Citation

Dias C, Oguchi T, Wimalasena K. Transp. Res. Rec. 2018; 2672(17): 48-60.

Affiliation

1Institute of Industrial Science, The University of Tokyo, Tokyo, Japan 2Department of Civil and Environmental Engineering, University of Ruhuna, Galle, Sri Lanka Corresponding Author: Address correspondence to Charitha Dias: cdias@iis.u-tokyo.ac.jp

Copyright

(Copyright © 2018, Transportation Research Board, National Research Council, National Academy of Sciences USA, Publisher SAGE Publishing)

DOI

10.1177/0361198118778931

PMID

unavailable

Abstract

Speed profiles can be considered as a key input for assessing safety, comfort and efficiency of highway or expressway segments. Therefore, understanding drivers' speeding behavior, particularly on expressway curve sections, is important. Most previous studies have modeled the speed on highway curve sections mainly as constant or a piecewise linear profile. Such approaches may not realistically represent the properties of speed and acceleration behavior. Furthermore, mechanisms underlying the speeding behavior through curve sections have not been comprehensively studied. In this study, the minimum-jerk concept, which was originally applied in neuroscience and robotics domains, is utilized to explore drivers' speeding behavior on expressway curve sections. GPS-based naturalistic driving data of vehicles travelling on the Tomei expressway in Japan under free-flow conditions were used to explore the applicability and validity of the proposed approach. How the proposed approach can be used to evaluate the effect of horizontal geometry and desired driving speed on drivers' speeding and acceleration behavior on expressway curve sections is also discussed. The findings of this study could be useful in modeling speed and acceleration choice behaviors on highway curve sections which could potentially be applied in highway design consistency evaluations. Furthermore, the outputs of this study may be useful in other advanced applications, such as modeling and visualizing realistic vehicle movements in driving simulators and virtual reality applications and trajectory planning of autonomous vehicles.

Language: en