Investigating the impacts of adverse road-weather conditions on saturation headway

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dc.contributor.authorHirose, Ryutaro
dc.contributor.examiningcommitteeRegehr, Jonathan (Civil Engineering)en_US
dc.contributor.examiningcommitteeSahu, Prasant (Civil Engineering)en_US
dc.contributor.supervisorMehran, Babak
dc.date.accessioned2022-08-23T14:24:42Z
dc.date.available2022-08-23T14:24:42Z
dc.date.copyright2022-08-22
dc.date.issued2022-08-21
dc.date.submitted2022-08-22T03:13:47Zen_US
dc.date.submitted2022-08-22T18:30:52Zen_US
dc.degree.disciplineCivil Engineeringen_US
dc.degree.levelMaster of Science (M.Sc.)en_US
dc.description.abstractAdverse road-weather (RW) conditions may deteriorate traffic operations and safety at intersections due to reduced capacity, frequent collisions, and increased traffic emissions. Weather responsive traffic management (WRTM) can potentially lessen the negative impact of adverse RW conditions. Yet, saturation flow rate (SFR) is a major input for any WRTM that is affected by RW conditions and traffic composition. Few studies investigated the combined effect of adverse RW conditions and heavy vehicle (HV) ratios on the operation of signalized intersections. Additionally, the classic method for measuring SFR estimates the mean of observed flow rates starting from a critical vehicle (CV), i.e., 5th vehicle in the queue per cycle which has several shortcomings including: (1) not considering the probabilistic nature of SFR, (2) ignoring the unsaturated vehicles in the queue i.e., vehicles preceding the CV, and (3) using a particular CV threshold regardless of RW conditions. This thesis investigates saturation headway variations considering RW conditions and HV ratios using the data collected at two busy signalized intersections in Winnipeg, Canada. Regression analysis was used to analyze saturation headways and passenger car equivalent (PCE) factors considering RW conditions. Further, a novel methodology is proposed to model SFR variations using survival analysis that was implemented to explore the stochastic characteristics of SFR considering different CV settings and RW conditions. The findings confirmed that adverse RW conditions can increase the saturation headway significantly e.g., by up to 38.7% for snowy RW conditions. Estimated PCE values under each RW classification and the regression models implied that HVs are less susceptible to adverse RW conditions in terms of their impact on saturation headway. The results from the proposed survival analysis method indicated that adverse RW conditions tend to move the CV position forward to the head of the queue. The findings of this thesis provide a practical method for estimation of SFR at signalized intersections under different adverse RW conditions and contribute to establishment of WRTM strategies to improve the safety and operation of signalized intersections in winter.en_US
dc.description.noteOctober 2022en_US
dc.identifier.urihttp://hdl.handle.net/1993/36729
dc.language.isoengen_US
dc.rightsopen accessen_US
dc.subjectHighway Capacityen_US
dc.subjectSaturation headwayen_US
dc.subjectTrafficen_US
dc.subjectSaturation flow rateen_US
dc.subjectAdverse road weatheren_US
dc.subjectSurvival analysisen_US
dc.titleInvestigating the impacts of adverse road-weather conditions on saturation headwayen_US
dc.typemaster thesisen_US
local.subject.manitobayesen_US
project.funder.identifierhttps://doi.org/10.13039/501100000038en_US
project.funder.nameNatural Sciences and Engineering Research Council of Canadaen_US
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