scholarly journals Calibration and validation of large-scale traffic simulation networks: a case study

2018 ◽  
Vol 130 ◽  
pp. 844-849 ◽  
Author(s):  
Bekir Bartin ◽  
Kaan Ozbay ◽  
Jingqin Gao ◽  
Abdullah Kurkcu
Author(s):  
Tomer Toledo ◽  
Haris N. Koutsopoulos ◽  
Angus Davol ◽  
Moshe E. Ben-Akiva ◽  
Wilco Burghout ◽  
...  

The calibration and validation approach and results from a case study applying the microscopic traffic simulation tool MITSIMLab to a mixed urban-freeway network in the Brunnsviken area in the north of Stockholm, Sweden, under congested traffic conditions are described. Two important components of the simulator were calibrated: driving behavior models and travel behavior components, including origin–destination flows and the route choice model. In the absence of detailed data, only aggregate data (i.e., speed and flow measurements at sensor locations) were available for calibration. Aggregate calibration uses simulation output, which is a result of the interaction among all components of the simulator. Therefore, it is, in general, impossible to identify the effect of individual models on traffic flow when using aggregate data. The calibration approach used takes these interactions into account by iteratively calibrating the different components to minimize the deviation between observed and simulated measurements. The calibrated MITSIMLab model was validated by comparing observed and simulated measurements: traffic flows at sensor locations, point-to-point travel times, and queue lengths. A second set of measurements, taken a year after the ones used for calibration, was used at this stage. Results of the validation are presented. Practical difficulties and limitations that may arise with application of the calibration and validation approach are discussed.


1996 ◽  
Vol 5 (1) ◽  
pp. 23-32 ◽  
Author(s):  
Chris Halpin ◽  
Barbara Herrmann ◽  
Margaret Whearty

The family described in this article provides an unusual opportunity to relate findings from genetic, histological, electrophysiological, psychophysical, and rehabilitative investigation. Although the total number evaluated is large (49), the known, living affected population is smaller (14), and these are spread from age 20 to age 59. As a result, the findings described above are those of a large-scale case study. Clearly, more data will be available through longitudinal study of the individuals documented in the course of this investigation but, given the slow nature of the progression in this disease, such studies will be undertaken after an interval of several years. The general picture presented to the audiologist who must rehabilitate these cases is that of a progressive cochlear degeneration that affects only thresholds at first, and then rapidly diminishes speech intelligibility. The expected result is that, after normal language development, the patient may accept hearing aids well, encouraged by the support of the family. Performance and satisfaction with the hearing aids is good, until the onset of the speech intelligibility loss, at which time the patient will encounter serious difficulties and may reject hearing aids as unhelpful. As the histological and electrophysiological results indicate, however, the eighth nerve remains viable, especially in the younger affected members, and success with cochlear implantation may be expected. Audiologic counseling efforts are aided by the presence of role models and support from the other affected members of the family. Speech-language pathology services were not considered important by the members of this family since their speech production developed normally and has remained very good. Self-correction of speech was supported by hearing aids and cochlear implants (Case 5’s speech production was documented in Perkell, Lane, Svirsky, & Webster, 1992). These patients received genetic counseling and, due to the high penetrance of the disease, exhibited serious concerns regarding future generations and the hope of a cure.


2008 ◽  
Author(s):  
D. L. McMullin ◽  
A. R. Jacobsen ◽  
D. C. Carvan ◽  
R. J. Gardner ◽  
J. A. Goegan ◽  
...  

Author(s):  
Lori Stahlbrand

This paper traces the partnership between the University of Toronto and the non-profit Local Food Plus (LFP) to bring local sustainable food to its St. George campus. At its launch, the partnership represented the largest purchase of local sustainable food at a Canadian university, as well as LFP’s first foray into supporting institutional procurement of local sustainable food. LFP was founded in 2005 with a vision to foster sustainable local food economies. To this end, LFP developed a certification system and a marketing program that matched certified farmers and processors to buyers. LFP emphasized large-scale purchases by public institutions. Using information from in-depth semi-structured key informant interviews, this paper argues that the LFP project was a disruptive innovation that posed a challenge to many dimensions of the established food system. The LFP case study reveals structural obstacles to operationalizing a local and sustainable food system. These include a lack of mid-sized infrastructure serving local farmers, the domination of a rebate system of purchasing controlled by an oligopolistic foodservice sector, and embedded government support of export agriculture. This case study is an example of praxis, as the author was the founder of LFP, as well as an academic researcher and analyst.


2020 ◽  
Vol 86 (7) ◽  
pp. 12-19
Author(s):  
I. V. Plyushchenko ◽  
D. G. Shakhmatov ◽  
I. A. Rodin

A viral development of statistical data processing, computing capabilities, chromatography-mass spectrometry, and omics technologies (technologies based on the achievements of genomics, transcriptomics, proteomics, metabolomics) in recent decades has not led to formation of a unified protocol for untargeted profiling. Systematic errors reduce the reproducibility and reliability of the obtained results, and at the same time hinder consolidation and analysis of data gained in large-scale multi-day experiments. We propose an algorithm for conducting omics profiling to identify potential markers in the samples of complex composition and present the case study of urine samples obtained from different clinical groups of patients. Profiling was carried out by the method of liquid chromatography mass spectrometry. The markers were selected using methods of multivariate analysis including machine learning and feature selection. Testing of the approach was performed using an independent dataset by clustering and projection on principal components.


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