Traffic Operations and Management

Emerging Technologies for Higher Fuel Economy Automobile Standards

Tim Lipman
2017

Transportation systems contribute significantly to air pollution and ∼15% globally and ∼25% in the United States to emissions climate-changing gases. In the United States, the Corporate Average Fuel Economy (CAFE) standards for motor vehicles were significantly raised in 2012 for the first time in almost three decades. The standards now call for an average across manufacturers of 54.5 miles per gallon (mpg) for new passenger cars by 2025, or 163 grams per mile (g/mi) of greenhouse gas (GHG) emissions, and of 47 mpg (196 g/mi) by 2021. The light truck standards, which include minivans and...

Driving California’s Transportation Emissions to Zero

Austin Brown
Daniel Sperling
Bernadette Austin
J. R. DeShazo
Lew Fulton
Tim Lipman
Colin Murphy
Jean Daniel
Gil Tal
Carolyn Abrams
Debapriya Chakraborty
Daniel Coffee
Sina Dabag
Adam Davis
Mark Delucchi
Kelly Fleming
Kate Forest
Juan Carlos Garcia Sanchez
Susan Handy
Michael Hyland
Alan Jenn
Seth Karten
Blake Lane
Michael Mackinnon
Elliot Martin
Marshall Miller
Monica Ramirez-Ibarra
Stephen Ritchie
Sara Schremmer
Joshua Segui
Susan Shaheen
Andre Tok
Aditya Voleti
Julie Witcover
Allison Yang
2021

The purpose of this report is to provide a research-driven analysis of options that can put California on a pathway to achieve carbon-neutral transportation by 2045. The report comprises thirteen sections. Section 1 provides an overview of the major components of transportation systems and how those components interact. Section 2 discusses the impacts the COVID-19 pandemic has had on transportation. Section 3 discusses California’s current transportation-policy landscape. These three sections were previously published as a synthesis report. Section 4 analyzes the different carbon scenarios...

Evaluation of Fuel Cell Auxiliary Power Units for Heavy-Duty Diesel Trucks

Christie-Joy Brodrick
Tim Lipman
Mohammad Farshchi
Nicholas P. Lutsey
Harry A. Dwyer
Daniel Sperling
William Gouse
Bruce Harris
Foy King
2002

A large number of heavy-duty trucks idle a significant amount. Heavy-duty line-haul truck engines idle about 20–40% of the time the engine is running, depending on season and operation. Drivers idle engines to power climate control devices (e.g., heaters and air conditioners) and sleeper compartment accessories (e.g., refrigerators, microwave ovens, and televisions) and to avoid start-up problems in cold weather. Idling increases air pollution and energy use, as well as wear and tear on engines. Efforts to reduce truck idling in the US have been sporadic, in part because it is widely...

Optimizing fermentation process miscanthus-to-ethanol biorefinery scale under uncertain conditions

Matthew Bomberg
Daniel L Sanchez
Tim Lipman
2014

Ethanol produced from cellulosic feedstocks has garnered significant interest for greenhouse gas abatement and energy security promotion. One outstanding question in the development of a mature cellulosic ethanol industry is the optimal scale of biorefining activities. This question is important for companies and entrepreneurs seeking to construct and operate cellulosic ethanol biorefineries as it determines the size of investment needed and the amount of feedstock for which they must contract. The question also has important implications for the nature and location of lifecycle...

Electric Vehicle Charge Management for Lowering Costs and Environmental Impact

Elpiniki Apostolaki-Iosifidou
Marco Pruckner
Soomin Woo
Tim Lipman
2020

As the number of electric vehicles is increasing, there is a pervasive call for research and new strategies in the field of vehicle grid integration. Using electric vehicle real-time data, drivers' spatial behavior and patterns can be derived for their morning and evening commute. These patterns combined with dynamic electricity costs, wholesale and retail, and variable greenhouse gas (GHG) emissions, lead to significant outcomes on savings and environmental impact. In this study, electric vehicle charging management is analyzed for the case of north California, using real world data. The...

Position and Speed Estimation Using Deep Learning-Based KKL Observer in Mixed Autonomy Traffic Systems

Marani, Yasmine
Fu, Zhe
N'doye, Ibrahima
Feron, Eric
Laleg-Kirati, Taous-Meriem
Alexandre Bayen
2025

This paper proposes a deep learning-based Kazantzis–Kravaris–Luenberger (KKL) observer design to estimate position and speed in mixed-autonomy traffic environments. The approach relies on position measurements of vehicles surrounding the autonomous vehicle (AV), obtained through remote sensing, resulting in a subsequent time delay due to communication latency. The proposed deep learning KKL observer is designed to compensate for this delay and to ensure global asymptotic convergence of the estimation of position and speed by using a chain of sub-observers. We employ an unsupervised...

Traffic Delay at Unsignalized Intersections: Clarification of Some Issues

Carlos Daganzo
1977

Investigations in this area have been directed at finding the delay to a motorist who arrives at an intersection and wishes to cross a high-priority traffic stream. In this paper two conceptual errors that have appeared in some past publications are identified and corrected.

The Uniqueness of a Time-Dependent Equilibrium Distribution of Arrivals at a Single Bottleneck

Carlos Daganzo
1985

Motorists going through a bottleneck during the morning rush hour have to time their departure times to ensure they arrive to work at a reasonable time. Traffic and congestion levels at the bottleneck depend on the motorists' work schedule and the disutility of unpunctuality. This paper shows that, under certain conditions, there is only one equilibrium order of arrivals; an order under which motorists do not have an incentive to jockey for position in the queue.

Modeling Distribution Problems with Time Windows. Part II: Two Customer Types

Carlos Daganzo
1987

This paper extends the results of a previous study concerning distribution with time windows. It is recognized that customers who do not need to be allocated to a time window should receive different service than the rest. Three strategies were studied to accomplish that: stratified service, discriminating service, and staggered and discriminating service. Of these, the last strategy yields the lowest local distribution distance per customer, a distance which can be less than half that for the strategy explained in the previous paper (joint service). Stratified service, however, can yield...

Modeling Distribution Problems with Time Windows: Part I

Carlos Daganzo
1987

This paper shows how distribution problems with delivery time constraints can be modeled approximately with just a few variables. Its objective is neither to develop a scheduling algorithm nor an exact predictive method; rather, it is to illustrate some trade-offs and principles that can be used for planning and algorithm development. A workday is divided into time periods. Time windows are modeled by specifying the period in which a vehicle should visit each customer. (The companion paper explores scenarios where many customers do not specify a time window, and thus, it is advantageous...