# Traffic Simulations: Multi-City Calibration of Metropolitan Highway Networks

arXiv: https://arxiv.org/abs/2501.04783 · HTML: https://mlsanity.com/paper/2501.04783/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 8 Jan 2025.

## Built on by (most cited first, 1 of 1)

- [Scaling Federated Linear Contextual Bandits via Sketching](https://mlsanity.com/paper/2605.00500/) (2026)

## Abstract (arXiv)

This paper proposes an approach to perform travel demand calibration for high-resolution stochastic traffic simulators. It employs abundant travel times at the path-level, departing from the standard practice of resorting to scarce segment-level sensor counts. The proposed approach is shown to tackle high-dimensional instances in a sample-efficient way. For the first time, case studies on 6 metropolitan highway networks are carried out, considering a total of 54 calibration scenarios. This is the first work to show the ability of a calibration algorithm to systematically scale across networks. Compared to the state-of-the-art simultaneous perturbation stochastic approximation (SPSA) algorithm, the proposed approach enhances fit to field data by an average 43.5% with a maximum improvement of 80.0%, and does so within fewer simulation calls.