Intelligent Transportation Systems

Public Health Sector Influence in Transportation Decision-Making: The Case of Health Impact Assessment

Carolyn McAndrews
Elizabeth Deakin
2020

Health impact assessment (HIA) is a method of analyzing and communicating the potential health-related outcomes of policies and projects in a variety of fields, including transportation. The transportation policy process already has formal routines to incorporate information about air quality, noise, safety, and other health issues. However, the HIA method could broaden the set of issues under consideration (e.g., physical activity), the types of decisions assessed, and the actors involved. In theory, HIA seeks to influence transportation decisions and serve as a platform for public...

Intelligent Transport Systems

Elizabeth Deakin
Karen Trapenberg Frick
Alexander Skabardonis
2004

If you've seen an electronic massage sign along the highway that tells you how long it will take to get downtown or to the airport, or paid your toll or your parking fees with an electronic tag, or ridden a bus that triggered the traffic lights to turn green as it approached them, then you have experienced some of the benefits of Intelligent Transportation Systems (ITS)—an umbrella term for a variety of new technologies and operations methods for highways and transit. Other on-the-ground ITS applications are less visible to the average traveler, but every bit as useful: they help traffic...

Risk Assessment and Risk Management for Transportation Research

Elizabeth Deakin
Karen Trapenberg Frick
Kathleen Phu
2014

This paper sets forth a preliminary methodology to assess and manage risk for transportation research. The California Dept. of Transportation (Caltrans) funds numerous transportation research projects that range from studies that aim to improve the understanding of travel behavior to field operations tests and deployment studies for new technologies. The risk assessment methodology is designed to help 1) identify needs for transportation research, 2) identify likely audiences for the anticipated research products, as well as potential applications; 3) identify potential barriers that could...

Vehicle Technologies for Achieving Near and Longer Term Fuel Economy and Climate Goals

Tim Lipman
2020
Motor vehicles are a key element of transport systems worldwide, providing vitally important access to goods and services. However, motor vehicles powered by internal combustion engines directly emit harmful pollutants and climate-changing gases. New fuels and new automotive technologies offer the potential to simultaneously make motor vehicles much cleaner and more efficient by reducing tailpipe emissions and allowing the focus to be on the “upstream” emissions from fuels production. This can be accomplished through an increasing array of hybrid electric and pure electric...

Analysis of The Combined Vehicle-and Post‐Vehicle-Use Value of Lithium‐Ion Plug-In-Vehicle Propulsion Batteries

Brett Williams
Tim Lipman
2011

Advances in electric-drive technology, including lithium-ion batteries, as well as the development of strong policy drivers such as California’s Global Warming Solutions Act, now contribute to a more promising market environment for the widespread introduction of plug-in vehicles in California. Nevertheless, battery costs remain high and uncertain, presenting significant hurdles to commercialization. This report builds upon previous research (CEC-500-2009-091) investigating the potential reduction in plug-in-hybrid battery lease payments that incorporation of value from postvehicle...

The CO2 Abatement Potential of California's Mid-Sized Commericial Buildings

Michael Stadler
Chris Marnay
Gonçalo Cardoso
Tim Lipman
Olivier Mégel
Srirupa Ganguly
Afzal Siddiqui
Judy Lai
2009

The Ernest Orlando Lawrence Berkeley National Laboratory (LBNL) is working with the California Energy Commission (CEC) to determine the potential role of commercial sector distributed generation (DG) with combined heat and power (CHP) capability deployment in greenhouse gas emissions (GHG) reductions. CHP applications at large industrial sites are well known, and a large share of their potential has already been harvested. In contrast, relatively little attention has been paid to the potential of medium-sized commercial buildings, i.e. ones with peak electric loads ranging from 100 kW to 5...

SMART Mobility. Advanced Fueling Infrastructure Capstone Report

John Smart
Zicheng Bi
Alicia Birky
Brennan Borlaug
Erin Burrell
Eleftheria Koutou
Dong-Yeon Lee
Tim Lipman
Andrew Meintz
Eric Miller
Ahmed Mohamed
Matthew Moniot
Amy Moore
Yutaka Motoaki
Zachary Needell
Omer Onar
Clement Rames
Nicholas Reincke
Mohammad Roni
Shawn Salisbury
Colin Sheppard
Danho Ange Lionel Toba
Victor Walker
Dustin Weigl
Eric Wood
Fei Xie
Yonggen Yi
Teng Zeng
Hongcai Zhang
Yan Zhou
Zhi Zhou
2020

The U.S. Department of Energy’s Systems and Modeling for Accelerated Research in Transportation (SMART) Mobility Consortium is a multiyear, multi-laboratory collaborative, managed by the Energy Efficient Mobility Systems Program of the Office of Energy Efficiency and Renewable Energy, Vehicle Technologies Office, dedicated to further understanding the energy implications and opportunities of advanced mobility technologies and services. The first three-year research phase of SMART Mobility occurred from 2017 through 2019 and included five research pillars: Connected and Automated Vehicles,...

Reducing Greenhouse Emissions and Fuel Consumption: Sustainable Approaches for Surface Transportation

Susan Shaheen
Tim Lipman
2007

Climate change is rapidly becoming known as a tangible issue that must be addressed to avoid major environmental consequences in the future. Recent change in public opinion has been caused by the physical signs of climate change–melting glaciers, rising sea levels, more severe storm and drought events, and hotter average global temperatures annually. Transportation is a major contributor of carbon dioxide (CO2) and other greenhouse gas emissions from human activity, accounting for approximately 14 percent of total anthropogenic emissions globally and about 27 percent in the U.S....

DeepTimeGeo: Trajectory Reconstruction From Sparse Data With Transformer

Cao, Shangqing
Wu, Jiaman
Kasliwal, Aparimit
Chen, Baoqi
Perona, Giuseppe
Marta Gonzalez
2026

The completion of sparse Location-Based Service (LBS) data for modeling urban-scale origin-destination (OD) flow is of great importance to transportation planning applications. Sparse trajectories lack realistic human mobility patterns. Only with completed trajectories one can derive urban-scale OD flow that resembles complete travel diaries as those gathered by surveys or actively collecting phone applications. We present DeepTimeGeo (DTG), a transformer encoder-only model that reconstructs complete trajectories from sparse LBS inputs. We adopt a rank-based representation of locations to...

Learning to Recommend in Unknown Games

Alanqary, Arwa
Baba, Zakaria
Wu, Manxi
Alexandre Bayen
2026

We study preference learning through recommendations in multi-agent game settings, where a moderator repeatedly interacts with agents whose utility functions are unknown. In each round, the moderator issues action recommendations and observes whether agents follow or deviate from them. We consider two canonical behavioral feedback models-best response and quantal response-and study how the information revealed by each model affects the learnability of agents' utilities. We show that under quantal-response feedback the game is learnable, up to a positive affine equivalence class, with...