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Pedestrian Scenario Design and Performance Assessment in Driving Simulations. Achal Oza, Qiong Wu, Ronald Mourant Virtual Environments Laboratory Northeastern University Presented by Achal Oza oza@coe.neu.edu Driving Simulation Conference 2005 North America November 30, 2005 Orlando, FL.
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Pedestrian Scenario Design and Performance Assessment in Driving Simulations Achal Oza, Qiong Wu, Ronald Mourant Virtual Environments Laboratory Northeastern University Presented by Achal Oza oza@coe.neu.edu Driving Simulation Conference 2005 North America November 30, 2005 Orlando, FL
Overview • Motivation • Technology • Triggering System • Scenarios and Results • Analysis
Motivation • 4,749 pedestrians were killed in motor vehicle accidents in 2003 • Improve safety by developing scenarios that may be unsafe or impossible to test in a real-world environment • Test subjects for situation awareness, hazard detection, and decision-making
Overview • Motivation • Technology • Triggering System • Scenarios and Results • Analysis
Technology • ‘91 Dodge Caravan • Force feedback steering wheel and pedals • Alienware computerPentium 4 3.4 GHzGeForce 6800 Ultra • Parabolic screen • 1024 x 768 resolution30° horizontal field of view
Overview • Motivation • Technology • Triggering System • Scenarios and Results • Analysis
Pedestrian Model • MD2 file format (originally developed for Quake 2) • Two types of animations: • Walking • Idling
Triggering System • An object’s action is triggered by another object performing a specified action • Pedestrians use two type of triggers: • Traffic lights • User vehicle
Triggering SystemTraffic Light Triggers • The pedestrian is bound to a traffic light • Walking is triggered by a green light • Continues walking even after light change back to red
Triggering SystemUser Vehicle • Pedestrian is bound to the user vehicle • Walking is triggered when the vehicle enters a specified radius
Overview • Motivation • Technology • Triggering System • Scenarios and Results • Crosswalk Scenario • Intersection Dash Scenario • Vehicle Turning Scenario • Bus Stop Scenario • Analysis
Crosswalk Scenario • Crosswalk with a yield-to-pedestrians sign • Crossing starts when driver is 225 feet away • High pedestrian visibility
Results for Crosswalk Scenario • 8 out of 10 subjects avoided a collision • Stopped near crosswalk • Good Time-To-Collision estimate • The remaining two slowed down after collision
Overview • Motivation • Technology • Triggering System • Scenarios and Results • Crosswalk Scenario • Intersection Dash Scenario • Vehicle Turning Scenario • Bus Stop Scenario • Analysis
Intersection Dash Scenario • Driver waits at an intersection for a red light to turn green • Pedestrian illegally crosses after the driver enters the intersection
Results for Intersection Dash Scenario • 6 out of 10 subjects avoided a collision • The remaining four ran through the red light
Overview • Motivation • Technology • Triggering System • Scenarios and Results • Crosswalk Scenario • Intersection Dash Scenario • Vehicle Turning Scenario • Bus Stop Scenario • Analysis
Vehicle Turning Scenario • Pedestrian crosses in front of the user vehicle while making a left turn at an intersection • High pedestrian visibility
Results for Vehicle Turning Scenario • 6 out of 10 subjects stopped before reaching the pedestrian • Remaining four slowed down, without completely stopping, allowing the pedestrian to safely cross
Overview • Motivation • Technology • Triggering System • Scenarios and Results • Crosswalk Scenario • Intersection Dash Scenario • Vehicle Turning Scenario • Bus Stop Scenario • Analysis
Bus Stop Scenario • Initially obstructed from view by a bus • Jaywalker enters street when driver is within 130 feet • Minimal pedestrian visibility
Results for Bus Stop Scenario • 10 out of 10 subjects collided with the pedestrian • 4 out of 10 stopped after the collision
Overview • Motivation • Technology • Triggering System • Scenarios and Results • Analysis
Scenario Analysis • Scenarios ranked from safe to dangerous: • Crosswalk • Vehicle Turning • Intersection Dash • Bus Stop • Safety increases when visibility increases
Future Study • Focus on varying pedestrian visibility • Larger sample sizes and more test groups • Experienced and inexperienced drivers • Add intelligence to the pedestrians • Hesitate when crossing in a dangerous area • Collect real-world data for validation (where possible) • Use a variety of pedestrian models • Children, the elderly, etc.
References 1. NHTSA, (2004). Traffic Safety Facts 2003-National Highway Traffic Safety Administration 2. Kenneth R. Laughery, Theodore E. Anderson & Edwin A. Kidd (1967). “A computer simulation model of driver-vehicle performance at intersection.” Proceeding of the 1967 22nd national conference. ACM Press. New York, NY, USA. 3. Dirk Helbing. (1992) “Model for Pedestrian Behavior.” Pages 93-98 in: Natural Structures. Principles, Strategies, and Model in Architecture and Nature, Part II. 4. Staplin, L., K. Lococo, and S. Byington. “Older Driver Highway Design Handbook.” The Scientex Corporation – Transportation Safety Division, Pennsylvania 19443, FHWA-RD-97-135, January 1998. 5. Gale, A.G., et al. “Time-To-Collision As A Cue For Decision-Making in Braking.” Vision in Vehicles. Vol. 3, 1991, pp. 19-26. 6. Hoffman, Errol R., and Rudolf G. Mortimer. “Drivers’ Estimates Of Time To Collision.” Accid Anal Prev, Vol. 26, No. 4, 1994, pp. 511-520.
Questions? Achal Oza oza@coe.neu.edu Virtual Environments Laboratory Northeastern University