Development of a Traffic Management Decision Support Tool for Freeway Incident Traffic Management (FITM) Plan Deployment Phase 3: An Incident Duration and Impact Prediction (IDIP) System
Huang, Y. L., Cheng, Y., & Chang, G. L. (2023). Development of a Traffic Management Decision Support Tool for Freeway Incident Traffic Management (FITM) Plan Deployment Phase 3: An Incident Duration and Impact Prediction (IDIP) System (Report No. MD-22- SHA/UM/6-1). University of Maryland (College Park, Md.). https://rosap.ntl.bts.gov/view/dot/79832
Huang, Yen-Lin, Yao Cheng, and Gang-Len Chang. Development of a Traffic Management Decision Support Tool for Freeway Incident Traffic Management (FITM) Plan Deployment Phase 3: An Incident Duration and Impact Prediction (IDIP) System. Report no. MD-22- SHA/UM/6-1. University of Maryland (College Park, Md.), 2023. https://rosap.ntl.bts.gov/view/dot/79832.
Huang, Yen-Lin, et al. Development of a Traffic Management Decision Support Tool for Freeway Incident Traffic Management (FITM) Plan Deployment Phase 3: An Incident Duration and Impact Prediction (IDIP) System. University of Maryland (College Park, Md.), 2023, Report no. MD-22- SHA/UM/6-1, ROSA P. https://rosap.ntl.bts.gov/view/dot/79832.
This phase of the study has finalized the innovative system for real-time prediction of a detected incident’s duration and its potential traffic impacts on both the subject freeway and its neighboring local streets due to the queues and resulting detouring off-ramp flows. With such information, highway agencies responsible for incident response and traffic management can inform en-route motorists via any advanced traveler information system or public media of the location and time duration over which the freeway segment will be plagued by nonrecurrent congestion queues. Depending on the severity level of the detected incidents and the estimated traffic impacts, responsible traffic agencies can either concurrently or sequentially respond with appropriate strategies.
The primary goal of this study is to finalize the IDIP system’s development so that CHART can reliably project the impacts of a detected incident, fro
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Huang, Y. L., Cheng, Y., & Chang, G. L. (2023). Development of a Traffic Management Decision Support Tool for Freeway Incident Traffic Management (FITM) Plan Deployment Phase 3: An Incident Duration and Impact Prediction (IDIP) System (Report No. MD-22- SHA/UM/6-1). University of Maryland (College Park, Md.). https://rosap.ntl.bts.gov/view/dot/79832
Huang, Yen-Lin, Yao Cheng, and Gang-Len Chang. Development of a Traffic Management Decision Support Tool for Freeway Incident Traffic Management (FITM) Plan Deployment Phase 3: An Incident Duration and Impact Prediction (IDIP) System. Report no. MD-22- SHA/UM/6-1. University of Maryland (College Park, Md.), 2023. https://rosap.ntl.bts.gov/view/dot/79832.
Huang, Yen-Lin, et al. Development of a Traffic Management Decision Support Tool for Freeway Incident Traffic Management (FITM) Plan Deployment Phase 3: An Incident Duration and Impact Prediction (IDIP) System. University of Maryland (College Park, Md.), 2023, Report no. MD-22- SHA/UM/6-1, ROSA P. https://rosap.ntl.bts.gov/view/dot/79832.
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