working paper
The length of the urban work trip, and especially how it is influenced by land-use patterns, have become critical issues for urban economic theory and for public policy toward transportation and land use. Many economic models and policy analyses hinge on the belief that land-use patterns affect commuting importantly; yet the empirical evidence for this belief is weak. In this paper, we use disaggregate data for a very large urban region to examine this key relationship anew.
working paper |
Sep 1991
working paper |
Jun 1991
working paper |
Oct 1991
published journal article
Change in local land use policy is generally a necessary precursor to future land use changes. Using the recently opened Century Freeway/Transitway (I-105) in Los Angeles County as a case study, this article examines the land use policy responses of local jurisdictions traversed by a new transportation facility. Focusing on this local policy context, we analyze former and current general plans and zoning ordinances from the 13 jurisdictions near che freeway/transitway and we interview city managers or directors of community development from each jurisdiction. Changes have most often been to foster commercial and mixed use designation. However, our analysis of zoning changes in che corridor area also indicates that some jurisdictions are attempting co deintensify land uses, and this dynamic is even more evident when a wider analysis area of the affected jurisdictions is employed (one mile band). We offer several reasons for these results and comment on relevance to an understanding of accessibility.
conference paper
The San Pedro Bay Ports (SPBP) of Los Angeles and Long Beach in Southern California is one of the largest port container complexes in the world, and the largest one is the United States. To decrease the air pollution associated with port operations, a number of measures have been adopted, including the Clean Trucks Program, which was introduced in 2008 to modernizing and clean up the fleet of drayage trucks serving the SPBP. The objective of this paper is to quantify the reduction in emissions attributable to the Clean Trucks Program, with a focus on Nitrogen Oxide (NOx) and Particulate Matter (PM2.5). The authors approach is innovative as it relies on micro-simulation (TransModeler) to capture the link between congestion and pollutant emissions. The authors find that the Clean Trucks Program could contribute significantly to the emissions of NOx (~27%) and PM2.5 (~25%) for all the freeway traffic in the study area. These preliminary results suggest that the Clean Trucks Program is promising, but its cost-effectiveness should be analyzed.
conference paper
Given that small fleets (defined as those with 20 or fewer vehicles) represent a considerable portion of the heavy-duty vehicle (HDV) sector, understanding their perspectives, along with those of large fleets, on zero-emission vehicles (ZEVs) and related policies is crucial for achieving the U.S. HDV sector’s ZEV transition goals. However, research focusing on small fleets or comparing both segments has been limited. Focusing on California’s drayage sector with stringent ZEV transition targets, this study investigates the awareness and perceptions of small and large fleet operators on ZEV technologies and policies established to promote ZEV adoption. Using a fleet survey, we obtained 71 responses from both small and large fleets. We employed a comprehensive exploratory approach, utilizing descriptive analysis, hypothesis testing, and thematic analysis. Findings reveal that both segments generally rated their ZEV knowledge as close to neutral, with about a third reporting limited awareness of the ZEV policy. Both segments highlighted various adoption barriers, including challenges with infrastructure, costs, and operational compatibility. Business strategies under the ZEV policy differed significantly: small fleets planned to delay or avoid ZEV procurement, with some considering relocation, while large fleets were more proactive, with many already having procured or preparing to procure ZEVs. Both segments voiced concerns about the disproportionate impact on small fleets. The findings enhance our understanding of equity issues in ZEV adoption across fleet segments and offer valuable insights for policymakers committed to a more equitable distribution of the impacts.
published journal article |
Apr 2024
conference paper
Gross Vehicle Weight Rating (GVWR)-based vehicle activity data is widely used in freight planning, fuel efficiency evaluation, and on-road emission estimation. However, a vehicle’s GVWR remains challenging to obtain using existing highway sensor infrastructure. This paper describes a novel approach to acquire GVWR-based classification data through the fusion of two complementary infrastructure-based sensing technologies: inductive loop sensors and side-fire video cameras. While inductive loops are widely deployed in the U.S., they only provide single-dimensional data with limited information. Side-fire cameras can offer richer details to enhance vehicle classification. Accordingly, an open-source intelligence (OSINT) method was used to establish a GVWR-based vehicle dictionary, linking vehicle specifications from online data sources to GVWR classes. A dataset comprising 9,154 vehicle inductive loop signatures paired with images was then collected and annotated according to the pre-defined dictionary. Next, signature-based and image-based classification models were developed for GVWR classification. Each model was designed to function independently. A signature-based GVWR classification model was trained with a multi-layer perceptron (MLP) neural net architecture and optimized through the implementation of a weighted cross-entropy loss function. A two-stage image-based GVWR classification framework was designed to extract vehicle objects and classify them based on the GVWR scheme. Finally, a linear fusion model was implemented to combine the output of the signature- and image-based models to achieve an improvement over each standalone classification model. The sensor fusion framework significantly outperformed each individual sensing technology, achieving an average correct classification rate of 0.97 and an score of 0.96, which surpasses state-of-the-art methods.
working paper
The paper reports on the analysis of violation and crash data as part of an evaluation of the impact on traffic safety of the San Diego Photo Red Light Enforcement System. The system was found to have resulted in a statistically significant reduction in the number of red light running violations. The decreases in violations occurred at almost all camera enforced intersections and the decreases continued, at a diminishing rate, throughout the period the cameras were operated. The impact on traffic safety was more complex. For traffic traveling in the enforced direction at intersections with red light cameras, crashes attributable to red light running decreased after implementation to approximately 60 percent of pre-enforcement rates, while rear end crashes increased to approximately 140 percent of pre-implementation levels. These before-and-after changes in crash rates were statistically significant, while there were no significant changes in crash rates for traffic traveling in directions not covered by the red light cameras. In addition, it is concluded that photo enforcement was more effective in reducing crashes at intersections where through movement was enforced, than where left turns were enforced.
published journal article
book/book chapter
published journal article
As dynamic traffic simulation (DTS) becomes ever more popular, how to provide the input data, that is, a dynamic originâ??destination (O-D) table, for simulation becomes an important question. During recent years, many researchers have proposed estimation methods for a dynamic O-D table from an academic point of view, but transportation engineers appear to use the dynamic approach in practical applications rarely. In recent simulation projects, ad hoc schemes have been used by practitioners for developing dynamic O-D tables for subareas from larger, static planning O-D tables without much theoretical soundness. The authors developed a dynamic O-D estimation model based on a path-flow approach and iterative simulations, along with a scheme to find a justifiable seed O-D table, and applied it to a real-world context. A major arterial corridor in Suwon, South Korea, was selected, and the link turning counts were collected at intersections. A microscopic DTS model, PARAMICS, was used with the dynamic O-D table to simulate link turning counts. The test results show that the developed O-D estimation technique is efficient, with simulated link traffic counts and section travel times very close to the reality.
published journal article
