5 h morning peak period simulation using the integrated corridor management system (ICMS) Aimsun network, a complete and wide-ranging network covering San Diego’s I-15 mainline corridor, on-off ramps and arterial roads. Whereas ALINEA is already included in the base distribution of Aimsun, a new implementation of HERO was programmed from algorithms found in the literature and adapted for use on such a network. Different measures of performance (MOP) were used to assess the efficiency of each algorithm and HERO was found to outperform all the other algorithms: gains of 1.5% over ALINEA and 4% over do-nothing on the mainline average travel time, and gains of 0.5% over ALINEA and 1.5% over do-nothing for the average weighted harmonic speed on all mainline and ramp sections. However, although tests showed that better results can be obtained on the mainline, careful calibration was needed to attain overall positive MOP and not penalize vehicles entering on ramps. The paper concludes with proposed improvements to the original algorithm.

New approaches to improving enterprise management systems using international models and standards in a digital transformation environment

2020 ◽  
pp. 24-29
Author(s):  
V.V. Silaeva ◽  
◽  
V.P. Semenov ◽  
Keyword(s):  
Management System ◽  
Integrated Management ◽  
Digital Transformation ◽  
International Standards ◽  
System Model ◽  
Management Systems ◽  
Enterprise Management ◽  
Integrated Management System ◽  
New Approaches ◽  
Iso 31000

The relevance of creating integrated management systems for enterprises in a digital transformation environment is proved. New approaches to improving the management system in accordance with the new European excellence model (EFQM 2020) and international standards for achieving sustainable success and risk management are described. Approach to the development of integrated management system model based on the new EFQM 2020 model and international standards such as ISO 9004:2018 and ISO 31000:2018 is offered.

L1 Adaptive Control for Aircraft Air Management System Pressure-Regulating Bleed Valve

2017 ◽  
Vol 139 (12) ◽  
Author(s):  
John Cooper ◽  
Chengyu Cao ◽  
Jiong Tang
Keyword(s):  
Management System ◽  
Control Valve ◽  
Pressure Control ◽  
Adaptive Controller ◽  
System Model ◽  
Flow Control Valve ◽  
L1 Adaptive Control ◽  
System Pressure ◽  
L1 Adaptive Controller ◽  
Linear Controllers

This paper presents an L1 adaptive controller for pressure control using an engine bleed valve in an aircraft air management system (AMS). The air management system is composed of two pressure-regulating bleed valves, a temperature control valve, a flow control valve, and a heat exchanger/precooler. Valve hysteresis due to backlash and dry friction is included in the system model. The nonlinearities involved in the system cause oscillations under linear controllers, which decrease component life. This paper is the unique in the consideration of these uncertainties for control design. This paper presents simulation results using the adaptive controller and compares them to those using a proportional–integral (PI) controller.

Integrated management system model for organization based on quality management and lean production technologies

2021 ◽  
pp. 20-24
Author(s):  
V.V. Silaeva ◽  
◽  
V.P. Semenov ◽  
Keyword(s):  
Quality Management ◽  
Management System ◽  
Integrated Management ◽  
Lean Production ◽  
System Model ◽  
Integrated Management System ◽  
Value Stream ◽  
Model Based ◽  
Production Technologies

The article describes managing the processes of an organization as managing a holistic entity through the characteristics of the value stream. At the same time, the value stream is an activity aimed at creating the value for customer, which is implemented through a system of interconnected processes/operations. The article demonstrates the possibilities of integrating the modern models, standards, methods and tools for quality management and lean production into the processes of an organization in order to achieve the aims. Integrated management system model based on quality management and lean production technologies is presented.

scholarly journals Application Research of Key Frames Extraction Technology Combined with Optimized Faster R-CNN Algorithm in Traffic Video Analysis

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Zhi-guang Jiang ◽  
Xiao-tian Shi
Keyword(s):  
Video Analysis ◽  
Management System ◽  
Large Scale ◽  
Data Communication ◽  
Transportation System ◽  
Extraction Technology ◽  
Transportation Management ◽  
Key Frame Extraction ◽  
Original Algorithm ◽  
Key Frame

The intelligent transportation system under the big data environment is the development direction of the future transportation system. It effectively integrates advanced information technology, data communication transmission technology, electronic sensing technology, control technology, and computer technology and applies them to the entire ground transportation management system to establish a real-time, accurate, and efficient comprehensive transportation management system that works on a large scale and in all directions. Intelligent video analysis is an important part of smart transportation. In order to improve the accuracy and time efficiency of video retrieval schemes and recognition schemes, this article firstly proposes a segmentation and key frame extraction method for video behavior recognition, using a multi-time scale dual-stream network to extract video features, improving the efficiency and efficiency of video behavior detection. On this basis, an improved algorithm for vehicle detection based on Faster R-CNN is proposed, and the Faster R-CNN network feature extraction layer is improved by using the principle of residual network, and a hole convolution is added to the network to filter out the redundant features of high-resolution video images to improve the problem of vehicle missed detection in the original algorithm. The experimental results show that the key frame extraction technology combined with the optimized Faster R-CNN algorithm model greatly improves the accuracy of detection and reduces the leakage. The detection rate is satisfactory.

scholarly journals The energy policy risk management system model: theories and practices

2020 ◽  
Vol 23 (4) ◽  
pp. 33-48
Author(s):  
Iryna Nyenno ◽  
Natalia Selivanova ◽  
Natalya Korolenko ◽  
Vyacheslav Truba
Keyword(s):  
Risk Management ◽  
Energy Policy ◽  
Management System ◽  
System Model ◽  
Risk Management System ◽  
Policy Risk
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