Apollo R Transport Choice Modeling

I’m designing a discrete choice experiment that explores consumer preferences in the transportation sector, focusing exclusively on private-vehicle options. I have drafted the attributes and levels; now I need a robust Apollo-R workflow that takes the experiment from experimental design through to model estimation and concise reporting.

What I expect from you:
• Clean, well-commented R scripts that build the choice sets, simulate or load the survey data, and estimate the models (MNL first, then Mixed Logit/Latent Class if appropriate) using the Apollo package.
• Clear documentation of each step so I can rerun the code with new data later.
• A short technical memo (PDF or Word) that summarises the results, interprets key parameters, and flags any policy or marketing insights about private-vehicle choice.
• All outputs should run on R 4.x with only CRAN dependencies plus Apollo.

Acceptance will be based on:
1. Code runs end-to-end without errors on my machine.
2. Fit statistics and willingness-to-pay measures are reported and reasonable.
3. Memo explains findings in plain language for a non-technical audience.

If you have prior examples of Apollo implementations or published transport DCE work, feel free to point me to them—seeing similar projects will speed up our collaboration.