Development of a Traffic Management Decision Support Tool (DST) for Freeway Incident Traffic Management (FITM) Plan Deployment: Phase-2: An Enhanced DST-2, including I-95, I-495, I-695, I-70, US 29
Chang, G. L., Huang, Y. L., Lu, Y. C., & Lin, Y. T. (2021). Development of a Traffic Management Decision Support Tool (DST) for Freeway Incident Traffic Management (FITM) Plan Deployment: Phase-2: An Enhanced DST-2, including I-95, I-495, I-695, I-70, US 29 (Report No. MD-21-SHA/UM/5-32). University of Maryland (College Park, Md.). https://rosap.ntl.bts.gov/view/dot/60119
Chang, Gang-Len, Yen-Lin Huang, Yi-Chi Lu, and Yi-Ting Lin. Development of a Traffic Management Decision Support Tool (DST) for Freeway Incident Traffic Management (FITM) Plan Deployment: Phase-2: An Enhanced DST-2, including I-95, I-495, I-695, I-70, US 29. Report no. MD-21-SHA/UM/5-32. University of Maryland (College Park, Md.), 2021. https://rosap.ntl.bts.gov/view/dot/60119.
Chang, Gang-Len, et al. Development of a Traffic Management Decision Support Tool (DST) for Freeway Incident Traffic Management (FITM) Plan Deployment: Phase-2: An Enhanced DST-2, including I-95, I-495, I-695, I-70, US 29. University of Maryland (College Park, Md.), 2021, Report no. MD-21-SHA/UM/5-32, ROSA P. https://rosap.ntl.bts.gov/view/dot/60119.
Ground in the development experience of the piloting the Incident Duration Prediction Module (IDPM) for I-95 and its application results, this study further developed IDPMs for I-495, I-695, I-70, and US 29, each with distinguishing traffic patterns and roadway features. Considering the uniquely critical role assumed by I-495 and I-695, respectively, in the Washington and Baltimore regions and their large incident records, the design and construction of these two IDPMs mostly follow the same methodology as with IDPM-I-95. To circumvent the demanding expertise and efforts needed for data quality control and calibration of an IDPM’s prediction rules from many incident records, this study has developed an innovative Transferability Assessment Method (TAM) that allows construction of a new system to take advantage of existing IDPMs’ embedded knowledge. The developed TAM has been adopted for constructing the IDPMs for I-70 and US 29, based on the prediction rules in IDPMs for I-95, I-695, and I-495.
Chang, G. L., Huang, Y. L., Lu, Y. C., & Lin, Y. T. (2021). Development of a Traffic Management Decision Support Tool (DST) for Freeway Incident Traffic Management (FITM) Plan Deployment: Phase-2: An Enhanced DST-2, including I-95, I-495, I-695, I-70, US 29 (Report No. MD-21-SHA/UM/5-32). University of Maryland (College Park, Md.). https://rosap.ntl.bts.gov/view/dot/60119
Chang, Gang-Len, Yen-Lin Huang, Yi-Chi Lu, and Yi-Ting Lin. Development of a Traffic Management Decision Support Tool (DST) for Freeway Incident Traffic Management (FITM) Plan Deployment: Phase-2: An Enhanced DST-2, including I-95, I-495, I-695, I-70, US 29. Report no. MD-21-SHA/UM/5-32. University of Maryland (College Park, Md.), 2021. https://rosap.ntl.bts.gov/view/dot/60119.
Chang, Gang-Len, et al. Development of a Traffic Management Decision Support Tool (DST) for Freeway Incident Traffic Management (FITM) Plan Deployment: Phase-2: An Enhanced DST-2, including I-95, I-495, I-695, I-70, US 29. University of Maryland (College Park, Md.), 2021, Report no. MD-21-SHA/UM/5-32, ROSA P. https://rosap.ntl.bts.gov/view/dot/60119.
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