Human behavior and automated driving features

Weekly check-ins on Tuesdays (noon-1pm, starting June 8) and Thursdays (11am-noon, starting June 3)

Goal

Learn basic survey data analysis through hands-on experience with the State of the State Survey (SOSS)

Schedule

Week 1 (June 1- June 4): Identifying relevant variables to include in a model

Question:

1. In theory, what factors (including sociodemographic factors) may or may not explain acceptance of driver assistance technologies?
2. In theory, what factors (including sociodemographic factors) may or may not explain interests in owning or leasing self-driving vehicles?

Task:

Review and summarize existing literature on these topics to answer the above questions. e.g. Acceptance of the advanced driver assistance systems applications does not depend on people’s characteristics, including age, driving experience, gender, or frequency of navigation device usage (source: https://www.tandfonline.com/doi/full/10.1080/15472450.2012.716646).

Goal of the week:

Submission of draft write-up of literature (~2000 words) you read and found for this week and the two previous weeks on Overleaf. Remember each paragraph should capture one topic and lead with the main summary of that paragraph

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Week 2 (June 7- 11): Preparing data for analysis

Task:

1. Load and clean the SOSS data; get familiar with it
2. Generate a table of sample statistics (with weights preferably)

Goal of the week:

Submission of summary statistics and draft write-up of the table (you always have to summarize in publication of what you are presenting in tables & figures) in Overleaf

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Week 3 (June 14- 18): Analyzing acceptance of driver assistance technologies

Question:

1. How comfortable are Michiganders with driver assistance technologies?
2. Are there any differences in Michiganders’ comfortability with driver assistance technologies among different demographics?

Task:

1. Descriptively analyze driving18, driving19, driving20, and driving21 to answer question 1
2. Model driving18, driving19, driving20, and driving21 with variables identified in Week 1 to answer question 2 (use logistic regressions or other models that you think make sense)

Goal of the week:

Submission of draft write-up of analysis including graphs in Overleaf

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Week 4 (June 21- 25): Analyzing driving behavior change due to automated features

Question:

1. How likely are Michiganders to change their driving behaviors if their vehicles have collision avoidance system (i.e. alert drivers of the risk of a collision and assist them by automatically braking or steering to avoid it)?
2. How likely are Michiganders to change their driving behaviors if their vehicles do not have collision avoidance system but others do?
3. Have Michiganders heard of self-driving vehicles?
4. How interested are Michiganders in owning or leasing a completely self-driving vehicle in the future? Any sociodemographic difference?

Task:

Analyze driving22, driving23, driving16, driving17 with similar techniques learned in Week 3 to answer the above questions

Goal of the week:

Submission of draft write-up of analysis including graphs in Overleaf

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Week 5 (June 28- July 2): Revisions and methodology

Task:

1. Revise write-up of findings from previous weeks
2. Write up methodology and include an assessment of limitations in Overleaf

Goal of the week:

1. Revise and streamline your entire analysis (~1200 words) in Overleaf (no more than four graphs or tables in analysis)
2. Submission of draft write-up of methodology including data collection and analysis as well as limitation of both (~500 words)