Ahad, Mohammad

Chen, Yunfeng

Gao, Weinan

Iroghama, Osahon

Shen, Junan

Wu, Hongyue

English

Purdue E-Pubs

Cognitive Attention and Its Application in Countermeasures on a Curve Section*Purdue University, West Lafayette; **Georgia Southern University, Statesboro; ***Florida Institute of Technology, MelbourneProblem Statement and Objective• Cause of premature death: motor vehicle crashes• Causes of 90% traffic crashes: human errors – visual information processing• Attention-related issues: inattention, distracted attention, and “looked but failed to see” This study aims to:• Propose a methodology to evaluate the effectiveness of countermeasures of traffic safety based on drivers’ cognitive attention and driving performance.MethodologyComparison using Analysis of Variance  • Significant differences among the countermeasures and weather and traffic flow of:o Eye movement (cognitive attention)o Driving performanceo Short-term memoryVisualization of Attention• Most participants focused their attention on the roadway.Hongyue Wu*, Yunfeng Chen*, Junan Shen**, Weinan Gao***, Mohammad Ahad**, and Osahon Iroghama**Relationship between Countermeasures and Safety• Effective countermeasures:o Edge line pavement markingo Shoulder rumble stripso Flexible delineator postso Curve warning signo Increased shoulder width• Weather and traffic flow: o Foggy weather with heavy traffic flow: most dangerouso Clear weather and no traffic flow: most safeFindings and Conclusion• Case: two-lane rural curve (Cypress Lake Road, Statesboro, GA)• Curve type: horizontal and vertical curves; right and left curves• Length: 3000ft (0.57 mile)• Road Grade: 30ft difference at first 0.4 mile• Traffic flow: light traffic and heavy traffic• Weather: clear and fogFigure 4. Basic Scenario Model ExampleFigure 5. Heat MapRunsCountermeasures in each runCountermeasuresR1 C1 C1=Centerline Pavement MarkingR2 C1, C2 C2=Edge Line Pavement MarkingR3 C1, C2, C3 C3=Shoulder Rumble StripsR4 C1, C2, C4 C4=Flexible delineator postsR5 C1, C2, C5 C5=Posted Speed SignR6 C1, C2, C6 C6=Curve Warning SignR7 C1, C2, C7 C7=Curve Speed Warning SignR8 C1, C2, C8 C8=Increased Shoulder WidthR9 C1, C2, C9 C9=Changed Horizontal Curve CurvatureR10 C1, C2, C10 C10=Decreased Curve Grade on Negative GradeR11 C1, C2, C11 C11=Increased Curve Grade on Positive GradeDriving Simulation and Scenario ModelingTable 1. Countermeasures and RunsPre-surveySimulated driving tasksPost-surveyDemographic InformationEye Movement DataDriving Performance DataShort-term Memory DataQuestionnaireEye TrackerQuestionnaireDriving SimulatorFigure 2. Experiment Procedure• Eye tracker: Tobii eye tracker 4C with upgrade key• Driving simulator: STISIM M100• Traffic simulation: ParamicsFigure 3. Selected CaseConclusion• The proposed methodology can evaluate the effectiveness of countermeasures considering cognitive attention and driving performance to improve traffic safety. Figure 1. Driving Simulator and Eye Tracker System

Cognitive Attention and Its Application in Countermeasures on a Curve Section

https://docs.lib.purdue.edu/cgi/viewcontent.cgi?article=4527&context=roadschool

Cognitive Attention and Its Application in Countermeasures on a Curve Section

Abstract

Similar works

Full text

Available Versions

Purdue E-Pubs