Emission reduction potential of freeway stop-and-go wave smoothing
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arXiv
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| Autores principales: | , , , , , , |
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| Formato: | Preprint |
| Publicado: |
2026
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| _version_ | 1866911535872344064 |
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| author | Ji, Junyi Gloudemans, Derek Zachár, Gergely Barbour, William Sprinkle, Jonathan Piccoli, Benedetto Work, Daniel B. |
| author_facet | Ji, Junyi Gloudemans, Derek Zachár, Gergely Barbour, William Sprinkle, Jonathan Piccoli, Benedetto Work, Daniel B. |
| contents | Real-world potential of stop-and-go wave smoothing at scale remains largely unquantified. Smoothing freeway traffic waves requires creating a gap so the wave can dissipate, but the gap suggested is often too large and impractical. We propose a counterfactual wave smoothing benchmark that reconstructs a smooth and feasible trajectory from each empirical trajectory by solving a quadratic program with fixed boundary conditions and a maximum allowable gap constraint. We estimate the emission reduction potential from trajectories using the MOVES model. Applying the framework to nine weeks of weekday peak traffic data, featuring rich day-to-day stop-and-go wave dynamics, from the I-24 MOTION testbed, we find meaningful reduction potential under a 0.1-mile maximum gap: average CO2 reductions of 7.92% to 12.04% across lanes, with concurrent reductions of 14.30% to 28.91% CO, 23.15% to 29.42% HC, and 24.37% to 30.98% NOx. Our analysis also quantifies the trade-off between maximum allowable gap opening and emissions benefits. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2603_21476 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Emission reduction potential of freeway stop-and-go wave smoothing Ji, Junyi Gloudemans, Derek Zachár, Gergely Barbour, William Sprinkle, Jonathan Piccoli, Benedetto Work, Daniel B. Systems and Control Real-world potential of stop-and-go wave smoothing at scale remains largely unquantified. Smoothing freeway traffic waves requires creating a gap so the wave can dissipate, but the gap suggested is often too large and impractical. We propose a counterfactual wave smoothing benchmark that reconstructs a smooth and feasible trajectory from each empirical trajectory by solving a quadratic program with fixed boundary conditions and a maximum allowable gap constraint. We estimate the emission reduction potential from trajectories using the MOVES model. Applying the framework to nine weeks of weekday peak traffic data, featuring rich day-to-day stop-and-go wave dynamics, from the I-24 MOTION testbed, we find meaningful reduction potential under a 0.1-mile maximum gap: average CO2 reductions of 7.92% to 12.04% across lanes, with concurrent reductions of 14.30% to 28.91% CO, 23.15% to 29.42% HC, and 24.37% to 30.98% NOx. Our analysis also quantifies the trade-off between maximum allowable gap opening and emissions benefits. |
| title | Emission reduction potential of freeway stop-and-go wave smoothing |
| topic | Systems and Control |
| url | https://arxiv.org/abs/2603.21476 |