Accident Rates of Novice Drivers with Simulator Training

Transcription

1 Accident Rates of Novice Drivers with Simulator Training R. Wade Allen*, George D. Park*, Marcia L. Cook*, Dary Fiorentino** *STI, **SCRI 2007 TRB Annual Meeting Human Factors Workshop on Teen Drivers This presentation concerns results of a research project on Novice Driver Training that we are conducting for the US Centers for Disease Control. This presentation describes the accident history of simulator trained novice drivers in comparison to traditionally trained drivers. 1

2 Project Objectives Develop PC Based Training and Assessment System Train 500 Unlicensed High School Students Compare Violation and Accident History of Simulator Trained Subjects with Traditionally Trained Drivers (Transfer of Training) 1/1/ TRB Annual Meetng 2 Three phases to project: 1) develop training system; 2) train novice drivers; 3) analyze accident rates Just recently received accident data, this presentation includes preliminary results 2

3 Hypothesis: Simulator Training Can Transfer to On- Road Performance and Reduce Novice Driver Accident Rate 1/1/ TRB Annual Meetng 3 Does simulator training reduce on-road accidents???? 3

4 Training Objectives Transmit knowledge relevant to driving scenarios (rules of road, TCD s) Train situation awareness and hazard perception Train decision making and appropriate control response (steering, braking, turn indicator) 1/1/ TRB Annual Meetng 4 A Power Point orientation was used to present information important for driving the simulation Information included background on TCD s (traffic control devices including markings, signs and signals), rules of the road and hazard scenarios. Driving scenarios contained a wide variety of hazards designed to train situation awareness, decision making and appropriate control response (steering, braking, turn indicator). 4

5 NOVICE DRIVER HARDWARE CONFIGURATIONS Palos Verdes, San Diego Hawthorne Culver City 1/1/ TRB Annual Meetng 5 Three levels of simulator fidelity: 1) High school computer lab, converted computers, low cost desk top set up; 2) Full cab, curved screen, high cost; 3) Desk top wide angle display, medium cost. Two settings: 1) research labs (Hawthorne and Culver City}; 2) High schools (Palos Verdes, San Diego). 5

6 Subject Recruitment Geographic Region Recruiting Method Simulator Configuration Number of Participants Hawthorne, CA DMV Office Wide FOV Vehicle Cab 159 Culver City, CA DMV Office Wide FOV Desktop 180 Palos Verdes, CA High School Drivers Ed. Single Monitor Desktop 147 San Diego, CA High School Drivers Ed. Single Monitor Desktop 68 1/1/ TRB Annual Meetng 6 DMV (Dept. of Motor Vehicles) office: subjects randomly selected from line while waiting to get learner s permit. Given incentives to participate. High School Driver s Education classes at high schools: all students in class were recruited. 6

7 Training Protocol Orientation and knowledge presentation Minimum of six minute driving scenarios with multiple hazardous events Possible to graduate on sixth trial if performance criteria met Up to three additional trials allowed to meet performance criteria 85 % of subjects graduated 1/1/ TRB Annual Meetng 7 Training protocol designed to be consistent with traditional driver education curricula. Presentation varied somewhat at each geographical location. 7

8 Age & Gender Distribution, N = 554 Number of Participants Females Males Age (years) 1/1/ TRB Annual Meetng 8 Median age 15 (eligible for learners permit) Slightly more females Majority are 16 and under 8

9 Configuration Type & Gender Distribution Number of Participants Single Monitor Three Monitor Vehicle cab Females Males Configuration Type 1/1/ TRB Annual Meetng 9 Gender distribution about even for single monitor system (high schools) More females in laboratory groups (three monitor and vehicle cab) 9

10 Participant Age at Time of Driver's License Issue Number of Participants Age (years) Females Males 1/1/ TRB Annual Meetng 10 Significant licensure at age 16 Another spike at age 18 (many students wait to age 18 to avoid GDL restrictions) 10

11 Time From Simulator Training to Licenced Driving Distribution by Geographic Region 45 Number of Participants San Diego Palos Verdes Hawthorne Culver City Simulator Training Date to Driver's License Issue Date (months) 1/1/ TRB Annual Meetng 11 Median time between training and licensure is about 8 months. Majority of subjects licensed within 18 months. Some subjects have significant delays in licensure (beyond 2 years) 11

12 Training Date to Licensure Distributions % of Drivers Hawthorne Culver City/West LA Palos Verdes San Diego Training Date to DL Date 1/1/ TRB Annual Meetng 12 Licensure delayed most for schools (Palos Verdes, San Diego). Culver City (lab) fastest licensure. Some Hawthorne recruitment came from announcements at local high schools. This may be responsible for licensure delay over Culver City. 12

13 Training Date to Accident Date Distributions Cummulative % Accidents Hawthorne Culver City/West LA Palos Verdes San Diego Training Date to Accident Date (months) 1/1/ TRB Annual Meetng 13 Accident accumulation distributions relative to training date are similar for each group. San Diego the most variable (smallest population). 13

14 Accident Rate by Group 0.07 Accident Count / Number of Drivers Culver City Hawthorne Palos Verdes San Diego Time after Driver's License Issue Date (Months) 1/1/ TRB Annual Meetng 14 Accident rate somewhat sparse when segmented by geographic group Variability in San Diego group apparent 14

15 Time Since Simulator Training by Geographic Region Number of Participants San Diego Palos Verdes Hawthorne Culver City Simulator Training Date to DMV Record Date (months) 1/1/ TRB Annual Meetng 15 DMV events (accidents and violations) occur over three years from training date 15

16 Total Accident Counts = 98, Including Before and After DL Issue Date Number ofaccidents Driver's License Issue Date to Accident Date (months) 1/1/ TRB Annual Meetng 16 Accidents occurring before licensure Accidents peak in first three months of licensure 16

17 Accident Status Distribution by Geographic Area Number of Participants , 81.1% 141, 88.7% 124, 84.4 % 34, 18.9% 18, 11.3% 23, 15.6% No Accidents Accidents 55, 80.9% 13, 19.1% 0 Culver City Haw thorne Palos Verdes San Diego Geographic Location 1/1/ TRB Annual Meetng 17 Hawthorne (lab) has lowest overall accident rate (11.3%) 17

18 Accident Status Distribution by Simulator Configuration Type Number of Participants , 83.3% 146, 81.1% 141, 88.7% 36, 16.7% 34, 18.9% 18, 11.3% Single Monitor Desktop Wide FOV Desktop Wide FOV Vehicle Cab Simulator Configuration Type No Accidents Accidents 1/1/ TRB Annual Meetng 18 Wide FOV Vehicle Cab gives the lowest accident rate 18

19 Number of Participants Accident Status Distribution by FOV Type & Training Environment 289, 84.8% 52, 15.3% Wide FOV & Laboratory 177, 83.1% 36, 16.9% Single Monitor Desktop PC & Classroom FOV Type & Training Environment No Accidents Accidents 1/1/ TRB Annual Meetng 19 Wide FOV gives the lowest accident rate 19

20 Overall CA DMV Record Status by Gender Number of Participants Males Females clean not clean CA DMV Record Status 1/1/ TRB Annual Meetng 20 Males more likely to have DMV records (accidents and tickets) 20

21 Accident Rate Relative to Training Date Hawthorne Culver City Palos Verdes San Diego y = x R 2 = Accident Rate y = x R 2 = y = x R 2 = y = x R 2 = Months from Training Date 1/1/ TRB Annual Meetng 21 Consider cumulative accident rates to get fair group comparisons Each 3 month period rate computed as number of accidents divided by number of drivers Hawthorne group (wide FOV vehicle cab) gives lowest accident rate 21

22 TD Regression Analysis Summary Experimental Group R 2 Slope 95% Lower Conf. Int. 95% Upper Conf. Int. Hawthorne Culver City Palos Verdes San Diego /1/ TRB Annual Meetng 22 Confidence intervals show that Hawthorne group has significantly lower accident rate than other groups. 22

23 Accident Rates for Traditionally Trained Drivers Mayhew 2003 (Nova Scotia) Cum Mayhew Cum Janke, et al Cum Male Cum Female y = x R 2 = Accident Rate 0.20 y = x R 2 = y = x R 2 = Months Since DL 1/1/ TRB Annual Meetng 23 Mayhew and Janke data give a good reference for typical accident rates of traditionally trained drivers Regression shows average accident rate is about accidents per driver or 8.4% for novice drivers 23

24 California Accident Rates 0.12 Accident Rate per Driver Janke, et al Male Female Age (years) 1/1/ TRB Annual Meetng 24 Novice driver accident rates over twice experienced driver rates. About 9% of drivers having accidents 24

25 Accident Rate Relative to DL Date Accident Rate/10000 Drivers Hawthorne Culver City Palos Verdes y = x R 2 = San Diego y = x R 2 = y = x R 2 = y = x R 2 = y = x R 2 = y = x R 2 = Months from DL 1/1/ TRB Annual Meetng 25 Now compare simulator trained driver groups with Mayhew and Janke data Accident rate versus months from drivers license allows us to compare simulator trained population against traditionally trained drivers. Hawthorne accident rate one third of Mayhew/Janke rate Culver City about three quarters of Mayhew/Janke rate 25

26 DL Regression Analysis Summary Experimental Group R 2 Slope 95% Lower Conf. Int. 95% Upper Conf. Int. Hawthorne Culver City Palos Verdes San Diego Mayhew /1/ TRB Annual Meetng 26 Confidence intervals show that Hawthorne and Culver City accident rates significantly lower than Mayhew/Janke rate. 26

27 Confounding Variables Experimental Group Setting Socio- Economic Driving Environment Hawthorne Research Lab Researchers Low to middle Urban Culver City Research Lab Researchers Low to middle Urban Palos Verdes Computer Lab Teaching Aide High Hilly, winding roads San Diego Classroom Teacher Middle Hilly, winding roads 1/1/ TRB Annual Meetng 27 Various considerations have confounded the accident comparisons of the various groups 27

28 Concluding Remarks Simulator training can reduce novice driver accident rate Efficacy improves with simulator fidelity Adequate level of fidelity not clear Role of driver education and instructors not clear 1/1/ TRB Annual Meetng 28 Preliminary conclusions 28

29 Future Research Questions Effectiveness of e-learning e and Computer Based Instruction? Instructor interaction? Developmental factors? Necessary level of simulator fidelity? 1/1/ TRB Annual Meetng 29 Thoughts for future research 29

30 Speed vs Accuracy Tradeoff 1.4 TTC (seconds) Conservative Final Training Single Monitor 3 Monitor Cab Female Male Mid Training Average Speed (mph) Initial Training Aggressive 1/1/ TRB Annual Meetng 30 Novice drivers initially get more aggressive with training, but in final trials when approaching graduation become more conservative. Females more conservative. Conservatism increases with FOV and fidelity. 30