Alex Chen and Chris Deits Statistics 566 – Final Presentation

1. Determining the Direct Effect of Triazolam on the increase of a driver’s steering entropy in the presence of simulator sickness in a simulated driving environment Alex Chen and Chris Deits Statistics 566 – Final Presentation

2. Background

3. Perspective: Driving as a Complex Task • Driving is one of the most complex tasks performed by people • Driving requires close coordination between different senses • Visual • Haptic (Touch) • Auditory • Vestibular (Balance – Motion) • Driving is cognitively taxing on people • Requires constant decision making on the part of the driving due to ever-changing environment conditions • Knowledge of this decision process is first step to understand the behavior of drivers. • Decision making in driving context can be seen a relatively simple feedback loop. • Decision making developed as mental model consists of four distinct states • Perception • Recognition • Action Selection • Action Implementation • Any disruption or inhibiting of these 4 cognitive processes can lead to unfortunate consequences when operating a vehicle.

4. Human Decision Making Process Attentional resources Response execution Receptors Response selection Perception Decision making Long-term memory Recognition Working memory Controlled system

5. Human Decision Making Process Attentional resources Response execution Receptors Response selection Perception Decision making Long-term memory Recognition Working memory Controlled system

6. Human Decision Making Process Attentional resources Response execution Receptors Response selection Perception Decision making Long-term memory Recognition Working memory Controlled system

7. Human Decision Making Process Attentional resources Response execution Receptors Response selection Perception Decision making Long-term memory Recognition Working memory Controlled system

8. Driver Fatigue and Drugs • Drowsy driving plays a role in an estimated 76,000 – 100,000 crashes each year in the US (Stutts et. al., 2003) • 50% of the accidents involving commercial drivers is fatigue related (Wickens et al., 2004) • Benzodiazepines, commonly used as sleep aids, were the 2nd most used psychoactive drug among crash-involved commercial drivers (US DOT, 2010) • Toxicology labs that test for the presence of the drug rate Ambien among the top 10 drugs found in impaired drivers.(“Zombie Drivers,” NY Times , 03/08/06) • Furthermore, these psychoactive drugs can have even more worrisome effects • One such is ”Zombie drivers” which when people on these drugs operate vehicle in their sleep or in a near sleep fashion

9. Project Data

10. Study Design Background Project Data Characteristics • The data was sourced from a joint research project between the University of Iowa and the University of Washington. • Study was randomized, complete cross-over design • The study’s intention was to investigate effect of a common sleeping pill, Triazolam, on commercial bus driver behavior • The study was performed in fully immersive driving simulator • Participant were recruited from the U. Iowa and Iowa City Metro System • 24 total participants • Three Dose levels investigated: Placebo, 0.125 mg. and 0.250mg of Triazolam • 3 Drives Investigated • Occurred 2 hrs. after drug administration • These were chose to maximize the influence of Triazolam on participants

11. Project Goals • We want to model the driving behavior of the driver under the influence of the drug, since we need to know whether or not the drug caused driving impairments (measured indirectly through steering entropy), and if so, if the drug mediated the impairments through certain mechanisms that we tried to measure • Simulator sickness can affect a person perception abilities, divert attentional and can affect decision response

12. Explanation of Entropy Basically, entropy is a measure of randomness. The higher the entropy, the higher the randomness of the distribution, and the more unpredictable any given next letter will be. Entropy is usually maximized when p(x_i) is evenly split among all n possibilities (in other words, when you really cannot predict what the next step will be any better than chance). Take a standard example: a coin flip. Here, we just have n = 2 (heads and tails). Entropy is maximized when the probability of heads is equal to the probability of tails (or ½)

13. Steering entropy has previously been used as a measure of workload, investigating how much workload increases when performing a secondary task whilst driving. When performing a secondary task, driving becomes less smooth and attention to the driving task decreases. When drivers are impaired, attention to the driving task reduces in a similar way. In this pre-trial experiment, driving in a purposely erratic manner was used to simulate impairment. This impairment manifests itself in a decrease of attention to the driving task and less smooth driving Taken from http://www.ectri.org/YRS03/Session-6/Flint.pdf

14. Dependent Measure: Steering Entropy • Steering Entropy (SE) is a measure of the randomness in steering control • Prediction Error: e(n) = qa(n) - qp(n), at time n • qp(n) - predicted steering angle • qa(n) - actual steering angle • qp(n) is calculated using a second order Taylor expansion of steering angle over time • The prediction error is approximately normally distributed with: e(n) ~ N(0, g). • The est. std. dev. of e(n), a derivative of the traditional measure of SE (Nakayama, 2000), at the 95th quantile, 2g, was used as the dependent measure • Any changes in overall steering entropy will be reflected in the change of the value of the std. dev. of e(n) at the 95th quantile, 2g • So basically – the higher the entropy, the more unpredictable the vehicle is, which presumably translates to higher accident rates

15. Steering Entropy Example

16. Independent Measures Simulator Sickness Dose Level • There were 3 Triazolam dose levels: Placebo, 0.125 mg. and 0.250mg • Peak Plasma levels of Triazolam reach maximum levels within 2 hours of ingestion and has a mean plasma half-life of 1.5 to 5.5 hrs. • Simulator sickness is a common presence in experiments using vehicle simulators • Simulator sickness can take on a range of symptoms, from general nausea to affecting perception and the vision of the drivers using the simulator. • Simulator sickness was measured via a post drive questionnaire (Kennedy et al.) • For each drive, participants will be dichotomized into those who experienced sim sickness and those who did not.

17. Descriptive Statistics Incidence of Simulator Sickness

18. Steering Entropy By Individuals

19. Analysis

20. Dose and Sickness Relationship

21. Entropy Modeling • In order to model the repeated measures data, a Linear Mixed effects model was fitted • The a random intercept for each participant was estimated for the random effect • An unstructured correlation structure was used for the within subject correlation • There was no significant effect, at the a =0.5 level, found for any variable • Both dose levels were marginally significant and showed lower levels of steering entropy LMM Effects Estimates

22. Conclusions • While the dose level of Triazolam does seem to have an effect on the incidence of simulator sickness. • For the effect of Triazolam on steering entropy, while not statistically significant, does show a decrease for both levels. • These lower steering entropy levels may indicate a lower incidence of corrective steering than they would normally. This may indicate more

23. Future Work • Development of a Bayesian Model Framework to help compensate for relatively small sample size. • Development of the a full causal model taking into account other variables • Investigation of effects of Triazolam on other behavior outcome measures • Average speed, Standard deviation of speed, Steering wheel movement speed and reversal frequency, Frequency of accelerator pedal pressures, Frequency of brake pedal pressures • Define relationship between steering entropy and lane deviation measures

24. References • Mourant, R. R. and T. R. Thattacheny (2000). Simulator sickness in a virtual environments driving simulator. In Proceedings of the IEA 2000/HFES 2000 Congress, pp.  534-537. • Stutts el al (2003) Driver risk factors for sleep-related crashes, Accident Analysis & Prevention, 35, 1, 321-331 • US DOT (2010) Federal Motor Carrier Safety Administration - Large Truck Crash Causation Study, accessed on Nov 20, 2010 from http://www -nass.nhtsa.dot.gov/LTCCS_PUB/SEARCHFORM.ASPX • Nakayama et al. (1999) Development of a steering entropy method for evaluating driver workload, Paper presented at SAE International Congress and Exposition, Detroit, MI. • Wickens et. al, (2004) “ Introduction to Human Factors Engineering, ” 2nd Edition, Pearson Prentice Hall • Kennedy et al., “Simulator Sickness Questionnaire: An Enhanced Method for Quantifying Simulator Sickness,”The International Journal of Aviation Psychology, 1993, 3(3): 203-220. • Pinherio, J. C., & Bates, D. M. (2000). Mixed-Effect Models in S and S-PLUS. New York: Springer. • Greenblatt, D. J., D. R. Abernethy, A. Locniskar, J. S. Harmatz, R. A. Limjuco, and R. I. Shader (1984, July). Effect of age, gender, and obesity on midazolam kinetics. Anesthesiology 61 (1), 27-35. • Laurell, H. and J. Törnros (1986, March). The carry-over effects of triazolam compared with nitrazepam and placebo in acute emergency driving situations and in monotonous simulated driving. Actapharmacologica et toxicologica58 (3), 182-186.

25. Supplemental Material