ITS Berkeley

(U)NFV: Supervised and Unsupervised Neural Finite Volume Methods for Solving Hyperbolic PDEs

Lichtle, Nathan
Canesse, Alexi
Fu, Zhe
Matin, Hossein Nick Zinat
Monache, Maria Laura Delle
Bayen, Alexandre M.
2025

We introduce (U)NFV, a modular neural network architecture that generalizes classical finite volume (FV) methods for solving hyperbolic conservation laws. Hyperbolic partial differential equations (PDEs) are challenging to solve, particularly conservation laws whose physically relevant solutions contain shocks and discontinuities. FV methods are widely used for their mathematical properties: convergence to entropy solutions, flow conservation, or total variation diminishing, but often lack accuracy and flexibility in complex settings. Neural Finite Volume addresses these limitations by...

Enabling Analysis and Visualization of Transportation Big Data

Rees, Stephen
Sprinkle, Jonathan
Wang, Xia
Bunting, Matthew
Work, Daniel B.
Lee, Jonathan W.
Monache, Maria Laura Delle
Bayen, Alexandre M.
Piccoli, Benedetto
2025

Transportation studies generate massive amounts of data that are difficult to store, process, query and visualize quickly and easily. Overcoming these challenges are an essential aspect of making the collected data useful to both the original study and other research that could build on the results. We explore the impact of database implementation, specifically IoTDB, on these aspects of data management with respect to transportation on existing datasets.

Human-In-The-Loop Classification of Adaptive Cruise Control at a Freeway Scale

Wang, Xia
Nice, Matthew
Bunting, Matt
Wu, Fangyu
Monache, Maria Laura Delle
Lee, Jonathan W.
Piccoli, Benedetto
Seibold, Benjamin
Bayen, Alexandre M.
Work, Daniel B.
Sprinkle, Jonathan
2025

The goal of this paper is to estimate whether a human or Adaptive Cruise Control (ACC) is managing a vehicle's speed control, based on observations by external sensors. The driving characteristics of individual vehicles---whether human-driven or ACC-controlled---play a crucial role in shaping overall traffic flow. To enable advanced traffic control strategies tailored to specific vehicle behaviors, this paper introduces a time-series deep learning classifier that leverages multiple models, including One-Dimensional Convolutional Neural Networks (1D-CNN), Recurrent Neural Networks (RNN),...

Decentralized Vehicle Coordination: The Berkeley DeepDrive Drone Dataset and Consensus-Based Models

Wu, Fangyu
Wang, Dequan
Hwang, Minjune
Hao, Chenhui
Lu, Jiawei
Zhang, Jiamu
Chou, Christopher
Darrell, Trevor
Bayen, Alexandre
2025

A significant portion of roads, particularly in densely populated developing countries, lacks explicitly defined right-of-way rules. These understructured roads pose substantial challenges for autonomous vehicle motion planning, where efficient and safe navigation relies on understanding decentralized human coordination for collision avoidance. This coordination, often termed “social driving etiquette,” remains underexplored due to limited open-source empirical data and suitable modeling frameworks. In this paper, we present a novel dataset and modeling framework designed to study motion...

Individual and City-level Variations in Heat-related Road Traffic Deaths in Latin America

Hsu, Cheng-Kai
Quistberg, D. Alex
Sanchez, Brisa N.
Kephart, Josiah L.
Bilal, Usama
Gouveia, Nelson
Ferrer, Carolina Pérez
Caiaffa, Waleska T.
de Lima Friche, Amélia Augusta
Yannone, Ignacio
Rodríguez, Daniel A.
2025

Latin America experiences both high road traffic mortality and extreme heat, which have been shown elsewhere to be interrelated. However, few studies have examined this association in Latin America—one of the world’s most urbanized, fastest-motorizing regions, with a high share of vulnerable road users—and even fewer have analyzed multiple cities across diverse climates and urban settings. Leveraging ambient temperature and road traffic mortality data (2000–2019) from 272 cities in six Latin American countries, we conducted a time-stratified case-crossover study. On the basis of over 1.9...

Built and Social Environment Characteristics Associated with Motorcyclist Mortality in Latin American Cities from the SALURBAL Study

Yannone, Ignacio Javier
Alazraqui, Marcio
Rodriguez Hernandez, Jordan L.
Sarmiento Dueñas, Olga Lucia
Rodríguez, Daniel A.
Ferrer, Carolina Pérez
Guzman, Luis A.
Perner, Mónica Serena
Trotta, Andres
Roux, Ana V. Diez
Quistberg, D Alex
2025

Motorcyclists are the fastest growing road user group in Latin America, and account for 25% of all road traffic collision deaths. This study examines the relationship between motorcyclist mortality and the built and social urban environment in Latin American cities.

Linear and Nonlinear Analysis of Wavy-Surface-Induced Laminar Separation Bubbles

Moniripiri, Mohammad
Rodriguez, Daniel
Hanifi, Ardeshir
2025

Linear global stability analysis is performed on a laminar separation bubble formed dueto surface waviness. The eigenspectrum shows a globally unstable mode, responsiblefor the three-dimensionalisation of the bubble, and a family of low-frequency globallystable modes. An adjoint sensitivity analysis shows high sensitivity of the stable modesupstream of the bubble’s reattachment point. Direct numerical simulation (DNS)alongside with a linear impulse response analysis are performed. DNS shows that, whentransition occurs due to self-excited mechanisms, low-frequency upstream propagatingwaves...

Rail Transit Ridership Changes in COVID-19: Lessons for Station Area Planning in California

Li, Meiqing
Rodríguez, Daniel A.
Pike, Susie
McNally, Michael
2025

Emerging evidence suggests that the recovery of transit ridership post-COVID has been uneven, especially for rail transit. This study aims to understand the station area land use, built form, and transit network characteristics that explain station-level changes in transit ridership pre- and post-COVID, and explores the degree to which those changes are rail transit-specific or the result of overall changes in visits to station areas. Specifically, we examine ridership changes between 2019 and 2021 for 242 rail stations belonging to the Bay Area Rapid Transit (BART), San Diego Metropolitan...

Plane-marching PSE Wavepacket Models for Perfectly-expanded Twin Jets

Padilla-Montero, Ivan
Rodriguez, Daniel
Jaunet, Vincent
Jordan, Peter
2025

The importance of wavepackets in the generation of mixing noise in twin jets is expected by extrapolation of the insights previously obtained from the study of single isolated jets. This work presents wavepacket models for supersonic round twin jets operating at perfectly-expanded conditions, computed via plane-marching parabolized stability equations based on mean flows obtained from the compressible RANS equations. High-speed schlieren visualizations and non-time-resolved PIV measurements are performed to obtain experimental datasets for validating the modelling strategy. The RANS...

Future Temperature-related Mortality in Latin American Cities under Climate Change and Population Scenarios

Bakhtsiyarava, Maryia
Kephart, Josiah L.
Sanchez, Brisa N.
Ramarao, M. V. S.
Arunachalam, Saravanan
Gouveia, Nelson
Dronova, Iryna
Schinasi, Leah H.
Bilal, Usama
Caiaffa, Waleska T.
Jaffe, Andrea
Diez Roux, Ana V.
Rodríguez, Daniel A.
2025

Background In Latin America, climate change, urbanization, and an aging population are intensifying health risks from extreme temperatures. To accurately assess future temperature-related mortality impacts, evidence that integrates key demographic factors—such as the dynamics of population age composition, mortality rates, and population size—is essential. Methods We projected the impact of nonoptimal temperatures on all-age and age-specific mortality during 2045–2054 for 326 cities in Latin America. Our analysis combined city-level daily mortality counts, gridded temperature data,...