Budget-Constrained Rail Electrification Modeling Using Symmetric Traffic Assignment: A North American Case Study

Patil, Priyadarshan N.; Walthall, Rydell; Boyles, Stephen D.

doi:10.1061/(asce)is.1943-555x.0000682

Cited by 3 publications

(2 citation statements)

References 26 publications

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“…This is particularly important for applications where TAP is solved multiple times as a sub-problem. Some applications include network design problems (Yang 1997;Patil, Walthall, and Boyles 2022;Gokalp, Patil, and Boyles 2021), sensitivity analysis (Boyles 2012), trip table estimation (Yang 1995;Lundgren and Peterson 2008), network pricing (Yang and Lam 1996), and other bilevel optimization problems (Yin 2000;Astroza et al 2017;Pandey and Patil 2022;Boyles et al 2018). Patil, Ross, and Boyles (2021) provide additional background on convergence analysis for TAP.…”

Section: Convergence Experimentsmentioning

confidence: 99%

A fresh look at symmetric traffic assignment and algorithm convergence

Patil¹

2023

Preprint

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Extensions of the static traffic assignment problem with link interactions were studied extensively in the past. Much of the network modeling community has since shifted to dynamic traffic assignment incorporating these interactions. We believe there are several reasons to re-examine static assignment with link interactions. First, if link interactions can be captured in a symmetric, monotone manner, equilibrium always exists and is unique, and provably-correct algorithms exist. We show that several of the most efficient algorithms for the separable traffic assignment problem can be readily applied with symmetric interactions. We discuss how the (asymmetric) Daganzo merge model can be approximated by symmetric linear cost functions. Second, we present computational evidence suggesting that convergence to equilibrium is faster when symmetric, monotone link interactions are present. This is true even when interactions are asymmetric, despite the lack of a provable convergence result. Lastly, we present convergence behavior analysis for commonly used network and link metrics. For these reasons, we think static assignment with link interactions deserves additional attention in research and practice.

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Section: Convergence Experimentsmentioning

confidence: 99%

A fresh look at symmetric traffic assignment and algorithm convergence

Patil¹

2023

Preprint

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“…Early approaches to conducting freight rail decarbonization analyses date back to the 1970s with Schwarm ( 26 ) and Ditmeyer et al ( 27 ) who analyzed the viability of track electrification, albeit from a primarily economic perspective, excluding environmental impact analyses. More recently, track electrification for the US freight rail network is considered as a budget-constrained network deployment problem with a built-in dynamic traffic assignment module to model the effects of track electrification on network congestion when the overall objective is to reduce rail emissions ( 28 ).…”

Section: Literature Reviewmentioning

confidence: 99%

Evaluation of Rail Decarbonization Alternatives: Framework and Application

Hernandez

Siddique

et al. 2023

Transportation Research Record: Journal of the Transportation R

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The Northwestern University Freight Rail Infrastructure & Energy Network Decarbonization (NUFRIEND) framework is a comprehensive industry-oriented tool for simulating the deployment of new energy technologies including biofuels, e-fuels, battery-electric, and hydrogen locomotives. By classifying fuel types into two categories based on deployment requirements, the associated optimal charging/fueling facility location and sizing problem are solved with a five-step framework. Life-cycle analysis (LCA) and techno-economic analysis (TEA) are used to estimate carbon reduction, capital investments, cost of carbon reduction, and operational impacts, enabling sensitivity analysis with operational and technological parameters. The framework is illustrated on lower-carbon drop-in fuels as well as battery-electric technology deployments for the US Eastern and Western Class I railroad networks. Drop-in fuel deployments are modeled as admixtures with diesel in existing locomotives, while battery-electric deployments are shown for varying technology penetration levels and locomotive ranges. When mixed in a 50% ratio with diesel, results show biodiesel’s capacity to reduce emissions at 36% with a cost of $ 0.13 per kilogram of CO2 reduced, while e-fuels offer a potential reduction of 50% of emissions at a cost of $ 0.22 per kilogram of CO2 reduced. Battery-electric results for 50% deployment over all ton-miles highlight the value of future innovations in battery energy densities as scenarios assuming 800-mi range locomotives show an estimated emissions reduction of 46% with a cost of $ 0.06 per kilogram of CO2 reduced, compared with 16% emissions reduction at a cost of $ 0.11 per kilogram of CO2 reduced for 400-mi range locomotives. The NUFRIEND framework provides a systematic method for comparing different alternative energy technologies and identifying potential challenges and benefits in their future deployments.

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