published journal article
working paper
This paper provides the data collection and research results for the Seamless Travel project. The Seamless Travel Project is a research project funded by Caltrans and managed by the University of California Traffic Safety Center, with David Ragland, PhD., as the Principal Investigator and Michael Jones as the Project Manager. The project is funded by Caltrans Division of Innovation and Research and is being conducted by the Traffic Safety Center of University of California Berkeley and Alta Planning + Design.
Measuring bicycle and pedestrian activity is a key element to achieving the goals of the California Blueprint for Bicycling and Walking (the Blueprint). Meeting these goals, which include a 50% increase in bicycling and walking and a 50% decrease in bicycle and pedestrian fatality rates by 2010, and increases in funding for both programs, will require a quantifiable and defensible base of knowledge. This research helps meet two of the Blueprint’s major strategic objectives: (1) collecting data on volumes and facilities, and (2) determining the most cost-effective methods of estimating bicycle and pedestrian collision rates.
working paper
Modern panel surveys frequently suffer from high and non-ignorable attrition, and transportation surveys suffer from poor travel time estimates. The initial sampling process for most transportation surveys is also non-ignorable since rare travel modes are oversampled (and mode choice is the key dependent variable). This paper examines new multiple imputation methods for adjusting forecasts and model estimates to account for these problems in a new panel survey of 1500 commuters in San Diego, California. These data are collected to evaluate charging solo commuters to use an existing 8-mile underutilized freeway carpool lane. We illustrate the impact of attrition and measurement error on a standard conditional logit model of commuters’ mode choice (solo drive in free lanes, pay to solo drive in the carpool lanes, or carpool for free in carpool lanes). Although the attrition rate between waves is 40% and non-ignorable, the quantitative impact on the results is negligible. However, measurement error in travel time does have an important impact on the key results from our model. Finally, failure to account for the measurement error process using multiple imputations yields a downward bias of at least 50% in the standard errors of the logit coefficient estimates.
working paper |
Nov 1999
working paper |
Apr 1999
working paper |
Jan 2000
conference paper
The current issues and challenges related to the large-scale implementation of intermodal freight transportation systems in the United States and Europe are addressed, and open research issues and challenges are identified. As congestion and environmental impacts continue to worsen, intermodal transportation will continue to increase in importance. Therefore, it is necessary to establish a research agenda for an in-depth study of intermodal freight and logistics issues in the European Union and the United States.
conference paper
Phd Dissertation
This dissertation focuses on the development of optimization methods and approximation algorithms for combinatorial auctions, particularly with application to the contract procurement problem in freight transportation. Combinatorial auctions are auctions in which a set of heterogeneous items are sold simultaneously and in which bidders can bid for their preferred combinations of items. They involve many difficult optimization problems both for auction hosts and bidders and have received significant attention from computer scientists, operations researchers and economists recently. Large shippers (typically manufacturing companies or retailers) have begun to use this method to procure services from trucking companies and logistics services providers. This dissertation first analyzes the economic impact of combinatorial auction-based procurement methods both on shippers and carriers using a simulation study and reveals that both parties can benefit from this economically efficient price discovery mechanism. While the majority of prior research has been from an auctioneer’s perspective, we demonstrate that bidders have even more complicated optimization problems in combinatoiral auctions. The bid construction problem, that is, how bidders should identify and construct beneficial bids, is very hard and remains an open question. This dissertation investigates this problem and proposes an optimization based approximation method that involves solving an NP-hard problem only once, yielding significant improvements in computational efficiency. Further, the current state of trucking and third party logistics industries are examined. The trucking industry is very competitive and small carriers are operating under thin margins. This dissertation addresses these issues by proposing an auction based collaborative carrier network in which participating carriers can identify inefficient lanes from daily operations quickly and exchange them with partners under an auction protocol. This system is proved to be Pareto efficient. Further, decision problems are discussed regarding how carriers should identify inefficient operations and how to make and select bids. This represents an effort to use advanced auction mechanisms to enhance the carriers’ operational efficiencies.
published journal article
published journal article
research report
The increasing diversity of vehicle type holdings and growing demand for BEVs and PHEVs have serious policy implications for travel demand and air pollution. Consequently, it is important to accurately predict or estimate the preference for vehicle holdings of households as well as the vehicle miles traveled by vehicle body- and fuel-type to project future VMT changes and mobile source emission levels. Leveraging the 2019 California Vehicle Survey data, this report presents the application of a utility-based model for multiple discreteness that combines multiple vehicle types with usage in an integrated model, specifically the MDCEV model. The model results suggest the important effects of household demographics, residence location, and built environment factors on vehicle body type and powertrain choice and usage. Further the predictions associated with changes inbuilt environment factors like population density can inform the design of land-use and transportation policies to influence household vehicle holdings and usage that can in turn impact travel demand and air quality issues in California.View the NCST Project Webpage
published journal article
Background. Exposure to high air temperature in late pregnancy is increasingly recognized as a risk factor for preterm birth (PTB). However, the combined effects of heatwaves with air pollution and green space are still unexplored. In the context of climate change, investigating the interaction between environmental factors and identifying communities at higher risk is important to better understand the etiological mechanisms and design targeted interventions towards certain women during pregnancy. Objectives. To examine the combined effects of heatwaves, air pollution and green space exposure on the risk of PTB. Methods. California birth certificate records for singleton births (2005–2013) were obtained. Residential zip code-specific daily temperature during the last week of gestation was used to create 12 definitions of heatwave with varying temperature thresholds and durations. We fit multi-level Cox proportional hazard models with time to PTB as the outcome and gestational week as the temporal unit. Relative risk due to interaction (RERI) was applied to estimate the additive interactive effect of air pollution and green space on the effect of heatwaves on PTB. Results. In total, 1 967 300 births were included in this study. For PM2.5, PM10 and O3, we found positive additive interactions (RERIs >0) between heatwaves and higher air pollution levels. Combined effects of heatwaves and green space indicated negative interactions (RERIs <0) for less intense heatwaves (i.e. shorter duration or relatively low temperature), whereas there were potential positive interactions (RERIs >0) for more intense heatwaves. Conclusion. This study found synergistic harmful effects for heatwaves with air pollution, and potential positive interactions with lack of green space on PTB. Implementing interventions, such as heat warning systems and behavioral changes, targeted toward pregnant women at risk for high air pollution and low green space exposures may optimize the benefits of reducing acute exposure to extreme heat before delivery.
