1953 Detroit Metropolitan Area Traffic Study – Data Discovered …

Jeffrey Lin calls my  attention to recovered microdata from the 1953 Detroit Metropolitan Area Traffic Study, available here:

He re-discovered these data at the UCLA data archive and asked the UCLA library to post it to Dataverse. This is one of the first travel surveys, led by Douglas Carroll himself (the progenitor of the four-step transportation planning model).

In a recent working paper, “Freeway Revolts!” Lin and Jeff Brinkman use these data to estimate the “barrier effects” of urban highways.

The Metropolitan Travel Survey Archive remains a useful place for historic surveys, and newer surveys can be found at the NREL Transportation Secure Data Center.

Overestimation and underestimation of travel time on commute trips: GPS vs. self- reporting

Recently published:

  • Carrion, Carlos and David Levinson (2019) Overestimation and underestimation of travel time on commute trips: GPS vs. self- reporting. Urban Science. 3(3), 70 [doi]

The underlying structure of road networks (e.g., circuity, relative discontinuity) contributes to the travel time perception of travelers. This study considers additional factors (e.g., arrival flexibility, access to traffic information) and tests nonlinearities linking perception of travel time. These factors are linked to four categories according to time perception research in psychology: temporal relevance, temporal uncertainty, and temporal expectancies; task complexity, absorption, and attentional deployment; and affective elements. This study estimates the relationship on data collected from commuters recruited from a previous GPS-based study in the Minneapolis-St. Paul region consisting of trips from home to work and back. For these work trips, the subjects’ self-reported travel times and the subjects’ travel times measured by GPS devices were collected. The results indicate that nonlinearities are present for road network attributes. Furthermore, the additional factors (e.g., arrival flexibility, access to traffic information) influence the travel time perception of travelers.

Figure 1 Proportion of trips according to travel time of commute from GPS data and survey data: GPS vs. stated; expected vs. GPS; stated vs. expected.
Figure 1 Proportion of trips according to travel time of commute from GPS data and survey data: GPS vs. stated; expected vs. GPS; stated vs. expected.

Transport Rankings

The 2019 Shanghai university rankings are out. In the Transport Science & Technology subject, the University of Sydney is ranked #5 in the world:

 

  1. Beijing Jiaotong University
  2. Tsinghua University
  3. Delft University of Technology
  4. Southeast University
  5. University of Sydney
  6. Tongji University
  7. Massachusetts Institute of Technology
  8. University of British Columbia
  9. University of California Berkeley
  10. Shanghai Jiao Tong University

Our Civil Engineering program moved to 24th according to these rankings. The University did well overall. While I don’t much trust rankings, I’ll brag anyway. I am proud to be a part of this. If you too want to be a part of this, get a degree at the University of Sydney. Our new Master of Transport Program is available now …