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IAP Project: Use of SHRP 2 NDS Data to Evaluate Roadway Departure Crash Characteristics - Phase II

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DataCite Commons2020-12-01 更新2024-07-13 收录
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https://dataverse.vtti.vt.edu/citation?persistentId=doi:10.15787/VTT1/5JMOH9
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Project Description This dataset supports research to better understand the relationship between driver, roadway and environmental characteristics and roadway departures. The study focused on assessing the impacts of specific roadway factors and roadway countermeasures in order to provide agencies with better information on which countermeasures are effective and why. Data Request Scope The following three sets of events are included in this dataset: Crash/Near-crash Events: These 92 events were specified by ISU Trips for Locations with Particular Characteristics: A total of 10,000 traversals were selected by ISU using several RID attributes and countermeasures of interest including night trips and trips with rainfall. Matched Baselines: ISU identified 700 events for matched baselines. Two baselines per event were selected by VTTI based on the following priorities: Same driver on same link, Same driver and same direction on link, Same driver and same time of day. Where sufficient trips were unavailable, other drivers were substituted. An additional 11 events were selected by ISU for 20 matched baselines per event. These additional baselines were selected by VTTI based on the following priorities: Same driver and same link, Left and Right marker probability > 512, and Median marker probability. Again where sufficient trips were unavailable, other drivers were substituted. Data Specification The datasets consisted of the following InSight variables: o Driver Demographics Questionnaire: ParticipantID; AgeWhenTripCollected; Sex; Licensure; Education; o Driving History Questionnaire: ParticipantID; AnnualMiles; YrsDriving; NumViol; NumCrashes; o Risk Taking Questionnaire: ParticipantID; Roll thru Stp; Spd 20+ Over; Spd10-20 Over; Rn Stp Sm; Rsks Fun; Fail Adj o Vehicle characteristics: Vehicle Type, Track Width The datasets also included the following Time Series variables: System.Time_Stamp; vtti.timestamp; vtti.file_id; vtti.abs vtti.accel_x; vtti.accel_y; vtti.accel_z; vtti.airbag_driver; vtti.alcohol_interior; vtti.cruise_state; vtti.year_gps; vtti.month_gps; computed.day_of_week; computed.time_bin; vtti.pdop; vtti.driver_button; vtti.esc; vtti.elevation_gps; vtti.head_confidence; vtti.head_position_x; vtti.head_position_x_baseline; vtti.head_position_y; vtti.head_position_y_baseline; vtti.head_position_z; vtti.head_position_z_baseline; vtti.head_rotation_x; vtti.head_rotation_x_baseline; vtti.head_rotation_y; vtti.head_rotation_y_baseline; vtti.head_rotation_z; vtti.head_rotation_z_baseline; vtti.headlight; vtti.light_level; vtti.left_line_right_distance; vtti.right_line_left_distance; vtti.right_marker_probability; vtti.left_marker_type; vtti.right_marker_type; vtti.left_marker_probability; vtti.lane_distance_off_center; vtti.lane_width; vtti.latitude; vtti.longitude; vtti.number_of_satellites; vtti.pedal_gas_position; vtti.pedal_brake_state; vtti.gyro_y; vtti.heading_gps; vtti.prndl; vtti.gyro_x; vtti.seatbelt_driver; vtti.speed_gps; vtti.speed_network; vtti.steering_wheel_position; vtti.traction_control_state; vtti.turn_signal vtti.video_frame; vtti.wiper; vtti.gyro_z; TARGET_ID; X_VEL_PROCESSED; Y_VEL_PROCESSED; Forward Video; and Rear Video
提供机构:
VTTI
创建时间:
2018-11-09
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