01520131

Component

https://doi.org/10.3141/2434-12

http://scholar.google.com...egan&publication_year=2014

A stereo image and high-accuracy positional data were used to generate and populate a low-fidelity graphics model. The data were acquired by a simple mobile mapping system. The use of positional data made it possible to generate automatically a sparse model consisting of a road, central road marking, a green area, and a skybox. This allowed for several applications, such as the synchronization of the model with the video and the semiautomatic population of road signs into the model data. An experiment was conducted to evaluate the model and the video as viable sources for behavioral testing of drivers. The correlations between driver speed in response to the model and the video are presented; this presentation allows for an examination of the effect of the fidelity of the driving simulator’s visual cue stream. The study results were used to compare driver speed in a real vehicle with driver speeds in the video and model roads, with correlations of 84.6% (between video and ground truth), 87.3% (between model and ground truth), and 92.8% (between video and model).

01545262

14-0473

English

pp 95–102

2014

Transportation Research Record: Journal of the Transportation Research Board

9780309295222

Print

Figures (6) ; References (33)

Behavior; Computer graphics; Driver performance; Drivers; Driving simulators; Mapping; Mathematical models; Speed; Video

Data and Information Technology; Education and Training; Highways; Safety and Human Factors; I72: Traffic and Transport Planning

TRIS, TRB, ATRI

Jan 27 2014 2:14PM

• Bicycles in Urban Areas: Review of Existing Methods for Modeling Behavior
• Cell Phone Resting Locations: Use of the 100-Car Naturalistic Driving Study to Determine the Most Frequent In-Vehicle Cell Phone Placement and Containers
• Combining Driving Performance Information in an Index Score: A Simulated Curve-Taking Experiment
• Compensatory Behavior of Drivers When Conversing on a Cell Phone: Investigation with Naturalistic Driving Data
• Effect of Different Distractions on Driving Performance for Drivers Using a Touch Screen
• Evaluation of Truncated Arrow per Lane Guide Signs
• Examination of Limitations Associated with Observing Driver Distraction
• Factors Affecting Drivers’ Cell Phone Use Behavior: Implications from a Naturalistic Study
• Integrating Behavioral Models in Network Operations: Evaluating Traveler Information and Demand Management for Weather-Related Events
• Microscopic Simulation Model for Pedestrian Flow at Signalized Crosswalks
• Novel Vehicle Motion Model Considering Driver Behavior for Trajectory Prediction and Driving Risk Detection
• Prediction of Drivers’ Speed Behavior on Rural Motorways Based on an Instrumented Vehicle Study
• Susceptibility to Driver Distraction Questionnaire: Development and Relation to Relevant Self-Reported Measures
• Traffic-Calming Measures Affecting Perceived Speed in Approaching Bends: On-Field Validated Virtual Environment
• Use of Drivers’ Jerk Profiles in Computer Vision–Based Traffic Safety Evaluations
• Use of Naturalistic Driving Data to Characterize Driver Behavior in Freeway Shockwaves