HPC-enabled computation of demand models at scale

Technical Report · Wed May 06 04:00:00 EDT 2020

DOI:https://doi.org/10.2172/1617377· OSTI ID:1617377

Nugent, Peter ^[1]

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1. Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)

The purpose of this project is to examine the energy impact of urban-scale traffic for the Los Angeles Basin by developing and implementing a scalable traffic assignment model. An energy optimization function will be posed and when integrated into the optimization code for travel assignment it can be mathematically proven to converge. The energy optimization function can then be compared to the typical travel time optimization that is traditionally used in traffic assignment models. The analysis will begin with static traffic assignment models with the routing for all origin and destinations computed in parallel on high performance computing facilities. Convergence of the numerical methods rely on the solution of convex programs (or extensions of these). This step will mostly consist of demonstrating the ability to parallelize the Frank Wolfe algorithm on various platforms.

• Research Organization: Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States); Univ. of California, Berkeley, CA (United States)
• Sponsoring Organization: USDOE Office of Science (SC), Advanced Scientific Computing Research (ASCR) (SC-21). Scientific Discovery through Advanced Computing (SciDAC)
• DOE Contract Number: AC02-05CH11231
• OSTI ID: 1617377
• Report Number(s): LBNL--2001315; LBNL-CRADA--AWD00003092
• Country of Publication: United States
• Language: English

Related Subjects

29 ENERGY PLANNING, POLICY, AND ECONOMY
97 MATHEMATICS AND COMPUTING