Investigating the Impact of In-car Communication on Law Enforcement Officer Patrol Performance in an Advanced Driving Simulator in Mississippi, 2011 (ICPSR 34922)

Published: Dec 21, 2016 View help for published

Principal Investigator(s): View help for Principal Investigator(s)
Carrick Williams, Mississippi State University; Daniel Carruth, Mississippi State University

https://doi.org/10.3886/ICPSR34922.v1

Version V1

These data are part of NACJD's Fast Track Release and are distributed as they there received from the data depositor. The files have been zipped by NACJD for release, but not checked or processed except of the removal of direct identifiers. Users should refer to the accompany readme file for a brief description of the files available with this collections and consult the investigator(s) if further information is needed.

This study used an experimental design to evaluate law enforcement officers' driving, visual attention, and situation awareness during patrol driving. The conditions were varied to determine the impact of information presentation formats on officers' ability to execute patrols. In addition, the effectiveness of in-vehicle technologies that may provide additional support to the officer and reduce the impact of information overload were investigated.

Williams, Carrick, and Carruth, Daniel. Investigating the Impact of In-car Communication on Law Enforcement Officer Patrol Performance in an Advanced Driving Simulator in Mississippi, 2011. Ann Arbor, MI: Inter-university Consortium for Political and Social Research [distributor], 2016-12-21. https://doi.org/10.3886/ICPSR34922.v1

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United States Department of Justice. Office of Justice Programs. National Institute of Justice (2010-DJ-BX-2017)

Access to these data is restricted. Users interested in obtaining these data must complete a Restricted Data Use Agreement, specify the reasons for the request, and obtain IRB approval or notice of exemption for their research.

Inter-university Consortium for Political and Social Research
2011-06 -- 2011-11
2011-01 -- 2012-12

These data are part of NACJD's Fast Track Release and are distributed as they were received from the data depositor. The files have been zipped by NACJD for release, but not checked or processed except for the removal of direct identifiers. Users should refer to the accompanying readme file for a brief description of the files available with this collection and consult the investigator(s) if further information is needed.

Please note for text data files with no variable names in the header, the column values corresponds with the variable names specified in the codebook, in the same order.

Provided in this release are 10 SAS code files and one Java script file used to manipulate and analyze the data.

Please note SAS data file gazeaggregated.sas7bdat does not include experiments with missing data. Please see the comments in SAS code file NIJCJRGazeDataEntry.sas for details.

The purpose of the study was to provide an objective evaluation of law enforcement officer driving behavior, visual attention, and situation awareness under standard patrol conditions. The goal of the study was to understand whether and how law enforcement officer's effectiveness during patrol tasks is impacted by dispatch communication and in-vehicle devices. The two general objectives were as follows:

  1. The primary objective was to evaluate the impact of processing dispatch-provided information on officer driving and patrol behaviors, officer visual scanning patterns, and officer situation awareness during simulated patrol activities. Achievement of this objective provided an understanding of how the combination of the driving task and patrol tasks affected overall officer performance.
  2. The secondary objective was to evaluate how increased information availability, such as in-car computer terminals and other technological devices, impacted officer performance.

The study used a within-subjects experimental design where each participant participated in a baseline condition, that is baseline patrol driving with no additional information, then the following experimental conditions that manipulated communication format and technology:

  • Patrol while monitoring natural auditory and static display.
  • Patrol while monitoring ten-code auditory and static display.
  • Patrol while monitoring natural auditory and dynamic display.
  • Patrol while monitoring ten-code auditory and dynamic display.

The driving simulator located at the Center for Advanced Vehicular Systems (CAVS) on the Mississippi State University campus was used and provided standard vehicle controls in a full sedan style cab. All driving scenarios were designed using the scenario development tool SimVista and were run using SimCreator (Real-Time Technologies, Inc.; Royal Oak, MI). To simulate mobile data terminal communications, a Sony Vaio VGN-T260P mini notebook computer with a screen size of 10.6in or 27cm was mounted to the right of the gear shift in the cab of the simulator, 91 cm from the driver head rest, with the seat in the position that most officers used. Gaze patterns were recorded using a faceLAB 4.6 stereo video based eye tracker and software (Seeing Machines; Canberra, Australia). Recorded gaze patterns were overlaid onto the scene and at least two experiment raters coded the gazes.

A total of 24 sworn law enforcement officers were recruited from Starkville Police Department, Columbus Police Department, and Tupelo Mississippi Police Department to participate in the experiment. Ten officers provided written consent to participate, but failed to complete the experiment. These individuals either withdrew voluntarily or were impacted by simulator sickness to the degree that the experimenter terminated the experiment. 14 law enforcement officers completed the experiment.

Cross-sectional

Law enforcement officers from Starkville Police Department, Columbus Police Department, and Tupelo Mississippi Police Department.

Individual
experimental data, observational data, survey data

Simulator Dataset

  • DAT files folder contains 138 raw text files exported from SimObserver, faceLAB, and Data Distillery software, with each file for a particular subject, drive number, and experiment rater. Each file contains 18 variables on video frame time stamp, simulator runtime for video frames, steering angle, brake pressure, throttle pressure, velocity, position from the center of the lane, X and Y screen coordinates of gaze vector intersection, X and Y screen coordinates of gaze vector intersection in pixels, identifier of the object intersected by gaze vector intersection, scripted event, whether steering status was left, straight or right, whether the vehicle was in motion or stopped, and experimenter rated gaze location.
  • DrivingData_CJR folder contains 68 text data files, with each file for a particular subject and drive number. Each file contains 12 variables on video frame time stamp, simulator runtime for video frames, steering angle, brake pressure, throttle pressure, velocity, position from the center of the lane, X and Y screen coordinates of gaze vector intersection, X and Y screen coordinates of gaze vector intersection in pixels, whether the vehicle was in motion or stopped, and whether steering status was left, straight, or right.
  • SAS data file aggregated.sas7bdat (n = 2,018,917) was created using SAS code NIJCJRDataEntry.sas (provided in this release) from the text data files in DrivingData_CJR folder. This data contains a total of 16 variables, the 12 variables in the DrivingData_CJR folder text data files and additional variables on subject number, subject's police department, drive number, and experimental condition.
  • SAS data file gazeaggregated.sas7bdat (n = 1,773,905) which was created using SAS code NIJCJRGazeDataEntry.sas (provided in this release) from the text data files in DrivingData_CJR folder. This data contains a total of 16 variables, the 12 variables in DrivingData_CJR folder text data files and additional variables on subject number, subject's police department, drive number, and experimental condition.
  • SAS data file drivemeans.sas7bdat (n = 68) which was created using SAS code DriveOrderMeans.sas (provided in this release) using aggregated.sas7bdat contains 20 variables on: subject number; experiment condition; drive number; data counts; mean steering angle, brake pressure, throttle pressure, velocity, and lane offset; and standard deviation of steering angle, brake pressure, throttle pressure, velocity, and lane offset.

Driver Point of Gaze Dataset

  • IRRComp Files folder contains 68 Excel files, with each file for a particular subject and experimental condition. Each Excel file contains 24 variables on video frame time stamp, simulator runtime for video frames, steering angle, brake pressure, throttle pressure, velocity, position from the center of the lane, X and Y screen coordinates of gaze vector intersection, X and Y screen coordinates of gaze vector intersection in pixels, identifier of the object intersected by gaze vector intersection, scripted event, whether steering status was left, straight or right, whether the vehicle was in motion or stopped, experimenter rated gaze location, both coders agree MDT was observed while vehicle was in motion, subject looking at MDT, subject looking at MDT while vehicle in motion, and time subject looking at MDT while vehicle in motion. Also, at the end of each worksheet is a set of statistics on percentage that raters agreed, percentage that raters agreed that mobile data terminal (MDT) was being observed, percentage of the entire drive frames that both coders agree MDT was observed while vehicle was in motion, percentage of MDT that occurred while vehicle was in motion, percentage of time moving was spent looking at MDT, number of separate instances of subject looking at MDT, time subject spent observing MDT during the entire drive, total time of drive, number of glances lasting less than two second, and total time of all glances lasting longer than two seconds.
  • MDTTtotals.txt text data file (n = 70) contains six variables on subject number, drive number, experimental conditions, percentage of the entire drive frames that both coders agree MDT was observed while vehicle was in motion, percentage of time moving was spent looking at MDT, number of separate instances of subject looking at MDT, and percentage of MDT that occurred while vehicle was in motion.
  • NIJCJRGazeTotals.xlsx Excel file (n = 70) contains eight variables on subject number, drive number, experimental conditions, number of gazes to mobile data terminal (MDT), number of gazes to MDT longer than two seconds, total time of gazes to MDT, sum of glazes to MDT longer than 2 seconds, and mean gaze time greater than two seconds.
  • SAS data file gazemeans.sas7bdat (n = 60) which was created using SAS code GazeDispersionMeans.sas (provided in this release) using gazeaggregated.sas7bdat contains 11 variables on: subject number; experiment condition; drive number; data counts; X and Y screen coordinates; mean of X and Y screen coordinates of gaze vector intersection; and standard deviation of X and Y screen coordinates of gaze vector intersection.
  • SAS data file mdttotals.sas7bdat (n = 70) which was created using SAS code MDTMeansANOVA.sas (provided in this release) using MDTTotals.txt contains six variables on subject number, experiment condition, drive number, proportion of drive spent looking at mobile data terminal (MDT) while vehicle is in motion, and ratio of time spent looking at MDT while vehicle is in motion and time spent looking at MDT across entire drive.

Situation Awareness Assessment Dataset

  • SATEST_DATA folder contains 254 text data files, with each file for a particular subject, event, drive number, and experimental condition. Each text data file contains six variables on subject number, drive number, experimental condition, event, event question, and response to event question.
  • SATest_Recode.txt text data file (n = 682) contains four variables on subject number, drive number, event question, and response accuracy.
  • SAS data file satest.sas7bdat (n = 682) which was created using SAS code SATestAnalyses.sas (provided in this release) using SATest_Recode.txt contains four variables on subject number, experiment condition, event question, and if the response was correct or not.

Subject Demographics and Motion Sickness/Simulator Sickness Questionnaire Dataset

Data_Forms_CJR.xlsx Excel file contains two worksheets.

  • MS-SSQComplete worksheet (n = 98) contains data from Motion Sickness/Simulator Sickness questionnaire for participants, a baseline and after each simulator run. It contains 31 variables on subject number, form number (1 being before any simulated driving, then after every subsequent simulated drive), level of general discomfort, fatigue, boredom, drowsiness, headache, eyestrain, difficulty focusing, salivation, sweating, nausea, difficulty concentrating, mental depression, fullness of the head, dizziness, vertigo, visual flashbacks, faintness, breathing, appetite, confusion, burping, vomiting, and other symptoms.
  • Demographics worksheet (n = 14) contains following 12 variables on subject number, age, gender, ethnicity, race, police academy attendance, length of training, additional training attended, type of training, education level, years of experience as an officer, and years of experience assigned to patrol.

A Likert-type scale was used.

2016-12-21

2016-12-21

2018-02-15 The citation of this study may have changed due to the new version control system that has been implemented. The previous citation was:
  • Williams, Carrick, and Daniel Carruth. Investigating the Impact of In-car Communication on Law Enforcement Officer Patrol Performance in an Advanced Driving Simulator in Mississippi, 2011. ICPSR34922-v1. Ann Arbor, MI: Inter-university Consortium for Political and Social Research [distributor], 2016-12-21. http://doi.org/10.3886/ICPSR34922.v1

Notes

  • These data are part of NACJD's Fast Track Release and are distributed as they were received from the data depositor. The files have been zipped by NACJD for release, but not checked or processed except for the removal of direct identifiers. Users should refer to the accompanying readme file for a brief description of the files available with this collection and consult the investigator(s) if further information is needed.

  • The public-use data files in this collection are available for access by the general public. Access does not require affiliation with an ICPSR member institution.

  • One or more files in this data collection have special restrictions. Restricted data files are not available for direct download from the website; click on the Restricted Data button to learn more.

  • The citation of this study may have changed due to the new version control system that has been implemented.
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This dataset is maintained and distributed by the National Archive of Criminal Justice Data (NACJD), the criminal justice archive within ICPSR. NACJD is primarily sponsored by three agencies within the U.S. Department of Justice: the Bureau of Justice Statistics, the National Institute of Justice, and the Office of Juvenile Justice and Delinquency Prevention.