Despite a large body of research on operating speeds, there is still much to learn about the factors that affect free-flow speeds, especially with regard to the development of a continuous speed profile for two-lane rural highways. This paper presents a new approach to modeling driver speed profile along two-lane rural roads. Speed data regarding individual drivers traveling on selected two-lane rural roads were sampled during a naturalistic experiment that used an onboard Global Positioning System (GPS). GPS devices facilitate the collecting and processing of continuous speed data. Unlike spot speed measurements, which have typically been collected in similar studies, continuous speed data are useful for studying the actual speed profile with regard to acceleration–deceleration behavior and maximum speed on tangents and curves. New variables are used in the regression equation. These variables refer to the horizontal curvature and the vertical grade as weighted values of the geometric features of the alignment preceding and following the vehicle position. To predict the operating speed, the model takes into account the geometric alignment of the road preceding and following the vehicle, as this information is used by drivers to establish the driving task, which is based on memory expectation, vehicle dynamics, and visual perception. The final result is an algorithm for modeling a continuous speed profile without previous assumption of acceleration–deceleration rate and constant speed on tangents and curves.
New Approach to Defining Continuous Speed Profile Models for Two-Lane Rural Roads
CERNI, Gianluca
2012
Abstract
Despite a large body of research on operating speeds, there is still much to learn about the factors that affect free-flow speeds, especially with regard to the development of a continuous speed profile for two-lane rural highways. This paper presents a new approach to modeling driver speed profile along two-lane rural roads. Speed data regarding individual drivers traveling on selected two-lane rural roads were sampled during a naturalistic experiment that used an onboard Global Positioning System (GPS). GPS devices facilitate the collecting and processing of continuous speed data. Unlike spot speed measurements, which have typically been collected in similar studies, continuous speed data are useful for studying the actual speed profile with regard to acceleration–deceleration behavior and maximum speed on tangents and curves. New variables are used in the regression equation. These variables refer to the horizontal curvature and the vertical grade as weighted values of the geometric features of the alignment preceding and following the vehicle position. To predict the operating speed, the model takes into account the geometric alignment of the road preceding and following the vehicle, as this information is used by drivers to establish the driving task, which is based on memory expectation, vehicle dynamics, and visual perception. The final result is an algorithm for modeling a continuous speed profile without previous assumption of acceleration–deceleration rate and constant speed on tangents and curves.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.