Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Factors Contributing to Operating Speeds on Arterial Roads by Context Classifications
The aim of this study was to evaluate and identify the factors influencing operating speed considering context classification. The study focused on three context classifications: C3R–Suburban Residential, C3C–Suburban Commercial, and C4–Urban General. Tobit models were proposed and developed using big data, including traffic and roadway characteristics, land-use attributes, and sociodemographic information. Three years of INRIX speed data were obtained to calculate the 85th-percentile speed. The study proposed an approach to adjust the 85th-percentile speed from INRIX data, given that traffic flow on arterials could be disrupted by signalized intersections. Afterward, empirical analysis was conducted by developing three Tobit models: Generic, C3C/C3R, and C4 models using the adjusted 85th-percentile speed. For the three developed models, several variables [e.g., inside shoulder width, speed limit, and number of signalized intersections per mile (1.609 km)] were found to have significant influence on the 85th-percentile speed. The analysis also revealed potential speed management countermeasures that have significant impact on the 85th-percentile speed which, when implemented, could reduce speed-related crashes and enhance the safety of vulnerable road users.
Factors Contributing to Operating Speeds on Arterial Roads by Context Classifications
The aim of this study was to evaluate and identify the factors influencing operating speed considering context classification. The study focused on three context classifications: C3R–Suburban Residential, C3C–Suburban Commercial, and C4–Urban General. Tobit models were proposed and developed using big data, including traffic and roadway characteristics, land-use attributes, and sociodemographic information. Three years of INRIX speed data were obtained to calculate the 85th-percentile speed. The study proposed an approach to adjust the 85th-percentile speed from INRIX data, given that traffic flow on arterials could be disrupted by signalized intersections. Afterward, empirical analysis was conducted by developing three Tobit models: Generic, C3C/C3R, and C4 models using the adjusted 85th-percentile speed. For the three developed models, several variables [e.g., inside shoulder width, speed limit, and number of signalized intersections per mile (1.609 km)] were found to have significant influence on the 85th-percentile speed. The analysis also revealed potential speed management countermeasures that have significant impact on the 85th-percentile speed which, when implemented, could reduce speed-related crashes and enhance the safety of vulnerable road users.
Factors Contributing to Operating Speeds on Arterial Roads by Context Classifications
Mahmoud, Nada (Autor:in) / Abdel-Aty, Mohamed (Autor:in) / Cai, Qing (Autor:in)
01.06.2021
Aufsatz (Zeitschrift)
Elektronische Ressource
Unbekannt
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