Replication Data for: Evaluation of Autonomous Vehicles and Smart Technologies for Their Impact on Traffic Safety and Traffic Congestion [supporting datasets]

Miles, James; Strybel, Thomas; University of Southern California, Los Angeles

doi:10.7910/DVN/BWCCET

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Replication Data for: Evaluation of Autonomous Vehicles and Smart Technologies for Their Impact on Traffic Safety and Traffic Congestion [supporting datasets]

2020-01-31
By Miles, James ; Strybel, Thomas

[PDF-140.46 KB]

English

Details Supporting Files You May Also Like

Details:

Creators:

Miles, James ; Strybel, Thomas

Miles, James ; Strybel, Thomas Less -
Corporate Creators:

University of Southern California, Los Angeles
Corporate Contributors:

California State University, Long Beach ; United States. Department of Transportation. University Transportation Centers (UTC) Program ; California. Dept. of Transportation. Division of Research, Innovation, and System Information

California State University, Long Beach ; United States. Department of Transportation. University Transportation Centers (UTC) Program ; California. Dept. of Transportation. Division of Research, Innovation, and System Information Less -
Subject/TRT Terms:

[+]

Autonomous Vehicle Handover Autonomous Vehicles Data Collection Driver Performance Drivers Driving Driving Simulators Mobility Passenger Transportation Safety Traffic Congestion Traffic Safety Transportation Planning Travel Behavior
Publication/ Report Number:

PSR-17-11
DOI:

https://doi.org/10.7910/DVN/BWCCET
Resource Type:

Dataset
Geographical Coverage:

California ; United States

California ; United States Less -
Corporate Publisher:

California. Dept. of Transportation. Division of Research and Innovation
Abstract:

Our research generated demographic, survey, and behavior data related to driver performance on a simulated highway environment. Data was collected from 36 individuals, that were predominantly undergraduate and graduate students at California State University Long Beach. All identifying information has been removed from the data. Specifically, data in the selected repositories includes: - Demographic data related to participant characteristics, including age, gender, ethnicity, and driving experience. - Subjective reports of participant trust in automation adopted from Jian et al. (2000) using a 6 choice Likert-type scale. The questionnaire is designed to measure specific attitudes about automation including trust (items 2-5) and overall view of automation (items 9-12). - Subjective reports of participant workload. Participants completed a paper-based NASA Task Load Index (TLX) workload scale (see Appendix B). NASA-TLX consists of 6 subscales measuring different subjective dimensions of workload: Mental Demands, Physical Demands, Temporal Demands, Frustration, Effort, and Performance. NASA-TLX also included an initial weighting of these dimensions. A single workload score is calculated from NASA-TLX following each track by measuring the percent rating (0-100) on each dimension and calculating the average across all dimensions. Higher values indicate increased subjective mental workload. • Driver performance measures when performing obstacle avoidance maneuvers on a simulated highway. Specific performance measure for each obstacle maneuver are provided in the repository including vehicle state at the initiation and completion of maneuvers.
Format:

PDF
Funding:

USDOT Grant 69A3551747109 Caltrans Grant 65A0674, Task Order 006
Collection(s):

University Transportation Centers US Transportation Collection
Main Document Checksum:

[+]

urn:sha256:73aa99917a5654c347f595f0ec21fffe1adde2c4e4c779dc680236d714f4b6bc
Download URL:

https://rosap.ntl.bts.gov/view/dot/54633/dot_54633_DS1.pdf
File Type:

Replication_Data_for_Evaluation_of_Autonomous_Vehicles_Dataset_Metadata.json

json

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