Analyzing intra-metropolitan variation in highway traffic performance in Los Angeles using archived real-time data

ABSTRACT

We conduct a case study of highway system performance in Los Angeles County. We use the Los Angeles Archived Data Management System, a comprehensive archive of regional real-time multi-modal transportation system data, to analyze effects of systematic, functional, random, and land use factors on performance variation over different time periods of the day. To understand functional class effects, we use cluster analysis on geometric and demand parameters to identify functionally similar groups of highway segments. We compare performance between groups and across segments within groups. We perform regression analysis to test the influence of various factors on performance. We find that after controlling for time of day, accidents, and adjacent population density, group or peer effects have significant influence. This suggests that peer group level, as opposed to regional, performance measurement and monitoring is useful. Our research has significant implications for transportation system monitoring and planning.

KEYWORDS:

• Highway system performance
• traffic congestion
• travel time reliability
• transportation planning
• case study

Acknowledgements

The authors would like to thank the ADMS project team members at the METRANS Transportation Center and the Integrated Media Systems Center, University of Southern California. The ADMS, the principal data source for this study, is supported by the Los Angeles County Metropolitan Transportation Authority. Feedback received on earlier versions of the manuscript at the 56th Annual Conference of the Association of Collegiate Schools of Planning, Portland, and at the 57th Annual Meeting of the Western Regional Science Association, Pasadena, California have helped improve the paper. The authors are responsible for all errors and omissions.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Notes

1 For examples of performance reporting, see Southern California Association of Governments 2007; the annual TTI Urban Mobility Scorecard, or the annual National Transportation Statistics (see National Transportation Statistics 2019).

2 The Urban Mobility Scorecard ended in 2015; INRIX now produces the Global Traffic Scorecard, which uses different metrics and is not comparable to the earlier Scorecards.

3 https://www.fhwa.dot.gov/policyinformation/hpms/shapefiles.cfm (accessed September 17, 2020).

4 https://gisdata-caltrans.opendata.arcgis.com/ (September 17, 2020).

5 We tested the effect of adjacent employment density in addition to population density. The two variables are correlated, and population effects are more consistent. We therefore chose to use population density.

Additional information

Funding

The project was funded by the U.S. Department of Transportation, and the Los Angeles County Metropolitan Transportation Authority. [grant number DTRT13-G-UTC57].