TY - JOUR
T1 - Determining Vehicle Operating Speed and Lateral Position Along Horizontal Curves Using Linear Mixed-Effects Models
AU - Fitzsimmons, Eric J.
AU - Kvam, Vanessa
AU - Souleyrette, Reginald R.
AU - Nambisan, Shashi S.
AU - Bonett, Douglas G.
PY - 2013/2
Y1 - 2013/2
N2 - Objective: Despite recent improvements in highway safety in the United States, serious crashes on curves remain a significant problem. To assist in better understanding causal factors leading to this problem, this article presents and demonstrates a methodology for collection and analysis of vehicle trajectory and speed data for rural and urban curves using Z-configured road tubes.Methods: For a large number of vehicle observations at 2 horizontal curves located in Dexter and Ames, Iowa, the article develops vehicle speed and lateral position prediction models for multiple points along these curves. Linear mixed-effects models were used to predict vehicle lateral position and speed along the curves as explained by operational, vehicle, and environmental variables. Behavior was visually represented for an identified subset of "risky" drivers.Results: Linear mixed-effect regression models provided the means to predict vehicle speed and lateral position while taking into account repeated observations of the same vehicle along horizontal curves.Conclusions: Speed and lateral position at point of entry were observed to influence trajectory and speed profiles. Rural horizontal curve site models are presented that indicate that the following variables were significant and influenced both vehicle speed and lateral position: time of day, direction of travel (inside or outside lane), and type of vehicle.
AB - Objective: Despite recent improvements in highway safety in the United States, serious crashes on curves remain a significant problem. To assist in better understanding causal factors leading to this problem, this article presents and demonstrates a methodology for collection and analysis of vehicle trajectory and speed data for rural and urban curves using Z-configured road tubes.Methods: For a large number of vehicle observations at 2 horizontal curves located in Dexter and Ames, Iowa, the article develops vehicle speed and lateral position prediction models for multiple points along these curves. Linear mixed-effects models were used to predict vehicle lateral position and speed along the curves as explained by operational, vehicle, and environmental variables. Behavior was visually represented for an identified subset of "risky" drivers.Results: Linear mixed-effect regression models provided the means to predict vehicle speed and lateral position while taking into account repeated observations of the same vehicle along horizontal curves.Conclusions: Speed and lateral position at point of entry were observed to influence trajectory and speed profiles. Rural horizontal curve site models are presented that indicate that the following variables were significant and influenced both vehicle speed and lateral position: time of day, direction of travel (inside or outside lane), and type of vehicle.
KW - horizontal curve
KW - linear mixed-effects model
KW - pneumatic road tubes
KW - speed profile
KW - traffic safety
KW - trajectory
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U2 - 10.1080/15389588.2012.701356
DO - 10.1080/15389588.2012.701356
M3 - Article
C2 - 23441950
AN - SCOPUS:84876315259
SN - 1538-9588
VL - 14
SP - 309
EP - 321
JO - Traffic Injury Prevention
JF - Traffic Injury Prevention
IS - 3
ER -