IVI HF

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IVI Human Factors Research Focus on Rear-End Crash Prevention Jan 12, 2004 Michael Perel IVI Human Factors Team Leader

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Rear-End 29%

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Understanding of geometric and kinematic scenarios in crashes

Human Factors Roadmapto Rear End Crash Prevention: 

Human Factors Roadmap to Rear End Crash Prevention Driver Aiding and Distraction Mitigation Countermeasures Immediate Vehicle Control Tactical Driver Action Strategic Driving Long-term Driver Adaptation Societal Adaptation Model adapted from J. Lee Crash TIME

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Immediate Vehicle Control Making warning detectable Making warning understandable Determining when driver needs to be warned (100-5,000 ms)

Tactical Driver Action: 

Tactical Driver Action Encouraging safe headway selection Designing devices to optimize driver attentional distribution Assuring accurate mental model of system operation 5-30 s

Strategic Driving: 

Strategic Driving (30s – Day) Understanding factors affecting driver willingness to multitask while driving Trip planning (pre set preferences)

Long-term Adaptation: 

Long-term Adaptation (Day – Months) Understanding factors affecting acceptance and reliance on warning system or Adaptive Cruise Control Identifying changes in driving behaviors that affect risk taking

Societal Adaptation: 

Societal Adaptation Determining the need for interface and performance standardization between vehicles Assessing usability and acceptance by broad range of driving population

Multiple Collision Warnings:Problem: 

Multiple Collision Warnings: Problem How will drivers respond to forward collision warnings when future vehicles also have road departure warning, lane change warning, intersection warning, etc? Multiple alarms may increase driver confusion Alarms in close temporal proximity may compete for driver’s attention Alerting benefits may decrease due to increased numbers of false or nuisance alarms

Multiple Collision Warnings:Objectives: 

Multiple Collision Warnings: Objectives Assess potential for and methods for overcoming driver confusion from multiple collision warnings Auditory warning localization Earcons Master warning Prioritization of warnings Application of findings to guidelines for standardization and integration of multiple warning systems

Multiple Collision Warnings: Approach: 

Multiple Collision Warnings: Approach Simulator study Drivers using vehicle with several IVI warning system interfaces Compare drivers responses to imminent collisions with single vs multiple warnings Evaluate performance improvements from alternative interface options

Multiple Collision Warnings: Status: 

Multiple Collision Warnings: Status Contract awarded to WESTAT and DRI Identified collision warning interfaces Developed experimental design Independent and dependent variables Subject tasks Procedures Developing simulator scenarios Planning for data collection Completion: July, 2004

Integration of Adaptive Cruise Control (ACC) and Forward Collision Warning (FCW): 

Integration of Adaptive Cruise Control (ACC) and Forward Collision Warning (FCW) Background ACC and FCW alter the traditional driving task Shared responsibility for headway maintenance and collision avoidance Drivers need detectable and understandable cues to help them know when they need to take over Diversity of interface and operational characteristics Objective How to present and coordinate ACC and FCW information and alerts

Integration of Adaptive Cruise Control (ACC) and Forward Collision Warning (FCW): 

Integration of Adaptive Cruise Control (ACC) and Forward Collision Warning (FCW) Research Questions/Experiments How perceptible are brake pulse alerts? What display modalities best convey ACC operations and FCW information—haptic and/or auditory? What is the effect of ACC and FCW authority and autonomy on driver performance and acceptance? What is the influence of non-useful FCW alarms on FCW effectiveness in imminent crash scenarios? Status Contract awarded to U of Iowa Using National Advanced Driving Simulator Experiments underway—completion Dec 2004

Voice Interface Research: 

Voice Interface Research Background Voice interfaces proposed as solution to driver distraction from visual/manual interfaces Objectives: Compare driving performance using speech-based versus visual/manual interfaces Assess how driver distraction is affected by voice interface characteristics

Voice Interface Research: 

Voice Interface Research Initial “Auto PC” study at NHTSA VRTC Conducted test track study in which subjects followed a car while performing voice interface tasks and a light detection task Preliminary findings Voice-based interface caused minor reduction in driver performance, limited to vehicle control and visual performance measures. No effect of voice interface on car following performance

Voice Interface Research: 

Voice Interface Research Current study focuses on how distraction potential is affected by voice interface characteristics: Voice interface task complexity Navigation of hierarchical menu structure Voice interface error rate Rate at which the system fails to recognize verbal commands Test track study using a simulated 511 traveler information system accessed using a hands-free wireless phone Completion in Summer 2004

Early Adopters Experiences with Advanced Technologies: 

Early Adopters Experiences with Advanced Technologies Objectives: Determine drivers’ usage and experience with new IVI-type technologies they have purchased What design and operational features enhance or detract from driver acceptance and safety Application of findings: Recommendations for improvements in interface design and operation Identification of possible new human factors problems and research needs Indications of device effectiveness for broad range of drivers and driving conditions

Approach: 

Approach Identify candidate commercial vehicle and passenger vehicle in-vehicle technologies ACC, Park Aid, Night Vision, Navigation, Collision warning, Side object detection Identify methods for contacting owners Conduct interviews and surveys Explore viability of instrumenting personal vehicles

Status: 

Status Awarded contract to WESTAT Identified available technologies Adaptive Cruise Control BMW, Mercedes, Jaguar, Lexus, Infinity,Cadillac Night Vision Cadillac, Lexus Navigation Park Aid Forward collision and side object warning (for trucks) Developing driver questions Big Challenge: identifying drivers and gaining their cooperation Completion: December 2004 ??

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For Further Information Mike.perel@nhtsa.dot.gov www.its.dot.gov