Last week I participated in the work of a workshop organized by the FHWA which explored utilizing various data sources for surface transportation human factors research. Here are some impressions from the workshop.
Bicycles are cool
Marco Dozza explores the use of bicycles and has a fleet of instrumented bikes. I really liked the elegance of his approach.
We can use technology to warn pedestrians (even when they have headphones)
Toru Hagiwara and Hidekatsu Hamaoka discussed research on protecting pedestrians in crosswalks. I can relate to this: ever since I started walking with kids, I’m sorely aware of the dangers of crosswalks.
We need a variety of data sources
Michael Manser, Sue Chrysler, John Lee and Linda Boyle gave presentations on a variety of data sources they’ve used: from laboratory studies to naturalistic driving data. They all agree that there’s a need to combine results from different data sources in order to find solutions to human factors problems. I was really impressed with John Lee’s discussion of the use of Twitter to understand traffic.
Panel discussions can be informative…
… when you have a skilled moderator (Don Fisher) and engaged participants (the presenters listed above). Don’s theme for the discussion (the 3 Cs): our data should be comprehensive and complementary, but it is sometimes also contradictory. The discussion brought up ideas such as:
- there’s a need for standardization (see Paul Green‘s work on SAE J2944 );
- Linda Boyle points out that there’s a fourth C: confusion;
- Sue Chrysler points out that discussions about data often focus on the “how?” (how can we collect, process, interpret data?). But we need to first resolve the “why?” and “what?” questions. I really appreciated this comment, as it is the central point I make in my ECE 900 course.
 Paul Green, “Standard Definitions for Driving Measures and Statistics: Overview and Status of Recommended Practice J2944,” AutomotiveUI 2013