Operating Speed as a Key Factor in Studying the Driver Behaviour in a Rural Context

Abstract

The research aims to explore the effects of geometric road features on driver speed behaviour in order to identify unsafe road segments where high reductions in speed between successive road elements occur. The sample involves two-lane rural roads on flat terrain (vertical grade less than 5%) in Southern Italy, totalling 184 km without spiral transition curves between the tangent segments and circular elements. The testing was carried out on 567 study sites, of which 248 are on circular curves and 319 on tangents. Speed data collection was carried out in environmental and traffic conditions using a laser. The conditions were the following: dry roads, free flow conditions, daylight hours and good weather conditions. The main goal was to calibrate and validate different operating speed prediction models: a) one model on tangent segments; b) one model on circular curves; c) only one model to be used at the same time on tangents and circular curves. The validation process involved almost 10% of the total road network length, that was removed from the calibration phase. The speed measurements of each of the first two datasets (a, b) were grouped into ten homogeneous substrates while for the remaining dataset (c) sixteen substrates were defined by using a hard c-means algorithm. Two statistical criteria were used to remove anomalous operating speed values from each group of three datasets, namely, the Chauvenet criterion and the Vivatrat method. The first criterion was preferred in the final process of model selection. The results of the first filtering procedure showed more homogeneous samples that guaranteed a higher correlation coefficient and lower residuals of the predictive models during the validation phase than the Vivatrat method. The models were developed using an Ordinary Least Squares (OLS) method. The explanatory variables were total segment length, lane width, curvature of the road element, the curvature change rate on homogeneous road segments, and the number of residential driveways per km. ANOVA and additional synthetic statistical parameters were assessed to check the effectiveness of using a single general model to predict operating speeds at the same time on tangents and on circular curves alike. The results suggested the reliability of this hypothesis and its effectiveness in bringing advantages during the application phase.

Operating Speed Prediction Model as a Tool for Consistency Based Geometric Design of Four-Lane Divided Highways

“…Now, curves with radius 500 m or less are considered as sharp (Figueroa Medina, Tarko 2005). Sharp horizontal curves affect the preferred speed (Fitzpatrick et al 2000a;Jacob, Anjaneyulu 2013;Russo et al 2016). Hence, any misjudgement in vehicle speed while entering a horizontal curve can turn out to be unsafe.…”

“…The Highway Capacity Manual (TRB 2010) suggests that vehicles travelling with headway equal to or greater than a threshold headway value are considered as free flowing. For rural highways, several researchers have adopted the threshold headway value as 5 s (Fitzpatrick et al 2000a;Hashim et al 2016;Gong, Stamatiadis 2008;Poe et al 1996;Russo et al 2015Russo et al , 2016. However, weak lane discipline in multi-lane divided highways can influence vehicles (Mathew et al 2015;Mallikarjuna, Rao 2011;Gunay 2003Gunay , 2007Bangarraju et al 2016;Drew 1968;Case et al 1953;May 1959;Rawson 2015) prior to centre of the horizontal curve.…”

“…Flatter curves have radius of 1700 ft (i.e., 518 m) or more (Figueroa Medina, Tarko 2005). Russo et al (2016) reported that curves having radius more than 500 m do not influence driving performance in horizontal alignment. A study in India by Jacob and Anjaneyulu (2013) indicates that radius of 400 m or below influence the preferred speed on horizontal curves.…”

A Novel Approach for Operating Speed Continuous Predication Based on Alignment Space Comprehensive Index

“…This designing method is prone to be inconsistent with successive elements of a road. Large amount of practical studies highlights the fact that inconsistent alignment might cause a sudden change in the characteristics of the roadway, which would lead to critical driving errors and crash risks [1,2]. A consistent alignment design is required to meet drivers' expectations and promotes harmonious driving behaviors.…”

“…Operating speed is an expressive parameter of driver's behavior influenced by multiple factors, such as alignment, vehicle dynamical properties, traffic flow composition, traffic management and control measures, climate, and sight distance. The 85th percentile of the free-flow speed distribution is commonly used to represent operating speed for design consistency evaluation [1,8].…”