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Project

#110 Detecting Driver Distraction

Principal Investigator
Maxine Eskenazi
Status
Completed
Start Date
Jan. 1, 2014
End Date
Dec. 31, 2014
Project Type
Research Advanced
Grant Program
MAP-21 TSET - Tier 1 (2012 - 2016)
Grant Cycle
2014 TSET UTC
Visibility
Public

Abstract

It is well known that texting during driving causes divided attention, higher cognitive load and accidents. At the same time, many people feel that hands-free talking on the phone is not dangerous. Yet the same type of effort (understanding a conversation, figuring out what to say, feeling emotions, etc) is present when speaking. While it might be less objectionable at lower speeds on limited access roads, as the amount of issues to deal with increases and as speed increases, driving and speaking on the phone are a very dangerous combination. While there has been much work on detecting distraction in the driver’s habits, there is much less on detecting distraction from the point of view of their speech patterns. In order to find a way to alert drivers to imminent danger, we will develop algorithms that automatically detect, from the driver’s speech, when they are too distracted to be driving. We will first collect data on a simulator under several conditions: changes in speed, changes in unexpected events on the road, changes in amount of information in the conversation. We will mine this data to find indicators that change as conditions deteriorate along these three parameters. Later work will use the data collected to develop an automatic distraction detection system.
Description
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Timeline
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Strategic Description / RD&T

    
Deployment Plan

    
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Expected Outcomes/Impacts

    
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Expected Outputs

    

    
TRID

    


    
Individuals Involved

    

        
            

                Email
                Name
                Affiliation
                Role
                Position
            

        
        
            
                

                    awb@cs.cmu.edu
                    Black, Alan
                    LTI
                    Co-PI
                    Faculty - Research/Systems
                

            
                

                    max@cs.cmu.edu
                    Eskenazi, Maxine
                    LTI/SCS
                    PI
                    Faculty - Tenured
                

            
    


    
Budget


    
    
Amount of UTC Funds Awarded
 $50000.00
    
Total Project Budget (from all funding sources)
 $50000.00

    
Documents

    
        

            
                

                    Type
                    Name
                    Uploaded
                

            
            
                
                    
                
                    
                
                    
                    

                        Final Report
                        
                            UTC_project_110_-_Detecting_Driver_Distraction_-_final_report.pdf
                        
                        July 2, 2018, 4:34 a.m.
                    

                    
                
                    
                
            
        

    

    
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