scholarly journals Multiple User-Class Dynamic Stochastic Assignment for a Route Guidance Strategy

10.5772/9648 ◽  
2010 ◽  
Author(s):  
Yongtaek Lim
Keyword(s):  
Route Guidance ◽  
Multiple User ◽  
Stochastic Assignment ◽  
Dynamic Stochastic ◽  
Class Dynamic

Quasi-Variational Inequality Approach to Multi-User-Class Dynamic Traffic Assignment

2000 ◽  
Vol 1710 (1) ◽  
pp. 11-19 ◽  
Author(s):  
Michiel C. J. Bliemer
Keyword(s):  
Variational Inequality ◽  
Traffic Assignment ◽  
Dynamic Traffic Assignment ◽  
Dynamic Traffic ◽  
Multiple User ◽  
Quasi Variational Inequality ◽  
Important Input ◽  
Class Dynamic ◽  
Link Travel Time ◽  
Modified Projection Method

The extension of a single-user-class macroscopic dynamic traffic assignment model to include multiple user classes is considered. The distinction between user classes is based on vehicle characteristics. Cars and trucks are two typical classes. To deal with various asymmetries that may occur, such as intra-user-class interaction and spatial and temporal asymmetries, the model is specified as a quasi-variational inequality problem. A nested modified projection method is successfully adopted to solve the assignment problem. The solution of the problem depends heavily on the choice of some very important input: the multiclass link travel time functions. Under mild restrictions there exists a solution, which need not be unique. A case study illustrates the model.

Multiclass Dynamic Traffic Assignment Model: Formulation and Computational Experiences

1996 ◽  
Vol 1537 (1) ◽  
pp. 74-82
Author(s):  
Hong K. Lo ◽  
Bin Ran ◽  
Bruce Hongola
Keyword(s):  
Information Systems ◽  
Dynamic Traffic Assignment ◽  
Traffic Information ◽  
Stochastic Dynamic ◽  
Route Guidance ◽  
Modeling Framework ◽  
Solution Quality ◽  
Multiple User ◽  
Real Time Traffic ◽  
The Impact

To model the impact of advanced transportation management and information systems, especially route guidance and other traffic information systems, it is often necessary to develop traffic models that acknowledge the existence of different user classes and that acknowledge that each class may respond to traffic information differently. As a minimum the model should differentiate vehicles that receive real-time traffic information from those that do not. Most existing approaches that incorporate multiple user classes are based on simulation. Although there are advantages of doing so, their main disadvantage is lack of solution quality and property. Recognizing the importance of these, an analytic approach in which the solution properties and quality are well defined is developed. The users are divided into three classes: (a) fixed-route travelers, (b) stochastic dynamic user-optimal, and (c) dynamic user-optimal. The approach defines the property of each class and integrates each into one modeling framework through a variational inequality formulation. Subsequently, a solution algorithm for the formulation is provided and the results of the algorithm are verified through six scenarios.

Plug-in scripts for EFTEM automation

1996 ◽  
Vol 54 ◽  
pp. 546-547
Author(s):  
N. D. Evans ◽  
M. K. Kundmann
Keyword(s):  
Electron Microscopy ◽  
National Laboratory ◽  
Oak Ridge ◽  
Multiple User ◽  
Transmission Electron ◽  
Short Period ◽  
User Facility ◽  
Instrument Control ◽  
And Control ◽  
Research Equipment

Post-column energy-filtered transmission electron microscopy (EFTEM) is inherently challenging as it requires the researcher to setup, align, and control both the microscope and the energy-filter. The software behind an EFTEM system is therefore critical to efficient, day-to-day application of this technique. This is particularly the case in a multiple-user environment such as at the Shared Research Equipment (SHaRE) User Facility at Oak Ridge National Laboratory. Here, visiting researchers, who may oe unfamiliar with the details of EFTEM, need to accomplish as much as possible in a relatively short period of time.We describe here our work in extending the base software of a commercially available EFTEM system in order to automate and streamline particular EFTEM tasks. The EFTEM system used is a Philips CM30 fitted with a Gatan Imaging Filter (GIF). The base software supplied with this system consists primarily of two Macintosh programs and a collection of add-ons (plug-ins) which provide instrument control, imaging, and data analysis facilities needed to perform EFTEM.

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