A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
85th and 98th Percentile Speed Prediction Models of Car, Light, and Heavy Commercial Vehicles for Four-Lane Divided Rural Highways
In this study, the 85th and 98th percentile speed prediction models of car, light, and heavy commercial vehicles for four-lane divided horizontal curves in rural highways were developed using a stepwise multiple linear regression method. In total 10 sites were considered for developing the models and three for validation. Geometric features of horizontal curve and adjacent tangent sections along with vehicle speed at point of curvature and 50 m prior to point of curvature were considered as independent variables. The 85th and 98th percentile speed of car and sport utility vehicle were found to be comparable, and hence combined for further analysis. The 85th percentile speed of commercial vehicles at midcurve were found to be dependent on its speed at preceding section, which was finally predicted based on geometric features considered. For car, it was dependent on curve length and deflection angle. The 98th percentile speed at midcurve of all vehicle types were dependent on its 85th percentile speed. In validation, the root-mean square errors for the developed models were within . The study revealed that curve length could be an important factor in the geometric design procedure.
85th and 98th Percentile Speed Prediction Models of Car, Light, and Heavy Commercial Vehicles for Four-Lane Divided Rural Highways
In this study, the 85th and 98th percentile speed prediction models of car, light, and heavy commercial vehicles for four-lane divided horizontal curves in rural highways were developed using a stepwise multiple linear regression method. In total 10 sites were considered for developing the models and three for validation. Geometric features of horizontal curve and adjacent tangent sections along with vehicle speed at point of curvature and 50 m prior to point of curvature were considered as independent variables. The 85th and 98th percentile speed of car and sport utility vehicle were found to be comparable, and hence combined for further analysis. The 85th percentile speed of commercial vehicles at midcurve were found to be dependent on its speed at preceding section, which was finally predicted based on geometric features considered. For car, it was dependent on curve length and deflection angle. The 98th percentile speed at midcurve of all vehicle types were dependent on its 85th percentile speed. In validation, the root-mean square errors for the developed models were within . The study revealed that curve length could be an important factor in the geometric design procedure.
85th and 98th Percentile Speed Prediction Models of Car, Light, and Heavy Commercial Vehicles for Four-Lane Divided Rural Highways
Maji, Avijit (author) / Sil, Gourab (author) / Tyagi, Ayush (author)
2018-02-16
Article (Journal)
Electronic Resource
Unknown
Neural Network Modeling of 85th Percentile Speed for Two-Lane Rural Highways
| British Library Online Contents | 2012
Modeling the 85th percentile speed on Oklahoma two-lane rural highways via neural network approach
| British Library Conference Proceedings | 2000
Speed characteristics on four-lane divided highways in mixed traffic
| British Library Conference Proceedings | 2008
Operating Speed Prediction Models for Horizontal Curves on Rural Four-Lane Highways
| British Library Online Contents | 2008
A consistent method for rural speed zoning: 85th percentile speed profile vs risk based calculation
| British Library Conference Proceedings | 2006