Active traffic management case study: phase 1 : final report.

Details

• Creators:
  Sharma, Anuj ; Wang, Shuo ; Khattak, Aemal J.
• Corporate Creators:
  Iowa State University ; Iowa State University. Institute for Transportation ; Iowa State University. Department of Civil, Construction and Environmental Engineering ; University of Nebraska--Lincoln. Dept. of Civil Engineering
• Corporate Contributors:
  Nebraska. Dept. of Roads
• Subject/TRT Terms:
  • Case studies
  • Costs
  • Crash risk forecasting
  • Feasibility analysis
  • Probits
  • Ramp metering
  • Sensitivity analysis
  • Travel time
  • Urban highways
• Publication/ Report Number:
  SPR-P1(14) M007
• Resource Type:
  Tech Report
• Geographical Coverage:
  United States;Nebraska
• Edition:
  Final report
• Corporate Publisher:
  Nebraska. Dept. of Roads
• Abstract:
  This study developed a systematic approach for using data from multiple sources to provide active traffic management ; solutions. The feasibility of two active traffic management solutions is analyzed in this report: ramp-metering and real-time ; crash risk estimation and prediction. Using a combined dataset containing traffic, weather, and crash data, this study ; assessed crash likelihood on urban freeways and evaluated the economic feasibility of providing a ramp metering solution. ; A case study of freeway segments in Omaha, Nebraska, was conducted. The impact of rain, snow, congestion, and other ; factors on crash risk was analyzed using a binary probit model, and one of the major findings from the sensitivity analysis ; was that a one-mile-per-hour increase in speed is associated with a 7.5% decrease in crash risk. ; FREEVAL was used to analyze the economic feasibility of the ramp metering implementation strategy. A case study of a ; 6.3 mile segment on I-80 near downtown Omaha showed that, after applying ramp metering, travel time decreased from ; 9.3 minutes to 8.1 minutes and crash risk decreased by 37.5% during the rush hours. The benefits of reducing travel time ; and crash cost can easily offset the cost of implementing ramp metering for this road section. ; The results from the real-time crash risk prediction models developed for the studied road section are promising. A ; sensitivity analysis was conducted on different models and different temporal and spatial windows to estimate/predict crash ; risk. An adaptive boosting (AdaBoost) model using a 10 minute historical window of speeds obtained from 0.25 miles ; downstream and 0.75 miles upstream was found to be the most accurate estimator of crash risk.
  More +
• Format:
  PDF
• Download URL:
  https://rosap.ntl.bts.gov/view/dot/31121/dot_31121_DS1.pdf
• File Type:
  [PDF - 5.22 MB]
• Collection(s):
  US Transportation Collection
• Main Document Checksum:
  urn:sha-512:30b84880f2eb853f008534e406bd113530057e819961479c77c1c50587986a726a09e5430a34740415404564dce5856399800db5ba62cb551182d7dd1b4f7533