Affiliation:
1. Beijing Engineering Research Center of Urban Transport Operation Guarantee, Beijing University of Technology, Beijing 100124, China
2. Key Laboratory of Transportation Industry of Automotive Transportation Safety Enhancement Technology, Chang’an University, Xi’an 710064, China
Abstract
Variable message signs (VMS) are widely employed to offer drivers dynamic traffic information. However, it is still lacking practical guidance about the information volume displayed on a graphical VMS. Building on the result of the subjective questionnaire survey, a static cognitive experiment was conducted to analyze the influence of volume information (i.e., elements and displaying the number of roads) of graphical VMS on drivers’ visual cognition characteristics and then determine the threshold number of roads displayed on VMS. Forty-five drivers participated in the static cognitive experiment. Five indicators, including visual cognition time, cognition accuracy, comprehension accuracy, general assessment, and information acceptance, were used to estimate the influences of graphical VMS. Study results by descriptive statistics and statistical hypothesis testing indicated that drivers also preferred auxiliary elements (i.e., distance or time information) besides basic design elements (i.e., driving direction, current position, and road name) displayed on graphical VMS. With the increase in information volume, driver visual cognition time increased while other companion indexes (i.e., visual cognition accuracy and comprehension accuracy) generally worsened. Combining the data of drivers’ objective behavior and subjective scoring, the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method revealed that the number of roads shown on the graphical VMS should be no greater than five. The study results were verified by dynamic simulation experiments. This finding provides a supplement for the design standards and usage specifications for VMS.
Subject
Strategy and Management,Computer Science Applications,Mechanical Engineering,Economics and Econometrics,Automotive Engineering
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