Charitha Dias

Drivers’ Speeding Behavior on Expressway Curves: Exploring the Effect of Curve Radius and Desired Speed

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.

Calibrating a social force based model for simulating personal mobility vehicles and pedestrian mixed traffic

Abstract Personal mobility vehicles (PMVs), such as the Segway, have recently gained remarkable popularity as an alternative transport mode for short-distance trips in indoor and outdoor settings. Before allowing them on shared sidewalks, where the pedestrian and cyclist demand is high, interactions between PMV riders and other shared space users should be properly understood. Further, the designs of shared sidewalks and implementation policies should also be evaluated. Calibrated microscopic simulation tools could facilitate such purposes. This study aims to explore the applicability of a social force based microscopic simulation model, which was originally used to simulate pedestrian movements and interactions, for Segway and pedestrian mixed traffic. The parameters of the model are calibrated with data collected through controlled experiments under different Segway–pedestrian interaction scenarios. Lateral and longitudinal avoidance distances measured from trajectory data collected in a different controlled experiment was used to validate the model for a Segway rider avoiding a pedestrian. The findings of this study suggest that, with proper calibration, the social force model can potentially be used to simulate Segway-like PMVs and pedestrian mixed traffic.