Real-time partway deadheading strategy based on transit service reliability assessment

2012 ◽  
Vol 46 (8) ◽  
pp. 1265-1279 ◽  
Author(s):  
Bin Yu ◽  
Zhongzhen Yang ◽  
Shan Li
Keyword(s):  
Real Time ◽  
Reliability Assessment ◽  
Service Reliability ◽  
Transit Service

scholarly journals A Dynamic Short-Turning Bus Control for Uncertain Demand

2017 ◽  
Vol 2017 ◽  
pp. 1-9 ◽  
Author(s):  
Hu Zhang ◽  
Shuzhi Zhao ◽  
Huasheng Liu ◽  
Jin Li
Keyword(s):  
Real Time ◽  
Arrival Time ◽  
Uncertain Demand ◽  
Service Reliability ◽  
Real Time Control ◽  
Dynamic Approach ◽  
Short Term ◽  
Total Cost ◽  
Transit Service ◽  
Time Control

This paper formulates a dynamic approach for real-time bus control in uncertain demand. This dynamic approach aims to save the total cost for passengers and operators, while improving transit service reliability. An unfixed rolling horizon was implemented to choose the best dynamic approach. Real-time control predicts two discrete variables (arrival time and bus position) and determines the space-time point of buses. Furthermore, controlled actions include stop skipping and bus holding. The holding time starts when a bus serves a station and depends on previous intervals of passenger boarding and alighting at the station. The stop skipping action allows a bus to skip not only stations with a short-turning exception, but also stations with low demand for boarding that have been alighted in the short-turning segment. Stop skipping and bus holding actions for short-turning service both decrease the travel time of served passengers and the running time of buses, thus improving transit service reliability. A genetic algorithm was applied to solve the problem and the validity of the proposed dynamic approach was tested with four different scenarios. The result of these tests shows that a dynamic short-term bus control can significantly reduce total cost and improve transit service reliability.

Minutes Matter: A Bus Transit Service Reliability Guidebook

2020 ◽  
Author(s):  
◽  
Kari Watkins Carly Queen Simon Berrebi Georgia Institute of Technology ◽  
◽  
◽  
◽  
...  
Keyword(s):  
Service Reliability ◽  
Transit Service ◽  
Bus Transit

Damage Modes and Strength Reliability Strategies of Railway Wheel Set

2010 ◽  
Vol 118-120 ◽  
pp. 80-89 ◽  
Author(s):  
Yong Xiang Zhao ◽  
Bin Zhang
Keyword(s):  
Life Prediction ◽  
Growth Models ◽  
Reliability Assessment ◽  
Damage Analysis ◽  
Service Reliability ◽  
Growth Behaviour ◽  
Railway Wheel ◽  
Professional Societies ◽  
Stable Growth ◽  
Non Destructive

Damage modes, causes, and effects of railway wheel set are investigated from wide production fields. And then, the reliability strategies are classified as service reliability and development reliability. The development one includes design, material and manufacturing, quality approval/authentication, which is a basis of the service one. The service one is the true product quality, which has not only the basis of development reliability but also the effects of non-destructive monitoring level, damage analysis and assessment capacity, and repairing and renewing policies. Reliability of wheel set is so important that a series of code-based regularities have been issued by professional societies or associations. Optimal design is a most effective way to improve wheel set reliability. And in service, non-destructive inspection and repair opportunities are valuable to be synthetically programmed. The critical damage defect/flaw sizes should be scientifically determined. Three advances in strength reliability field should be introduced. They are affordable and appropriate method for reliability assessment and fatigue life prediction including the super long life regime, no-Paris type crack growth models which include crack initiation, stable growth, and approach fracture, and fatigue S-N relation derived from short cracking growth behaviour.

Real-Time Public Transport Operations: Library of Control Strategies

2017 ◽  
Vol 2647 (1) ◽  
pp. 26-32 ◽  
Author(s):  
Mahmood Mahmoodi Nesheli ◽  
Avishai (Avi) Ceder
Keyword(s):  
Real Time ◽  
Public Transport ◽  
Large Scale ◽  
Real Life ◽  
Small Scale ◽  
Control Procedure ◽  
Service Reliability ◽  
Real Time Control ◽  
Time Control ◽  
Control Actions

Modern public transport (PT) operations have evolved into a complex multimodal system in which small-scale disorder can propagate. Large-scale disruptions to passengers and PT agencies result. Various studies have been developed to model PT control at the operational level; however, the main downside of possible real-time control actions is the lack of intelligent modeling and a systematic process that can activate such actions immediately. This study presents a real-time control procedure to increase service reliability and to improve successful coordinated transfers in a complex PT system. The developed method aims at minimizing total travel time for passengers and reducing the uncertainty of meetings between PT vehicles. A library of operational tactics is first built to serve as a basis of the real-time decision-making process. The methodology developed is applied to a real-life case study in Auckland, New Zealand. The results showed improvements in system performance and confirmed the use of real-time control actions to maintain reliable PT service.

scholarly journals Cloud service reliability assessment approach based on multi-valued neutrosophic cross-entropy and entropy measures

Filomat ◽  
2018 ◽  
Vol 32 (8) ◽  
pp. 2793-2812 ◽  
Author(s):  
Yi Wang ◽  
Xiao-Kang Wang ◽  
Jian-Qiang Wang
Keyword(s):  
Decision Making ◽  
Reliability Assessment ◽  
Cloud Service ◽  
Cross Entropy ◽  
Distance Measures ◽  
Service Reliability ◽  
Entropy Measures ◽  
Assessment Approach ◽  
Criteria Weights ◽  
Better Than

Cloud service reliability assessment is a vital decision-making activity for companies and individuals. In this assessment, the evaluation information can be represented by multi-valued neutrosophic numbers (MVNNs). MVNNs are regarded as an integration of single-valued neutrosophic numbers (SVNNs) and hesitant fuzzy numbers (HFNs); therefore, considering the defects of entropy and crossentropy measures for SVNNs and HFNs, we first define a framework of entropy measures and a family of cross-entropy measures for MVNNs in this paper. Second, a novel extended VIKOR (VlseKriterijumska Optimizacija I Kompromisno Resenje) method based on entropy and cross-entropy measures is developed to address the decision-making problems when information about criteria weights is absolutely unknown. Finally, we apply the proposed method to evaluate cloud service reliability; also, a sensitivity analysis and a comparative analysis are made to interpret the practicality and effectiveness of it. The results of analyses verify that the proposed method based on cross-entropy is much better than the methods using general distance measures.

scholarly journals Positive Train Control (PTC): Calculating Benefits and Costs of a New Railroad Control Technology

2010 ◽  
Author(s):  
Randolph R. Resor ◽  
Michael E. Smith ◽  
Pradeep K. Patel
Keyword(s):  
Real Time ◽  
Point Of View ◽  
Class I ◽  
Location Information ◽  
Service Reliability ◽  
Economic Point ◽  
Track Maintenance ◽  
The Road ◽  
Train Control ◽  
Positive Train Control

The purpose of this analysis was to quantify the business benefits of Positive Train Control (PTC) for the Class I freight railroad industry. This report does not address the safety benefits of PTC. These were previously quantified by the Rail Safety Advisory Committee (RSAC), which identified nearly a thousand "PPAs" (PTC-preventable accidents) on U.S. railroads over a 12-year period, and determined the savings to be realized from each avoided accident. The RSAC finding was that avoidance of these PPAs was not, by itself, sufficient (from a strictly economic point of view) to justify an investment in PTC. Examples of potential business benefits include: * Line capacity enhancement * Improved service reliability * Faster over-the-road running times * More efficient use of cars and locomotives (made possible by real-time location information) * Reduction in locomotive failures (due to availability of real-time diagnostics) * Larger "windows" (periods during which no trains operate and maintenance workers can safely occupy the track) for track maintenance (made possible by real-time location information) * Fuel savings This paper presents the results of the analysis. It is important to recognize, however, that the state of the art in making these estimates is not sufficiently mature to make exact answers feasible. Presented here are the best estimates now possible, with observations as to how better information may be developed. Benefits were estimated in the above areas and the cost of deploying PTC on the Class I network (99,000 route miles and 20,000 locomotives) were calculated. The conclusions of the analysis were as follows: * Deployment of PTC on the Class I railroad network (99,000 route miles, 20,000 locomotives) would cost between $2.3 billion and $4.4 billion over five years * Annual benefits, once the system was fully implemented, were estimated at $2.2 billion to $3.8 billion * Internal rate of return was estimated (depending on timing and cost) to be between 44% and 160%

Real-Time Reliability Assessment of Wind Turbine Components Using a Back-Propagation Neural Network and SCADA Data

2021 ◽  
Author(s):  
Shenglei Du ◽  
Jingmei Guo ◽  
Lin Yi ◽  
Chen Zhang ◽  
Shi Liu
Keyword(s):  
Neural Network ◽  
Wind Turbine ◽  
Real Time ◽  
Back Propagation ◽  
Reliability Assessment ◽  
Back Propagation Neural Network ◽  
Condition Assessment ◽  
Assessment Method ◽  
Operating Conditions ◽  
Research Trend

Abstract The high cost of operation and maintenance (O&M) management has become an important factor hindering the sustainable development of the wind power industry. Performing accurate condition assessment of wind turbine components to optimize the structural design and O&M strategy has become a research trend. However, the random and varying operating conditions of wind turbines make this problem difficult and challenging. A Supervisory Control and Data Acquisition (SCADA) system collects signals that contain a large amount of raw and useful information from critical wind turbine sub-assemblies. Extracting key information from the SCADA data is an economical and effective way for condition assessment. A real-time reliability assessment method of wind turbine components using a Back-Propagation Neural Network (BPNN) and SCADA data is presented in this paper. The normal behavior models are established with the processed SCADA data, and the real-time reliability of wind turbine components are assessed based on the prediction result. For verification, the BPNN-based reliability assessment method is applied to a gearbox with real SCADA data of a 1.5MW onshore wind turbine located along the southeast coast of China. The results show the capability of the proposed model in assessing the reliability of wind turbine components continuously and in real time.

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