This readme.txt file was generated on 20240105 by Morris, Nichole (edited by data curator 20240227) Recommended citation for the data: Morris, Nichole L; Schwieters, Katelyn R; Tian, Disi; Craig, Curtis M. (2024). Simulated driver performance, error, and acceptance study of a J-turn intersection with 3 levels of signage. Retrieved from the Data Repository for the University of Minnesota, https://doi.org/10.13020/DNZ4-S946. ------------------- GENERAL INFORMATION ------------------- 1. Title of Dataset Simulated driver performance, error, and acceptance study of a J-turn intersection with 3 levels of signage 2. Author Information Principal Investigator Contact Information Name: Nichole L Morris, PhD Institution: University of Minnesota, Department of Mechanical Engingeering Address: 111 Church St SE, Minneapolis, MN 55455 Email: nlmorris@umn.edu ORCID: https://orcid.org/0000-0002-1296-9068 Associate or Co-investigator Contact Information Name: Katelyn R Schwieters Institution: University of Minnesota, Department of Mechanical Engingeering Address: 111 Church St SE, Minneapolis, MN 55455 Email: schwi154@umn.edu ORCID: https://orcid.org/0000-0001-9802-8957 Associate or Co-investigator Contact Information Name: Disi Tian, PhD Institution: University of Minnesota, Department of Mechanical Engingeering Address: 111 Church St SE, Minneapolis, MN 55455 Email: tianx229@umn.edu ORCID: https://orcid.org/0000-0002-9038-8875 Associate or Co-investigator Contact Information Name: Curtis M Craig, PhD Institution: University of Minnesota, Department of Mechanical Engingeering Address: 111 Church St SE, Minneapolis, MN 55455 Email: tianx229@umn.edu ORCID: https://orcid.org/0000-0002-5257-5936 3. Date published or finalized for release: 1/4/2024 4. Date of data collection (single date, range, approximate date) 20210820-20210928 5. Geographic location of data collection (where was data collected?): Minneapolis, MN 6. Information about funding sources that supported the collection of the data: This work is supported by the Minnesota Department of Transportation, Award: 1003325 WO 98 7. Overview of the data (abstract): Thirty-six participants with limited previous experience and knowledge of J-turns intersections (which restrict crossing movements at divided highway intersections) participated in a simulation study examining their driving performance and navigation of them. Participants crossed three simulated J-turn intersections (resembling a real J-turn intersection in Minnesota) in counterbalanced order, each featuring one of three signage level (Full signage, intermediate signage, minimum signage). They were asked three questions regarding their acceptance of J-turns before and after J-turn exposure. Their navigational path was visualized and three raters evaluated their performance against an optimal path and coded the occurence of navigational errors (11 possible). The combined error dataset, participant J-turn acceptance, and demographic factors are included in the data file. Image files of participants nagivational path are included in the dataset. -------------------------- SHARING/ACCESS INFORMATION -------------------------- 1. Licenses/restrictions placed on the data: CC0 1.0 Universal https://creativecommons.org/publicdomain/zero/1.0/ 2. Links to publications that cite or use the data: Morris, N. L., Schwieters, K. R. Craig, C. M., & Tian, D. (2023). Establishing a repeatable method for presenting nontraditional traffic treatments to maximize stakeholder support. (No. CTS 2022-31). Center for Transportation Studies, University of Minnesota; https://www.cts.umn.edu/research/project/establishing-a-repeatable-method-for-presenting-non-traditional-traffic-treatments-to-maximize-stakeholder-support. 112 pages. 3. Was data derived from another source? NO 4. Terms of Use: Data Repository for the U of Minnesota (DRUM) By using these files, users agree to the Terms of Use. https://conservancy.umn.edu/pages/drum/policies/#terms-of-use --------------------- DATA & FILE OVERVIEW --------------------- 1. File List A. Filename: jturn_data_12_21_23.csv Short description: CSV file containing long form data of participant demographics (non identifying), experimental condition, errors, and pre-post J-turn acceptance B. Filename: Data Dictionary.csv Short description: CSV file containing variable (header names from "jturn_data_12_21_23") and descriptions of variables C. Filename: Participant drive visualizations Short description: ZIP file containing PNG files of visualized path of each participant's navigation of the J-turn intersection 2. Relationship between files: Data dictionary file explains "jturn_data_12_21_23" and "Participant drive visualizations" are the images used to create the error counts in "jturn_data_12_21_23" -------------------------- METHODOLOGICAL INFORMATION -------------------------- 1. Description of methods used for collection/generation of data: Participants read the information sheet and completed the screening questionnaire online. If they were eligible, they were scheduled to complete the simulation test on campus. After participants arrived on campus, provided informed consent, they began the experiment. Participants performed a practice drive in the simulator to assess general propensity to simulation sickness. After, participants filled out a wellness questionnaire to assess symptoms of simulation sickness. If they experienced no simulation sickness symptoms, they proceeded to the next segments of the experiment. The participants answered a few brief questionnaires about their driving history, habits, and attitudes on a tablet computer. Then they drove through a regular thru-stop intersection in order to acclimate them to how the simulator functions when turning the vehicle. Then the participants made a turn on a second regular thru-stop intersection. After this turn, the participants stopped and took a break. Then the participants approached and navigated the first J-turn intersection (one of three signage conditions, randomized). After completing the turn, the participants will stopped for a break. Then the participants approached and navigated the second J-turn interesection (one of two remaining signage conditions, randomized). After completing the turn, the participants stopped to rest. Then the participants approached and navigated the last J-turn intersection (the remaining signage condition, randomized). After completing the turn, the participants stopped completed a final post-test questionnaire. During the drives, the research team monitored participants for symptoms of simulation sickness. Data from questionnaires was stored and navigated paths from the simulation was convered into a visualized path for error coding. 2. Methods for processing the data: The intended path for navigating this J-turn intersection design as established by state engineers provided a basis of comparison for the path taken by each participant across the three experimental J-turn crossing tasks. The intended path and established navigational steps were used to create a framework for identifying possible J-turn errors. Errors were then identified through a multi-method approach using navigational and vehicle control errors established in the task analysis and the data collected from the concurrent think aloud, semi-structured interviews, and simulated J-turn performance across all participants. The established errors were plotted and classified by step error and error severity (Reason et al., 1990). Error severity was defined considering the extent to which the participant deviated from the intended path as well as the potential risk of crash. This classification aimed to capture usability issues of the intersection design that may increase exposure risk with increased time on task as well as risk of collision with other vehicles. Errors were classified as major if they greatly increased the risk of a serious crash (e.g., head-on) or resulted in failure to complete the left turn (Dumas and Redish, 1993). Errors were identified as moderate if they were considered to result in a risk of minor crash (e.g., sideswipe) and/or included additional turning maneuvers not permitted under state law (i.e., Minnesota Statute 169.19), such as turning into the far lane or shoulder in a vehicle configuration which does not require such a maneuver. Errors were classified as minor if the risk of crashes in general was estimated to be low, but drivers failed to follow the expected steps of the intended path which would have a minor expected effect on usability of the intersection. The classified errors were also reviewed and validated by a MN state professional engineer. For each simulated J-turn drive, the data visualization of each participant’s traveled path was created (see Participant drive visualizations). The data visualizations were reviewed and coded separately, by three experienced and trained coders, using a binary error coding system (1 = yes, 0 = no) for each possible error. Given multiple raters, analysis used the interrater reliability statistic Fleiss’ Kappa (Fleiss, 1971). Fleiss’ κ = .71, z = 7.04, p < .001, indicating a good level of agreement. All coding differences were identified and discussed together by coders to reach a decision that best matched with the error definitions defined in the Error Classification section. Finally, a fourth coder settled the remaining disagreements with errors pertinent to straddling the lane(s). The final agreed upon error values are presented in "jturn_data_12_21_23" 3. Instrument- or software-specific information needed to interpret the data: Excel or other statistical analysis software 4. Standards and calibration information, if appropriate: n/a 5. Environmental/experimental conditions: Study Design: The study is a mixed experimental design, with type of signage condition being between-subjects for the very first drive (3 levels) and within-subjects for the following two drives (subsequent drives). First Exposure (Between Subjects) (3 Levels of Signage: Minimum, Intermediate, Full), Repeated (Within Subjects) (3 Levels of Signage: Minimum, Intermediate, Full). IRB determination: Exempt (STUDY00013229) 6. Describe any quality-assurance procedures performed on the data: For each simulated J-turn drive, the data visualization of each participant’s traveled path was created (see Participant drive visualizations). The data visualizations were reviewed and coded separately, by three experienced and trained coders, using a binary error coding system (1 = yes, 0 = no) for each possible error. Given multiple raters, analysis used the interrater reliability statistic Fleiss’ Kappa (Fleiss, 1971). Fleiss’ κ = .71, z = 7.04, p < .001, indicating a good level of agreement. All coding differences were identified and discussed together by coders to reach a decision that best matched with the error definitions defined in the Error Classification section. Finally, a fourth coder settled the remaining disagreements with errors pertinent to straddling the lane(s). The final agreed upon error values are presented in "jturn_data_12_21_23" Errors were subjected to a quality check to ensure their accuracy. Errors committed that would result in missed steps and consequently no chance to commit an error within that step were identified and the data was analyzed to ensure that these instances were not included in the dataset. 7. People involved with sample collection, processing, analysis and/or submission: Nichole Morris, Katelyn Schwieters, Disi Tian, Peter Easterlund, Marshall Mabry ----------------------------------------- DATA-SPECIFIC INFORMATION FOR: jturn_data_12_21_23.csv ----------------------------------------- Note: This dataset is presented in long form. So, it repeats the J-turn attitude scores (pre_good; pre_willing; pre_community, pre_att_sum, post_good, post_willing, post_community, post_att_sum, att_change) and other demographic variables (age, gender (1F, 2M), city) across the three drives. Analyses of these variables should be collapsed so that the duplicate values are not included in analyses. 1. Number of variables:34 2. Number of cases/rows: 102 3. Missing data codes:n/a Data contains only one drive for Participant 8 and participant 53, and two drives for Participant 65 and Participant 77. 4. Variable List A. Name: participant Description: Participant ID number B. Name: firsttime Description: J-turn drive exposure order (1 = first time exposure, 0 = 2nd or 3rd exposure) C. Name: jturn_exp Description: Knowledge or experience with J-turn/RCUTs (0 = none, 1 = little-to-no knowledge) D. Name: crash_exp Description: Participant experienced a crash or near-miss at any intersection in the past 10 years (0 = no, 1 = yes) E. Name: signage Description: Signage level present (1 = Minimum, 2 = Intermediate, 3 = Full) F. Name: error1 Description: Drove wrong way on intersection - cut through near or far cut-through lane (Step 2 Error) G. Name: error2 Description: Entered right shoulder instead of deceleration lane (Step 3 Error) H. Name: error3 Description: Entered right lane instead of deceleration lane (Step 3 Error) I. Name: error4 Description: Entered left lane instead of deceleration lane (Step 3 Error) J. Name: error5 Description: Straddle left lane and deceleration lane (Step 3 Error) K. Name: error6 Description: Late turn into deceleration lane (< 250 ft from U-turn) (Step 3 Error) L. Name: error7 Description: Did not make U-turn (Step 4 Error) M. Name: error8 Description: Made U-turn into right (far) lane (Step 5 Error) N. Name: error9 Description: Straddle right lane and shoulder or swerve out of lane onto shoulder (Step 5 Error) O. Name: error10 Description: Did not change lanes into right lane after U-turn (Step 6 Error) P. Name: error11 Description: Made multiple turns or multiple U-turns (Step 7 Error) Q. Name: high_sum Description: Total count of Major Severity Errors R. Name: med_sum Description: Total count of Moderate Severity Errorse S. Name: low_sum Description: Total count of Minor severity ErrorsD T. Name: high_bi Description: Binary count of at least one Major Severity Error (1 = one or more major severity errors, 0 = no major severity errors) U. Name: med_bi Description: Binary count of at least one Moderate Severity Error (1 = one or more moderate severity errors, 0 = no moderate severity errors) V. Name: low_bi Description: Binary count of at least one Minor Severity Error (1 = one or more minor severity errors, 0 = no minor severity errors) W. Name: age Description: Participant age in years X. Name: gender(1F, 2M) Description: Participant gender (1 = Female, 2 = Male) Y. Name: city Description: Participant self-identified location type of residency (1 = urban, 2 = suburban, 3 = rural) Z. Name: pre_good Description: "I think J-turns are a good idea" response pre-exposure to simulated J-turns (7-point Likert scale: 1 = Definitely not, 7 = Definitely) AA. Name: pre_willing Description: "I am willing to drive on a J-turn" response pre-exposure to simulated J-turns (7-point Likert scale: 1 = Definitely not, 7 = Definitely) AB. Name: pre_community Description: "I would be supportive of a J-turn in my community" response pre-exposure to simulated J-turns (7-point Likert scale: 1 = Definitely not, 7 = Definitely) AC. Name: pre_att_sum Description: Sum of pre-exposure Likert responses (pre_good + pre_willing + pre_community) Minimum possible score of 3, Maximum possible score of 21 AD. Name: post_good Description: "I think J-turns are a good idea" response post-exposure to simulated J-turns (7-point Likert scale: 1 = Definitely not, 7 = Definitely) AE. Name: post_willing Description: "I am willing to drive on a J-turn" response post-exposure to simulated J-turns (7-point Likert scale: 1 = Definitely not, 7 = Definitely) AF. Name: post_community Description: "I would be supportive of a J-turn in my community" response post-exposure to simulated J-turns (7-point Likert scale: 1 = Definitely not, 7 = Definitely) AG. Name: post_att_sum Description: Sum of post-exposure Likert responses (post_good + post_willing + post_community) Minimum possible score of 3, Maximum possible score of 21 AH. Name: att_change Description: Difference score between sum of pre-attitude responses and sum of post-attitude responses (post_att_sum - pre_att_sum) ----------------------------------------- DATA-SPECIFIC INFORMATION FOR: Participant Drive Visualizations.zip ----------------------------------------- 1. Number of variables:n/a 2. Number of cases/rows: 102 images 3. Missing data codes:n/a Data contains only one drive for Participant 8 and participant 53, and two drives for Participant 65 and Participant 77. 4. Image File List (within ZIP File) P4_D1_Intermediate P4_D2_Minimum P4_D3_Full P6_D1_Minimum P6_D2_Full P6_D3_Intermediate P7_D1_Intermediate P7_D2_Full P7_D3_Minimum P8_D1_Full P9_D1_Minimum P9_D2_Intermediate P9_D3_Full P13_D1_Full P13_D2_Minimum P13_D3_Intermediate P16_D1_Full P16_D2_Intermediate P16_D3_Minimum P17_D1_Intermediate P17_D2_Minimum P17_D3_Full P22_D1_Intermediate P22_D2_Minimum P22_D3_Full P23_D1_Full P23_D2_Minimum P23_D3_Intermediate P25_D1_Minimum P25_D2_Intermediate P25_D3_Full P26_D1_Intermediate P26_D2_Full P26_D3_Minimum P27_D1_Minimum P27_D2_Full P27_D3_Intermediate P31_D1_Full P31_D2_Intermediate P31_D3_Minimum P32_D1_Intermediate P32_D2_Full P32_D3_Minimum P33_D1_Full P33_D2_Minimum P33_D3_Intermediate P35_D1_Minimum P35_D2_Full P35_D3_Intermediate P36_D1_Intermediate P36_D2_Full P36_D3_Minimum P43_D1_Full P43_D2_Intermediate P43_D3_Minimum P44_D1_Minimum P44_D2_Full P44_D3_Intermediate P45_D1_Intermediate P45_D2_Full P45_D3_Minimum P46_D1_Minimum P46_D2_Full P46_D3_Intermediate P47_D1_Intermediate P47_D2_Full P47_D3_Minimum P48_D1_Full P48_D2_Minimum P48_D3_Intermediate P49_D1_Full P49_D2_Minimum P49_D3_Intermediate P50_D1_Minimum P50_D2_Intermediate P50_D3_Full P51_D1_Full P51_D2_Minimum P51_D3_Intermediate P53_D1_Intermediate P57_D1_Full P57_D2_Minimum P57_D3_Intermediate P62_D1_Minimum P62_D2_Intermediate P62_D3_Full P64_D1_Minimum P64_D2_Intermediate P64_D3_Full P65_D1_Minimum P65_D2_Full P70_D1_Minimum P70_D2_Intermediate P70_D3_Full P71_D1_Intermediate P71_D2_Full P71_D3_Minimum P72_D1_Full P72_D2_Intermediate P72_D3_Minimum P77_D1_Full P77_D2_Minimum