working paper

Converting Transit to Methanol: Costs and Benefits for California's South Coast Air Basin

Publication Date

July 1, 1987

Author(s)

Stephenie J. Frederick, Jane L.C. Morrison, Kenneth Small

Abstract

Methanol offers much promise as an alternative fuel whose combustion produces no sulfates and fewer nitrogen oxides and particulates than diesel. As another advantage, large quantities could be manufactured from domestic coal supplies. Believing that an extensive methanol program might well begin with public transit, we estimate the costs and benefits of converting the bus fleets of California’s South Coast Air Basin to methanol. Benefits are based on the reduced mortality attributable to lower sulfates and particulates; costs encompass both bus conversion and replacement. Comparing these benefits with costs over a wide range of methanol prices, we find that conversion to methanol merits further consideration as an anti-pollution strategy. We propose to extend the analysis to additional potential benefits and costs, and to other locales and types of vehicles.

Suggested Citation
Stephenie J. Frederick, Jane L.C. Morrison and Kenneth A. Small (1987) Converting Transit to Methanol: Costs and Benefits for California's South Coast Air Basin. Working Paper UCI-ITS-WP-87-3. Institute of Transportation Studies, Irvine. Available at: https://escholarship.org/uc/item/51m882vj.

published journal article

Carless in california: What the carless can tell us about shifting behaviors and improving mobility

Transfers Magazine

Abstract

About 7 percent of California households do not own motor vehicles. Unfortunately, families without cars, trucks, vans, SUVs, or motorbikes are rarely the focus of transportation research and policies, which typically center more on predicting and managing motor vehicle traffic. Widespread automobile ownership has shaped our society by enhancing mobility for most, but these benefits have come at the cost of frequent collisions, heavy traffic congestion, substantial carbon emissions, and widespread noise pollution. In 2015, California Gov. Jerry Brown signed an executive order requiring the state to reduce greenhouse gas emissions to 40 percent below 1990 levels by 2030, accelerating goals previously set by Assembly Bill 32 and Senate Bill 375. While these laws and executive orders have turned reducing vehicle-miles traveled into a prominent policy goal, the path away from an auto-dependent society is far from clear. Accordingly, researchers and policymakers can learn a great deal from the households who live without motor vehicles. To do this, we must first distinguish between â??voluntarily carless households,â?? who have chosen to not own motor vehicles, and â??involuntarily carless households,â?? who are carless by necessity.

Suggested Citation
Jean-Daniel Saphores and Suman K. Mitra (2019) “Carless in california: What the carless can tell us about shifting behaviors and improving mobility”, Transfers Magazine, (4), p. 6p. Available at: https://transfersmagazine.org/wp-content/uploads/sites/13/2019/11/Nov2019_Transfers_Saphores.pdf.

book/book chapter

Road Work: A New Highway Pricing and Investment Policy

Publication Date

January 1, 1989

Author(s)

Kenneth Small, Clifford Winston, Carol A Evans
Suggested Citation
Kenneth A. Small, Clifford Winston and Carol A Evans (1989) Road Work: A New Highway Pricing and Investment Policy. Washington, DC: The Brookings Institution. Available at: https://books.google.com/books?hl=en&lr=&id=KoPaqHQmGkcC&oi=fnd&pg=PA1&dq=KA+small&ots=UKr7ls4fh9&sig=046HGpxgUnrS-rEw4BGyN5JEUEQ#v=onepage&q&f=false.

published journal article

A further exploration of the uncertainty effect

Journal of risk and uncertainty

Publication Date

November 1, 2013

Author(s)

Wendy Wang, Tianjun Feng, Robin Keller
Suggested Citation
Yitong Wang, Tianjun Feng and L. Robin Keller (2013) “A further exploration of the uncertainty effect”, Journal of risk and uncertainty, 47(3), pp. 291–310. Available at: 10.1007/s11166-013-9180-x.

research report

Changes in transit use and service and associated changes in driving near a new light rail transit line

Publication Date

May 1, 2015

Abstract

Los Angeles is pursuing an ambitious rail transit investment program with plans to open six new lines by 2019. This report provides policy makes and planners a better understanding of the potential impacts of Los Angeles Metroâ??s rail transit investment program by assessing the changes in transit use of nearby residents and nearby bus service associated with the Expo Line, the first of the six new lines. The findings indicate that changes in bus service that are coincident with the introduction of new light rail transit can negatively affect the overall transit ridership in the corridor. In addition, households living near new Expo Line light rail stations reduced their vehicle miles traveled (VMT), but those households living near bus stops that were eliminated as part of the service change increased their VMT.

Suggested Citation
Hilary Nixon, Marlon Boarnet, Doug Houston, Steven Spears and Jeongwoo Lee (2015) Changes in transit use and service and associated changes in driving near a new light rail transit line, p. 63p.

published journal article

An exploratory analysis of alternative travel behaviors of ride-hailing users

Transportation

Abstract

The emergence of ride-hailing, technology-enabled on-demand services such as Uber and Lyft, has arguably impacted the daily travel behavior of users. This study analyzes the travel behavior of ride-hailing users first from conventional person- and trip-based perspectives and then from an activity-based approach that uses tours and activity patterns as basic units of analysis. While tours by definition are more easily identified and classified, daily patterns theoretically better represent overall travel behavior but are simultaneously more difficult to explain. We thus consider basic descriptive analyses for tours and a more elaborate approach, Latent Class Analysis, to describe pattern behavior. The empirical results for tours using data from the 2017 National Household Travel Survey show that 76% of ride-hailing tours can be represented by five dominant tour types with non-work tours being the most frequent. The Latent Class model suggests that the ride-hailing users can be divided into four distinct classes, each with a representative activity-travel pattern defining ride-hailing usage. Class 1 was composed of younger, employed people who used ride-hailing to commute to work. Single, older individuals comprised Class 2 and used ride-hailing for midday maintenance activities. Class 3 represented younger, employed individuals who used ride-hailing for discretionary purposes in the evening. Last, Class 4 members used ride-hailing for mode change purposes. Since each identified class has different activity-travel patterns, they will show different responses to policy directives. The results can assist ride-hailing operators in addressing evolving travel needs as users respond to various policy constraints.

Suggested Citation
Rezwana Rafiq and Michael G. McNally (2023) “An exploratory analysis of alternative travel behaviors of ride-hailing users”, Transportation, 50(2), pp. 571–605. Available at: 10.1007/s11116-021-10254-9.

published journal article

Integrating resident digital sketch maps with expert knowledge to assess spatial knowledge of flood risk: A case study of participatory mapping in Newport Beach, California

Applied Geography

Publication Date

September 1, 2016

Author(s)

Wing Cheung, Doug Houston, Jochen E. Schubert, Victoria Basolo, David Feldman, Richard Matthew, Brett F. Sanders, Beth Karlin, Kristen A. Goodrich, Seth Contreras, Adam Luke
Suggested Citation
Wing Cheung, Douglas Houston, Jochen E. Schubert, Victoria Basolo, David Feldman, Richard Matthew, Brett F. Sanders, Beth Karlin, Kristen A. Goodrich, Santina L. Contreras and Adam Luke (2016) “Integrating resident digital sketch maps with expert knowledge to assess spatial knowledge of flood risk: A case study of participatory mapping in Newport Beach, California”, Applied Geography, 74, pp. 56–64. Available at: 10.1016/j.apgeog.2016.07.006.

published journal article

Truck body type classification using a deep representation learning ensemble on 3D point sets

Transportation Research Part C: Emerging Technologies

Abstract

Understanding the spatiotemporal distribution of commercial vehicles is essential for facilitating strategic pavement design, freight planning, and policy making. Hence, transportation agencies have been increasingly interested in collecting truck body configuration data due to its strong association with industries and freight commodities, to better understand their distinct operational characteristics and impacts on infrastructure and the environment. The rapid advancement of Light Detection and Ranging (LiDAR) technology has facilitated the development of non-intrusive detection solutions that are able to accurately classify truck body types in detail. This paper proposes a new truck classification method using a LiDAR sensor oriented to provide a wide field-of-view of roadways. In order to enrich the sparse point cloud obtained from the sensor, point clouds originating from the same truck across consecutive frames were grouped and combined using a two-stage vehicle reconstruction framework to generate a dense three-dimensional (3D) point cloud representation of each truck. Subsequently, PointNet – a deep representation learning algorithm – was adopted to train the classification model from reconstructed point clouds. The model utilizes low-level features extracted from the 3D point clouds and detects key features associated with each truck class. Finally, model ensemble techniques were explored to reduce the generalization error by averaging the results of seven PointNet models and further enhancing the overall model performance. The optimal number of models in the ensemble was determined through a comprehensive sensitivity analysis with the consideration of the average correct classification rate (CCR), the variability of the prediction results, and the computation efficiency. The developed model is capable of distinguishing passenger vehicles and 29 different truck body configurations with an average CCR of 83 percent. The average correct classification rate of the developed method on the test dataset was 90 percent for trucks pulling a large trailer(s).

Suggested Citation
Yiqiao Li, Koti Reddy Allu, Zhe Sun, Andre Y. C. Tok, Guoliang Feng and Stephen G. Ritchie (2021) “Truck body type classification using a deep representation learning ensemble on 3D point sets”, Transportation Research Part C: Emerging Technologies, 133, p. 103461. Available at: 10.1016/j.trc.2021.103461.

published journal article

An Approach to Assessing Freeway Lane Management Hot Spots

Transportation Research Record: Journal of the Transportation Research Board

Publication Date

January 1, 2009

Abstract

This research presents a procedure for capitalizing on the trade-off between urban freeway managed lanes and general purpose lanes that compete for limited road space. The basic goal of the procedure is to provide policy guidance for sharing any excess lane capacity on a timely and efficient basis. Potential operating policy options for these two types of lanes are categorized as “do nothing,” “lane management,” and “more than lane management.” The “lane management” condition recognizes the extent and duration of a “hot spot” as defined by underutilized managed lanes with congested general purpose lanes, or vice versa. Four major and three minor lane management hot spots are deterministically and stochastically captured along a 24-mi freeway stretch in California. The major hot spots account for 8.3% of the total time–space set. The approach, which can also be applied to predict upcoming hot spots, generates satisfying accuracy. Finally, strategies are proposed to prevent the hot spots, and the effects of lane management are estimated. The application of this approach is useful especially for managed lanes with limited access points that prohibit arbitrary lane changing.

Suggested Citation
Chih-Lin Chung and Wilfred W. Recker (2009) “An Approach to Assessing Freeway Lane Management Hot Spots”, Transportation Research Record: Journal of the Transportation Research Board, 2099(1), pp. 141–150. Available at: 10.3141/2099-16.

conference paper

Interactive simulation for modeling dynamic driver behavior in response to ATIS

Proceedings of the ASCE Fifth International Conference on Computing in Civil and Building Engineering

Publication Date

January 1, 1993
Suggested Citation
Jeffrey L. Adler, Michael G. McNally and Wilfred W. Recker (1993) “Interactive simulation for modeling dynamic driver behavior in response to ATIS”, in Proceedings of the ASCE Fifth International Conference on Computing in Civil and Building Engineering. New York, NY: American Society of Civil Engineers, pp. 591–598.