01657467

Component

The rapid urbanization and increasing traffic have serious social, economic, and environmental impact on metropolitan areas worldwide. It is of a great importance to understand the complex interplay of road networks and traffic conditions. The authors propose a novel framework to estimate traffic conditions at the metropolitan scale using GPS traces. Their approach begins with an initial estimation of network travel times by solving a convex optimization program based on traffic flow theory. Then, they iteratively refine the estimated network travel times and vehicle traversed paths. Last, the authors perform a bilevel optimization process to estimate traffic conditions on road segments that are not covered by GPS data. The evaluation and comparison of the authors' approach over two state-of-the-art methods show up to 96.57% relative improvements. The authors have further conducted field tests by coupling road networks of San Francisco and Beijing with real-world GIS data, which involve 128,701 nodes, 148,899 road segments, and over 26 million GPS traces.

This paper was sponsored by TRB committee AHB45 Standing Committee on Traffic Flow Theory and Characteristics.

18-00974

English

6p

2018

Transportation Research Board 97th Annual Meeting

Digital/other

Figures; References; Tables

Field tests; Global Positioning System; Metropolitan areas; Networks; Optimization; Traffic characteristics; Traffic data; Traffic estimation; Traffic flow theory; Urban travel

Beijing (China); San Francisco (California)

Data and Information Technology; Highways; Operations and Traffic Management; Planning and Forecasting

Transportation Research Board Annual Meeting 2018 Paper #18-00974

TRIS, TRB, ATRI

Jan 8 2018 10:14AM