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1. Cluster analysis of day-to-day traffic data in networks

   https://doi.org/10.1016/j.trc.2022.103882  

   Zhang, Pengji; Ma, Wei; Qian, Sean (November 2022, Transportation Research Part C: Emerging Technologies)
2. Contextual Bayesian optimization of congestion pricing with day-to-day dynamics

   https://doi.org/10.1016/j.tra.2023.103927  

   Liu, Renming; Jiang, Yu; Seshadri, Ravi; Ben-Akiva, Moshe; Azevedo, Carlos Lima (January 2024, Transportation Research Part A: Policy and Practice)
3. Day-To-Day User Adaptation to a Robotic Ankle-Foot Prosthesis

   https://doi.org/10.1109/ICORR66766.2025.11063200  

   Miri, Sina; Jacobson, Michael; Major, Matthew J; Kim, Myunghee (May 2025, IEEE)
4. Multi-instrumental analysis of the day-to-day variability of equatorial plasma bubbles

   https://doi.org/10.3389/fspas.2023.1167245  

   Aa, Ercha; Zhang, Shun-Rong; Coster, Anthea J.; Erickson, Philip J.; Rideout, William (March 2023, Frontiers in Astronomy and Space Sciences)

   This paper presents a multi-instrument observational analysis of the equatorial plasma bubbles (EPBs) variation over the American sector during a geomagnetically quiet time period of 07–10 December 2019. The day-to-day variability of EPBs and their underlying drivers are investigated through coordinately utilizing the Global-scale Observations of Limb and Disk (GOLD) ultraviolet images, the Ionospheric Connection Explorer (ICON) in-situ and remote sensing data, the global navigation satellite system (GNSS) total electron content (TEC) observations, as well as ionosonde measurements. The main results are as follows: 1) The postsunset EPBs’ intensity exhibited a large day-to-day variation in the same UT intervals, which was fairly noticeable in the evening of December 07, yet considerably suppressed on December 08 and 09, and then dramatically revived and enhanced on December 10. 2) The postsunset linear Rayleigh-Taylor instability growth rate exhibited a different variation pattern. It had a relatively modest peak value on December 07 and 08, yet a larger peak value on December 09 and 10. There was a 2-h time lag of the growth rate peak time in the evening of December 09 from other nights. This analysis did not show an exact one-to-one relationship between the peak growth rate and the observed EPBs intensity. 3) The EPBs’ day-to-day variation has a better agreement with that of traveling ionospheric disturbances and atmospheric gravity waves signatures, which exhibited relatively strong wavelike perturbations preceding/accompanying the observed EPBs on December 07 and 10 yet relatively weak fluctuations on December 08 and 09. These coordinate observations indicate that the initial wavelike seeding perturbations associated with AGWs, together with the catalyzing factor of the instability growth rate, collectively played important roles to modulate the day-to-day variation of EPBs. A strong seeding perturbation could effectively compensate for a moderate strength of Rayleigh-Taylor instability growth rate and therefore their combined effect could facilitate EPB development. Lacking proper seeding perturbations would make it a more inefficient process for the development of EPBs, especially with a delayed peak value of Rayleigh-Taylor instability growth rate. 

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5. A Day-to-Day Dynamical Approach to the Most Likely User Equilibrium Problem

   https://doi.org/10.1287/trsc.2024.0525  

   Li, Jiayang; Wang, Qianni; Feng, Liyang; Xie, Jun; Nie, Yu Marco (July 2024, Transportation Science)

   The lack of a unique user equilibrium (UE) route flow in traffic assignment has posed a significant challenge to many transportation applications. The maximum-entropy principle, which advocates for the consistent selection of the most likely solution, is often used to address the challenge. Built on a recently proposed day-to-day discrete-time dynamical model called cumulative logit (CumLog), this study provides a new behavioral underpinning for the maximum-entropy user equilibrium (MEUE) route flow. It has been proven that CumLog can reach a UE state without presuming that travelers are perfectly rational. Here, we further establish that CumLog always converges to the MEUE route flow if (i) travelers have no prior information about routes and thus, are forced to give all routes an equal initial choice probability or if (ii) all travelers gather information from the same source such that the general proportionality condition is satisfied. Thus, CumLog may be used as a practical solution algorithm for the MEUE problem. To put this idea into practice, we propose to eliminate the route enumeration requirement of the original CumLog model through an iterative route discovery scheme. We also examine the discrete-time versions of four popular continuous-time dynamical models and compare them with CumLog. The analysis shows that the replicator dynamic is the only one that has the potential to reach the MEUE solution with some regularity. The analytical results are confirmed through numerical experiments. History: This paper has been accepted for the Transportation Science Special Issue on ISTTT25 Conference. Funding: This research was funded by the United States National Science Foundation’s Division of Civil, Mechanical and Manufacturing Innovation [Grant 2225087]. The work of J. Xie was funded by the National Natural Science Foundation of China [Grant 72371205]. Supplemental Material: The online appendix is available at https://doi.org/10.1287/trsc.2024.0525 . 

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