TranspoCamp and TRB Recap

So last week these two little get-togethers happened - Transportation Camp and the Transportation Research Board Annual Meeting.  This post is the stuff I have to talk about related to both.

Transportation Camp

  • Lots of discussion about transit.  Seems nearly all sessions had the word 'transit' used once.
  • There was a lot of technical discussion that were incremental improvements over current methods:
    • Object Tracking with Raspberry Pi (my big takeaway from this is to go get the latest RPi image for the Java support)
    • Transit On-Board Surveys
      • Using Nexus tablets isn't all that different from the PDAs NuStats used on our Transit On-Board Survey in 2010
      • Their code was noted as open source... definitely worth a look
      • Their interface is an improvement over the PDAs because of the ability to show maps
        • There is a possibility that this could be used to reduce geocoding overhead - the tablet could do it on the fly and show it to the respondent for confirmation... there is a privacy issue here
      • Their tools for tracking surveys were awesome
      • This was done in the Philippines
    • Tracking Taxis
      • This was also done in the Philippines
      • They built some cool tracking tools
      • They used the data as floating car travel time surveys
    • Bicycle Integration
      • Bicycle planners love multi-day surveys - additional days means that they have more trips to analyze
        • One planner was using the NHTS for data - one day, not a lot of trips
      • CycleTracks!
      • RackSpotter - crowd-sourced bicycle rack data

TRB Annual Meeting

  • Applications
  • Data
    • Social Media took center stage for part of the sessions.  There were two I scheduled for, although one I didn't make it to.  There is a lot of research looking in to how we can use social media in modeling, but it is not yet ripe for use.
    • There are important balancing acts among the context of data vs. the presentation of data  and the cost to collect the data vs. the cost to analyze data
    • More data makes decision making more difficult
    • As a profession, we need to concentrate on what decision is going to be made from data
      • We have a tendency to overwhelm decision makers
      • We frequently tell a decision maker how a watch is made when all they want to know is the time
    • Open data is important, but also open analysis is important
    • We always need to differentiate modeled data vs. observed data
    • Lots of lesser-quality data still has uses
      • Predictive modeling, like typing and driving
      • Sometimes lesser-quality data can be embellished with good data
    • GPS data modeling is still an emerging topic
      • Two presentations that I saw about getting the purpose of a trip
      • One presentation that I saw about getting the mode of a trip
  • Testing Models and the Next 50 Years of Modeling
    • Lots of discussion related to testing models
    • FHWA and OKI and PSRC are working on a project relating to testing models
    • I actually had a lot more written here, but unfortunately issues in my area that directly relate to my work means that it really isn't within my best interest to post it here.  It's unfortunate, because it is some good stuff (and it will be used moving forward in my work at OKI).

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