Access Across America: Auto 2015

CTS Catalyst September 2016 just came out, and announces our Access Across America: Auto 2015 study: Study estimates accessibility to jobs by auto in U.S. cities. The article is reprinted below:

Map of Accessibility to jobs by auto in U.S.
Accessibility to jobs by auto

A new report from the University’s Accessibility Observatory estimates the accessibility to jobs by auto for each of the 11 million U.S. census blocks and analyzes these data in the 50 largest (by population) metropolitan areas.

“Accessibility is the ease and feasibility of reaching valuable destinations,” says Andrew Owen, director of the Observatory. “Job accessibility is an important consideration in the attractiveness and usefulness of a place or area.”

Travel times are calculated using a detailed road network and speed data that reflect typical conditions for an  8 a.m. Wednesday morning departure. Additionally, the accessibility results for 8 a.m. are compared with accessibility results for 4 a.m. to estimate the impact of road and highway congestion on job accessibility.

Map of U.S. showing reduced job accessibility due to congestion
Reduced job accessibility due to congestion

Rankings are determined by a weighted average of accessibility, with a higher weight given to closer, easier-to-access jobs. Jobs reachable within 10 minutes are weighted most heavily, and jobs are given decreasing weights as travel time increases up to 60 minutes.

Based on this measure, the research team calculated the 10 metropolitan areas with the greatest accessibility to jobs by auto (see sidebar).

A similar weighting approach was applied to calculate an average congestion impact for each metropolitan area. Based on this measure, the team calculated the 10 metropolitan areas where workers experience, on average, the greatest reduction in job access due to congestion (see sidebar).

Areas with the greatest loss in job accessibility due to congestion

  1. Los Angeles
  2. Boston
  3. Chicago
  4. New York
  5. Phoenix
  6. Houston
  7. Riverside
  8. Seattle
  9. Pittsburgh
  10. San Francisco

Metropolitan areas with the greatest job accessibility by auto

  1. New York
  2. Los Angeles
  3. Chicago
  4. Dallas
  5. San Jose
  6. San Francisco
  7. Washington, DC
  8. Houston
  9. Boston
  10. Philadelphia

“Rather than focusing on how congestion affects individual travelers, our approach quantifies the overall impact that congestion has on the potential for interaction within urban areas,” Owen explains.

“For example, the Minneapolis–St. Paul metro area ranked 12th in terms of job accessibility but 23rd in the reduction in job access due to congestion,” he says. “This suggests that job accessibility is influenced less by congestion here than in other cities.”

The report—Access Across America: Auto 2015—presents detailed accessibility and congestion impact values for each metropolitan area as well as block-level maps that illustrate the spatial patterns of accessibility within each area. It also includes a census tract-level map that shows accessibility patterns at a national scale.

The research was sponsored by the National Accessibility Evaluation Pooled-Fund Study, a multi-year effort led by the Minnesota Department of Transportation and supported by partners including the Federal Highway Administration and 10 state DOTs.


Related Links

Do People Use the Shortest Path? An Empirical Test of Wardrop’s First Principle

Recently published

Fig 5. The number of speed observations on each link during the entire study period.
Fig 5. The number of speed observations on each link during the entire study period.

Abstract

Most recent route choice models, following either the random utility maximization or rule-based paradigm, require explicit enumeration of feasible routes. The quality of model estimation and prediction is sensitive to the appropriateness of the consideration set. However, few empirical studies of revealed route characteristics have been reported in the literature. This study evaluates the widely applied shortest path assumption by evaluating routes followed by residents of the Minneapolis—St. Paul metropolitan area. Accurate Global Positioning System (GPS) and Geographic Information System (GIS) data were employed to reveal routes people used over an eight to thirteen week period. Most people did not choose the shortest path. Using three weeks of that data, we find that current route choice set generation algorithms do not reveal the majority of paths that individuals took. Findings from this study may guide future efforts in building better route choice models.

Accessibility, network structure, and consumers’ destination choice: a GIS analysis of GPS travel data

Working paper:

Walking areas around a trip destination
Walking areas around a trip destination
  • Huang, Arthur and Levinson, David (2011) Accessibility, network structure, and consumers’ destination choice: a GIS analysis of GPS travel data.

    Anecdotal and empirical evidence has shown that road networks, destination accessibility, and travelers’ choice of destination are closely related. Nevertheless, there have not been systematic investigations linking individuals’ travel behavior and retail clusters at the microscopic level. Based on GPS travel data in the Twin Cities, this paper analyzes the impacts of travelers’ interactions with road network structure and clustering of services at the destination on travelers’ destination choice. A multinomial logit model is adopted. The results reveal that higher accessibility and diversity of services in adjacent zones of a destination are associated with greater attractiveness of a destination. Further, the diversity and accessibility of establishments in an area are often highly correlated. In terms of network structure, a destination with a more circuitous or discontinuous route dampens its appeal. Answering where and why people choose to patronize certain places, our planning, our findings shed light on the design of road networks and clusters from a travel behavior perspective.

    (working paper)

Google LatLong: Arterial traffic available on Google Maps

Arterial traffic available on Google Maps for selected cities (including Minneapolis).
It seems they are doing it from Google Maps for Mobile, and getting automatic feedback of location from GPS-enabled online users (and thereby deriving speed). Clearly this is a good thing for traffic data nerds, and critical mass for arterial travel times is a good thing, even if Google winds up being the dominant provider.