Advanced methodologies in dynamic traffic assignment modeling of managed lanes

Managed lane strategies are innovative road operation schemes for addressing congestion problems. These strategies operate a lane (lanes) adjacent to a freeway that provides congestion-free trips to eligible users, such as transit or toll-payers. To ensure the successful implementation of managed lanes, the demand on these lanes need to be accurately estimated. Among different approaches for predicting this demand, the four-step demand forecasting process is most common. Managed lane demand is usually estimated at the assignment step. Therefore, the key to reliably estimating the demand is the utilization of effective assignment modeling processes. ^ Managed lanes are particularly effective when the road is functioning at near-capacity. Therefore, capturing variations in demand and network attributes and performance is crucial for their modeling, monitoring and operation. As a result, traditional modeling approaches, such as those used in static traffic assignment of demand forecasting models, fail to correctly predict the managed lane demand and the associated system performance. The present study demonstrates the power of the more advanced modeling approach of dynamic traffic assignment (DTA), as well as the shortcomings of conventional approaches, when used to model managed lanes in congested environments. In addition, the study develops processes to support an effective utilization of DTA to model managed lane operations. ^ Static and dynamic traffic assignments consist of demand, network, and route choice model components that need to be calibrated. These components interact with each other, and an iterative method for calibrating them is needed. In this study, an effective standalone framework that combines static demand estimation and dynamic traffic assignment has been developed to replicate real-world traffic conditions. ^ With advances in traffic surveillance technologies collecting, archiving, and analyzing traffic data is becoming more accessible and affordable. The present study shows how data from multiple sources can be integrated, validated, and best used in different stages of modeling and calibration of managed lanes. Extensive and careful processing of demand, traffic, and toll data, as well as proper definition of performance measures, result in a calibrated and stable model, which closely replicates real-world congestion patterns, and can reasonably respond to perturbations in network and demand properties.^

Advanced Methodologies in Dynamic Traffic Assignment Modeling of Managed Lanes

Managed lane strategies are innovative road operation schemes for addressing congestion problems. These strategies operate a lane (lanes) adjacent to a freeway that provides congestion-free trips to eligible users, such as transit or toll-payers. To ensure the successful implementation of managed lanes, the demand on these lanes need to be accurately estimated. Among different approaches for predicting this demand, the four-step demand forecasting process is most common. Managed lane demand is usually estimated at the assignment step. Therefore, the key to reliably estimating the demand is the utilization of effective assignment modeling processes. Managed lanes are particularly effective when the road is functioning at near-capacity. Therefore, capturing variations in demand and network attributes and performance is crucial for their modeling, monitoring and operation. As a result, traditional modeling approaches, such as those used in static traffic assignment of demand forecasting models, fail to correctly predict the managed lane demand and the associated system performance. The present study demonstrates the power of the more advanced modeling approach of dynamic traffic assignment (DTA), as well as the shortcomings of conventional approaches, when used to model managed lanes in congested environments. In addition, the study develops processes to support an effective utilization of DTA to model managed lane operations. Static and dynamic traffic assignments consist of demand, network, and route choice model components that need to be calibrated. These components interact with each other, and an iterative method for calibrating them is needed. In this study, an effective standalone framework that combines static demand estimation and dynamic traffic assignment has been developed to replicate real-world traffic conditions. With advances in traffic surveillance technologies collecting, archiving, and analyzing traffic data is becoming more accessible and affordable. The present study shows how data from multiple sources can be integrated, validated, and best used in different stages of modeling and calibration of managed lanes. Extensive and careful processing of demand, traffic, and toll data, as well as proper definition of performance measures, result in a calibrated and stable model, which closely replicates real-world congestion patterns, and can reasonably respond to perturbations in network and demand properties.

Tactical sourcing, fast lane for medium value purchases

Medium value purchases make up a vast portion of organisations’ purchases. Medium value purchases differ from large purchases that the purchases value is smaller and quantity higher. They are not managed efficiently if they are managed as large purchases. However, they should not be managed as small purchases as they have savings possibilities that are not obtained with a process that is designed for small purchases. This study offers a solution for medium value spend management. The solution is tactical sourcing. The tactical sourcing is designed for Tieto Corporation’s need and it was influenced by Six Sigma methods and tools.

Immatures of tapuruia Felisbertoi Lane, 1973 (Cerambycidae, Cerambycinae, Hexoplonini)

The larva and pupa of Tapuruia felisbertoi Lane, 1973, collected in Hevea brasiliensis (Euphorbiaceae) in Mato Grosso, Brazil, are described and illustrated. Biological data and a comparison with the larvae of other Hexoplonini species are also presented.

Long-term nutritional assessment of patients with severe short bowel syndrome managed with home enteral nutrition and oral intake

Background: Parenteral nutrition (PN) is used to control the nutritional state after severe intestinal resections. Whenever possible, enteral nutrition (EN) is used to promote intestinal rehabilitation and reduce PN dependency. Our aim is to verify whether EN + oral intake (01) in severe short bowel syndrome (SBS) surgical adult patients can maintain adequate nutritional status in the long term. Methods: This longitudinal retrospective study included 10 patients followed for 7 post-operative years. Body mass index (BMI), percentage of involuntary loss of usual body weight (UWL), free fat mass (FFM), and fat mass (FM) composition assessed by bioelectric impedance, and laboratory tests were evaluated at 6, 12, 24, 36, 48, 60, 72, and 84 months after surgery. Energy and protein offered in HPN and at long term by HEN+ oral intake (01), was evaluated at the same periods. The statistical model of generalized estimating equations with p <0,05 was used. Results: With long term EN + 01 there was a progressive increase in the UWL, a decrease in BMI, FFM, and FM (p < 0,05). PN weaning was possible in eight patients. Infection due to central venous catheter (CVC) contamination was the most common complication (1.2 episodes CVC/patient/year). There was an increase in energy and protein intake supply provided by HEN+OI (p <0.05). All patients survived for at least 2 years, seven for 5 years and six for 7 years of follow-up. Conclusions: In the long term SBS surgical adult patients fed with HEN+OI couldn`t maintain adequate nutritional status with loss of FM and FFM. (Nutr Hosp. 2011;26:834-842) DOI:10.3305/nh.2011.26.4.5153

Use of GnRH agonist implants for long-term suppression of fertility in extensively managed heifers and cows

The ability of gonadotrophin releasing hormone (GnRH) agonist implants to suppress ovarian activity and prevent pregnancies, long-term, was examined in heifers and cows maintained under extensive management. At three cattle stations, heifers (2-year-old) and older cows (3- to 16-year-old) were assigned to a control group that received no treatment, or were treated with high-dose (12 mg, Station A) or low-dose (8 mg, Station B and Station Q GnRH agonist implants. The respective numbers of control and GnRH agonist-treated animals (heifers + cows) at each station were: Station A, 20 and 99; Station B, 19 and 89; Station C, 20 and 76. Animals were maintained with 4% bulls and monitored for pregnancy at 2-monthly intervals for approximately 12 months. Pregnancy rates for control heifers and control cows ranged from 60-90% and 80-100%, respectively, depending on the study site. The respective number of animals (heifers + cows) treated with GnRH agonist that conceived, and days to first conception, were: Station A, 9 (9%) and 336 3 days; Station B, 8 (10%) and 244 +/- 13 days; Station C, 20 (26%) and 231 +/- 3 days. Treatment with high-dose GnRH agonist prevented pregnancies for longer (similar to300 days) than treatment with low-dose GnRH agonist (similar to200 days). In the majority of heifers and cows treated with GnRH agonist, ovarian follicular growth was restricted to early antral follicles (2-4 mm). The findings indicate that GnRH agonist implants have considerable potential as a practical technology to suppress ovarian activity and control reproduction in female cattle maintained in extensive rangelands environments. The technology also has broader applications in diverse cattle production systems. (C) 2002 Elsevier Science B.V. All rights reserved.

Energy resource scheduling in a real distribution network managed by several virtual power players

Smart Grids (SGs) appeared as the new paradigm for power system management and operation, being designed to integrate large amounts of distributed energy resources. This new paradigm requires a more efficient Energy Resource Management (ERM) and, simultaneously, makes this a more complex problem, due to the intensive use of distributed energy resources (DER), such as distributed generation, active consumers with demand response contracts, and storage units. This paper presents a methodology to address the energy resource scheduling, considering an intensive use of distributed generation and demand response contracts. A case study of a 30 kV real distribution network, including a substation with 6 feeders and 937 buses, is used to demonstrate the effectiveness of the proposed methodology. This network is managed by six virtual power players (VPP) with capability to manage the DER and the distribution network.

Species composition of arbuscular mycorrhizal fungi differ in semi-natural and intensively managed pastures in an isolated oceanic island (Terceira, Azores)

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