Travel time data for modelers the do s don ts and maybes sam granato ohio dot
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Travel time data for modelers - the Do’s, Don’ts, and Maybes: Sam Granato, Ohio DOT. Why do we need data like this?. Because our customers don’t care about volume to “capacity” ratios, instead they want to know:. In the beginning – floating car surveys and spot speed sensors.

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Travel time data for modelers the do s don ts and maybes sam granato ohio dot

Travel time data for modelers - the Do’s, Don’ts, and Maybes:Sam Granato, Ohio DOT


Why do we need data like this
Why do we need data like this?

  • Because our customers don’t care about volume to “capacity” ratios, instead they want to know:


In the beginning floating car surveys and spot speed sensors
In the beginning – floating car surveys and spot speed sensors

  • CMS / CMAQ project effectiveness

  • Used for MPO travel model validation since 1990’s to better model congestion & Level of Service

  • Statewide, developed for “speed table” by type of road – both average and running speeds (to start up some “junction-based” model networks in Ohio)


Then the same but more and more things to use them for
Then, the same but more (and more things to use them for) sensors

  • “high sample size” floating car (arterials in Parkersburg/Marietta and freeways in Cleveland)

  • Can use to measure variability in travel time as well as more confident average, and how the variability changes as function of distance/# segments (i.e. from link-level to travel-path level


New sources of speed data
New sensorsSources of Speed Data

  • “Archive” data from vehicle fleets & cell probes

  • Extensive road network coverage, could replace or reduce/redeploy need for “floating car” surveys



Gps data availability
GPS Data availability : sensors

  • About 33,000 directional miles of TMC roadway statewide (including five miles into adjacent states)


Quality checks for any biases first compare to atr sites mostly rural freeways
Quality checks for any “biases”: sensorsFirst, compare to ATR sites (mostly rural freeways):

  • Differences exists in how these are measured (spot vs space mean speeds)

  • Statewide, average speeds higher on the ATR’s (about 7%)

  • Check for vehicle class based on WIM station locations on I-70 (Licking county) and I-77 (Noble county).


Quality checks for any biases second compare to statewide floating car surveys
Quality checks for any “biases”: sensorsSecond, compare to statewide floating car surveys

  • Differences exist in route segmentation

  • Very small sample sizes in the floating car surveys

  • Overall, in close agreement statewide on average speeds including by time of day


Gps data vs floating car uses limitations
GPS data ( sensorsvs floating car)– uses & limitations

  • Far higher sample sizes, more versatility on hour of day / day of week / season of year

  • Good for overall speed validation of model on average values, not necessarily for variability/reliability

  • Depending on level of access, might not have ability to see the impact of distance on reliability / journey time

  • “Buffer index” measures found to measure system-level, not user-level reliability


Local sample speed data provided us both (expected) sample sizes by corridor/HOD AND percentile values



Sample finding 1 a speed does not vary that much by time of day
Sample finding #1-A: Speed does not vary that much by time (and LOS) very wellof day

  • Volume offset by driver and vehicle characteristics

  • Signal timing, parking management


Sample finding 2 curves and railroad crossings don t seem to slow us down that much
Sample finding #2: Curves and Railroad crossings don’t (and LOS) very wellseem to slow us down that much


Questions
Questions? (and LOS) very well


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