A land-use clustering approach to capturing the level-of-service of large urban corridors
A case study in downtown Los Angeles
Bibliographic Data
| ID | 21247435 |
|---|---|
| Authors | Junseo Bae (0000-0002-4311-5233, University of the West of Scotland, corresponding author), Kunhee Choi (0000-0002-0184-2977, Texas A&M University) |
| Year | 2021 |
| Volume | 48 |
| Issue | 7 |
| Pages | 2093-2109 |
| Publication date | 2021-09-01 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Environment and Planning B Urban Analytics and City Science (JOURNAL) |
| Journal identifiers | ISSN: 2399-8083 • E-ISSN: 2399-8091 |
| Publisher | SAGE Publications (PUBLISHER • US) |
| DOI | 10.1177/2399808320954209 |
| OpenAlex | W3083324953 |
| Language | EN |
| Citations received | 1 |
| References cited | 35 |
Level-of-service has been widely used to measure the operational efficiency of existing highway systems categorically, based on certain ranges of traffic speeds. However, this existing method is generic for investigating urban traffic characteristics. Hence, there is a crucial knowledge gap in capturing the unique traffic speed conditions during a certain temporal duration, in a common spatial area that includes different land use clusters. This study fills this gap by modeling the link between traffic speeds and land use clusters during certain time periods, along with the given level-of-service criteria. As a case study, this study adopted the central business district in Los Angeles in the United States. A total of 1780 traffic sensor speed data on Interstate 10 East adjacent to the central business district of Los Angeles was collected and clustered by the land use designated by the zoning regulations of the city of Los Angeles. The proposed traffic time–speed curve model that integrates different land uses in a large urban core was then developed and validated statistically, using historical real-world traffic data. Finally, an illustrative example was presented to demonstrate how the proposed model can be implemented to measure critical time periods and corresponding speeds per land-use cluster, responding to the designated level-of-service criteria. This study focused on making recommendations for government transportation agencies to employ an appropriate method that can estimate critical time periods affecting the existing operational status of a highway segment in different land-use clusters within a common spatial area, while promoting an effective application of a set of traffic sensor speed data
Business · Civil engineering · Cluster analysis · Data mining · Downtown · Geography · Land use · Level of service · Transport engineering · Zoning · Computer Science · Engineering · Traffic and Road Safety · Traffic Prediction and Management Techniques · Transportation Planning and Optimization
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| Unique citing works | 1 |
|---|---|
| Citations per year | 0,2 |
| Citation span | 2021 - 2021 (1) |
| Citation velocity | historical |
| Highly cited | No |
| Citation types | Neutral: 1 |