Statistical evaluation of data requirement for ramp metering performance assessment. (November 2020)
- Record Type:
- Journal Article
- Title:
- Statistical evaluation of data requirement for ramp metering performance assessment. (November 2020)
- Main Title:
- Statistical evaluation of data requirement for ramp metering performance assessment
- Authors:
- Ma, Xiaobo
Karimpour, Abolfazl
Wu, Yao-Jan - Abstract:
- Highlights: Examine how much data is enough for before and after studies. Proposed a non-parametric statistic approach for ramp metering evaluation procedure. Two-month is the minimum data collection period for robust ramp metering evaluation. Proposed a methodology that only considers a few assumptions. Abstract: Ramp metering is known to be an effective freeway control measure that ensures the overall efficiency and safety of a highway system by regulating the inflow traffic on-ramps. Therefore, agencies are required to frequently assess the performance of their ramp meters. However, one major challenge for the agencies conducting ramp metering performance assessments is the lack of knowledge about data requirements. Data requirements consist of the information regarding the duration of data collection for accommodation time (the time needed for the users to get familiar with the change) and for the evaluation time. In this paper, a non-parametric statistic approach is proposed that is robust to the underlying distribution of the random variable. Meaning that the accuracy of the model is insensitive to the data distribution. For validation purposes, three active ramps along State Route 51, in the Phoenix Metropolitan area, Arizona are selected as the case study. ADOT altered their ramp control strategy from fixed-time to responsive control and is attempting to know the extent of data required for assessing its new ramp metering strategy. For this particular case study, theHighlights: Examine how much data is enough for before and after studies. Proposed a non-parametric statistic approach for ramp metering evaluation procedure. Two-month is the minimum data collection period for robust ramp metering evaluation. Proposed a methodology that only considers a few assumptions. Abstract: Ramp metering is known to be an effective freeway control measure that ensures the overall efficiency and safety of a highway system by regulating the inflow traffic on-ramps. Therefore, agencies are required to frequently assess the performance of their ramp meters. However, one major challenge for the agencies conducting ramp metering performance assessments is the lack of knowledge about data requirements. Data requirements consist of the information regarding the duration of data collection for accommodation time (the time needed for the users to get familiar with the change) and for the evaluation time. In this paper, a non-parametric statistic approach is proposed that is robust to the underlying distribution of the random variable. Meaning that the accuracy of the model is insensitive to the data distribution. For validation purposes, three active ramps along State Route 51, in the Phoenix Metropolitan area, Arizona are selected as the case study. ADOT altered their ramp control strategy from fixed-time to responsive control and is attempting to know the extent of data required for assessing its new ramp metering strategy. For this particular case study, the results suggest that two months' worth of data is the minimum data sufficient for a ramp metering assessment. The proposed assessment approach can be transferred to other ramp metering applications to help traffic engineers efficiently tune up ramp metering strategies. … (more)
- Is Part Of:
- Transportation research. Volume 141(2020)
- Journal:
- Transportation research
- Issue:
- Volume 141(2020)
- Issue Display:
- Volume 141, Issue 2020 (2020)
- Year:
- 2020
- Volume:
- 141
- Issue:
- 2020
- Issue Sort Value:
- 2020-0141-2020-0000
- Page Start:
- 248
- Page End:
- 261
- Publication Date:
- 2020-11
- Subjects:
- Ramp metering -- Evaluation -- Data requirement -- Ramp performance
Transportation -- Research -- Periodicals
388.011 - Journal URLs:
- http://www.sciencedirect.com/science/journal/09658564 ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.tra.2020.09.011 ↗
- Languages:
- English
- ISSNs:
- 0965-8564
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 9026.274604
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British Library HMNTS - ELD Digital store - Ingest File:
- 14735.xml