month of the year versus morning commute time (y1 vs. x3) ANOVA results showed even less of an effect:

Cypress-Fairbanks ISD
Whether or not the local school district was in session proved to be the greatest measured variable in explaining the morning commute time variation (y1 vs. x6):

Evening Commute ANOVAs

Day of the Work Week
While the day of the week proved to have a significant impact on the morning commute, the evening commute showed no such relationship (y2 vs. x1):

Week of the Month
Again, the week of the month did not explain the commute-time variation (y2 vs. x2):

Month of the Year
Another change from the morning results, the month of the year proved to have a significant effect, with February, April, and November showing the longest evening commute times (y2 vs. x3):

Cypress-Fairbanks ISD
The school session again showed significant influence, but it was not as strong in the evening as in the morning (y2 vs. x6):

Departure Time Analysis
For the continuous variable of departure time, I plotted smoothed curves of the mean commute time at each minute.

The morning departure-time plot shows relatively long commute times until about 7:40 AM, at which time a gradual decrease starts that continues in a largely linear fashion for the next hour. After 8:40 AM, traffic appears to have minimal impact. (y1 vs. x4):

The evening departure-time plot shows a peak commute time at about 5:10 PM, tapering off linearly through the next two or so hours. Departure times prior to 5:00 PM showed erratic results, but it is obvious that traffic played a decreasing role in evening commute time duration moving back through 4:00 PM, before which its influence is noticeable, but slight. (y2 vs. x5):

I usually leave home at 8:00 AM and work at 5:30 PM, but a 30-minute delay of each looks like it would shave five minutes off the morning commute and about 2.5 minutes off the evening one. Additional half-hour delays bring 2.5 minutes of commute time savings in the evening, but little to no savings in the morning. Slightly earlier departure times appear to result in commute-time increases for both trips. Moving back past 4:30 in the evening brings slight improvement in the evening commute, but savings in the morning would most likely require leaving before 6:30 AM.

Conclusions
Given the above data and analysis, what can be done to improve my commute times? Changing my morning or evening departure time looks promising. The best bet appears to be moving my schedule out a half-hour to 8:30 AM and 6:00 PM, bringing significant savings (about 7.5 minutes of commute time per day) without getting too far from normal business hours. Spread out over 50 work weeks, that results in a total savings of over 30 hours a year -– the equivalent of a 38-percent boost to my existing 80 hours of vacation.

Departure time isn't the say-all, however, and making this shift won't always result in a smooth and fast commute. The day of the week in the morning and the month of the year in the evening both have significant impacts, and whether or not school is in session affects both. I could possibly squeeze out a few more minutes of savings by scheduling my vacation days to align with the potentially longest commutes (e.g., non-Friday school days in the months of November, February and April), but the data shows significant variation up and above that described by the measured variables -– much likely due to factors outside of the control of the commuter (e.g., weather, wrecks, breakdowns, response to traffic predictions, etc.).

That said, the commuter may have more control than it appears. Adjusting your commute times and rearranging your vacation schedule will probably help in the meantime, but getting cars off the road is the only sure solution, and one that is within commuters' sphere of influence. It might require punching your "free reign" in the gut, but getting involved in your community by writing your congressperson or attending city council meetings in promotion/defense of improved mass transit could be the most effective way to "curb" your drive times in the long run.

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