working paper

A California Statewide Exploratory Analysis Correlating Land Use Density, Infrastructure Supply and Travel Behavior

Publication Date

September 30, 2008

Author(s)

Thomas Golob, Konstadinos Goulias

Areas of Expertise

Travel Behavior, Land Use, & the Built Environment

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Abstract

In this paper land use densities by type of employment and infrastructure supply are used together with social and demographic characteristics to explain non-motorized travel, transit use, and solo driving in California. The land use database, the highway network database, and the travel survey used for the analysis here covers the entire state of Califonia. Land use and infrastructure have a significant, substantial, and very different role for each behavior indicator used here. They alternate in significance and importance depending on the specific behavior analyzed. We also performed experiments to identify the appropriate geographical aggregation by comparing US Census tract vs US Census block group based land use densities and infrastructure densities. Regression models gave us mixed results leading us to suggest the use of a combination between the two geographies. Next steps are also outlined in the paper.

working paper

Evaluation of Incorporating Hybrid Vehicle Use of HOV Lanes

Publication Date

September 30, 2008

Author(s)

David Brownstone, Lianyu Chu, Thomas Golob, Will Recker

Areas of Expertise

Infrastructure Delivery, Operations, & Resilience Zero-Emission Vehicles & Low-Carbon Fuels

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Abstract

This report presents a method to investigate the operational and environmental effects of the policy of allowing qualified single-occupancy hybrid vehicles to use dedicated High-Occupancy Vehicle (HOV)/carpool lanes in California.. The method combines the traditional planning method with microscopic simulation modeling. The planning method is used for demand estimation and analysis and the microscopic traffic simulation modeling method is used for accurate measures of the system. The study employs a microscopic traffic simulation model that is capable of evaluating the HOV/hybrid system and providing detailed outputs that are not available in conventional static models. The study also includes detailed emissions modeling in order to estimate accurate emissions by integrating emission models into microscopic simulation models. An important aspect of the study involves predicting future hybrid vehicle demand; hybrid demand models are developed based on consumers’ automobile choice behavior analysis. This is modeled both with standard network calculations employing network assignments sensitive to time savings from HOV lane use as well as using estimates of the locations of households owning hybrid vehicles and the O-D matrices for the hybrid drivers. We use these results to modify existing models to enhance their accuracy for hybrid vehicles. The updated models are then be applied to data from the recent Caltrans 2000-2001 Statewide Household Travel Survey and the 2001 National Household Travel Survey (NHTS). These survey data allow us to locate the households and trip destinations of likely hybrid vehicle owners. Results from previous studies of demand for toll lanes have established monetary values of saved travel time that can be applied to estimated time savings from network simulations to forecast incentives for purchase of hybrid vehicles. We also develop a supply-side model to estimate availability and prices of hybrid vehicles by body type and manufacturer and price in order to forecast penetration of hybrid vehicles. A total of four different scenarios were constructed. With the assumption that the total demand for all scenarios remains the same and the hybrid-HOV policy results in some solo drivers switching to hybrid vehicle drivers, these four scenarios are evaluated in terms of a set of operational performance measures and air quality measures. The key findings from this study are summarized as follows:

•The initial wave of single occupant hybrid vehicles entering the HOV lanes do not have a substantial negative impact on HOV lane operations.

•A hybrid demand exceeding 50 thousand statewide will have significant impact on the HOV lane operations in OC.

•From the air quality perspective, a high share of hybrid vehicles will cause fewer emissions.

working paper

Corridor Deployment and Investigation of Anonymous Vehicle Tracking for Real-Time Traffic Performance Measurement

Publication Date

September 30, 2008

Author(s)

Stephen Ritchie, Shin-Ting (Cindy) Jeng, Seri Park

Areas of Expertise

Intelligent Transportation Systems, Emerging Technologies, & Big Data

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Abstract

This report presents the results of a multi-year research effort on the development of a real-time section-based traffic performance measurement system using inductive vehicle signatures obtained from single conventional loop sensors along a six-mile freeway corridor in the City of Irvine, California and a separate effort to investigate the potential of a new type of inductive sensor called the Blade™ for the purpose of commercial vehicle surveillance at the San Onofre Truck Weigh and Inspection Facility in Southern California. The real-time performance measurement system (RTPMS) is based on a new vehicle reidentification algorithm called RTREID-2 and vehicle classification model, both of which are based on a new data extraction method that extracts an equal number of Piecewise Slope Rate (PSR) values from each vehicle signature. As a part of this study, a framework based on CORBA was developed to enable communication between field computers and the RTPMS server. A database system was also developed to store the output from the RTPMS server and present it in a prototype RTPMS Testbed Website that presents advanced real-time traffic performance measures. In the separate investigation of Blade™ inductive sensors, a new commercial vehicle classification model was developed to profile commercial vehicles by their body type and axle configuration. A new commercial vehicle vector classification framework is introduced to describe the depth of information available from this developed model. The results obtained from both studies have yielded very promising results, and warrants the need for further investigation.

research report

Development of an Adaptive Corridor Traffic Control Model (PATH TO 6323)

Publication Date

September 30, 2008

Author(s)

Will Recker

Areas of Expertise

Infrastructure Delivery, Operations, & Resilience Intelligent Transportation Systems, Emerging Technologies, & Big Data

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Abstract

This report documents work performed on PATH TO 5323. Due to an administrative mandate, the work performed and reported herein constitutes only the early stages of the multi-year project that was approved under PATH TO 5323, and subsequently divided into two distinct awards—TO 5323 and TO 6323. Moreover, a series of events during the early stages of the project substantially redirected the original effort. These factors led to a major redirection from the original project. The majority of the work performed under the revised TO 5323 was then to develop a methodology consistent with the new direction of the project, which is detailed in this report.

Under the revised direction, the objective of the project is to develop and implement a real-time adaptive control system for corridor management. The proposed control strategy is based on a mathematical representation that describes the behavior of the real-life processes (traffic flow in corridor networks and actuated controller operation). In formulating the optimal control problem, we have restricted our attention to control of only those parameters commonly found in modern actuated controllers (e.g., Type 170 and 2070 controllers). By doing this, we hope to ensure that the procedures developed herein can be implemented with minimal adaptation of existing field devices and the software that controls their operation.

Phd Dissertation

Network Design Formulations, Modeling, and Solution Algorithms for Goods Movement

Publication Date

September 16, 2008

Author(s)

Pruttipong Apivatanagul

Areas of Expertise

Freight, Logistics, & Supply Chain

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Abstract

Efficient fright transportation is essential for a strong economic system. Increases in demands for freight transportation, however, lessens the efficiency of existing infrastructure. In order to alleviate this problem effectively, evaluation studies must be performed in order to invest limited resources for maximum social benefits. In addition to many difficulties related to evaluating individual projects, complimentary and substitution effects that occur when considering transportation projects together must be properly accounted for. Current practices, however, limit the number of projects that can feasibly be considered at one time.

This dissertation proposes network design models which can automatically create project combinations and search for the best of these. Network design models have been studied for the passenger movements and focus on highway expansions. In this dissertation, the focus is shifted to freight movements which involve multimodal transportation improvements. A freight network design model is developed based on a bi-level optimization model. The development then involves two components. The first task is to set the freight investment problems within the bi-level format. This includes finding a suitable freight flow prediction model which can work well with the bi-level model. The second task is to provide a solution algorithm to solve the problem.

The dissertation sets the framework of the freight flow network design model, identifies expected model issues, and provides alternatives that alleviate them. Through a series of developments, the final model uses a shipper-carrier freight equilibrium model to represent freight behaviors. Capacity constraints are used as a means to control service limitations since reliability issues, an important factor for freight movements, cannot be captured by steady state traffic assignment. A case study is implemented to allocate a budget for improvements on the California highway network. The transportation modes are selected by the shipper model which can include truck, rail, or multimodal transportation. The results shown that the proposed network design model provides better solutions compared with traditional ranking methods. The solution algorithm can manage the problem with a reasonable number of project alternatives.

BEng/PhD/MS Thesis

Commercial vehicle classification system using advanced inductive loop technology

Publication Date

September 7, 2008

Associated Project

Measuring Commercial Vehicle Travel Through New High Fidelity Inductive Sensors

Author(s)

Andre (Yeow Chern) Tok

Areas of Expertise

Freight, Logistics, & Supply Chain Intelligent Transportation Systems, Emerging Technologies, & Big Data

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Abstract

Commercial vehicles typically represent a small fraction of vehicular traffic on most roadways. However, their influence on the economy, environment, traffic performance, infrastructure, and safety are much more significant than their diminutive numerical presence suggests. This dissertation describes the development and prototype implementation of a new high-fidelity inductive loop sensor and a ground-breaking commercial vehicle classification system based on the vehicle inductive signatures obtained from this sensor technology. This new sensor technology is relatively easy to install and has the potential to yield reliable and highly detailed vehicle inductive signatures for advanced traffic surveillance applications. The Speed PRofile INterpolation Temporal-Spatial (SPRINTS) transformation model developed in this dissertation improves vehicle signature data quality under adverse traffic conditions where acceleration and deceleration effects can distort inductive vehicle signatures. The axle classification model enables commercial vehicles to be classified accurately by their axle configuration. The body classification models reveal the function and unique impacts of the drive and trailer units of each commercial vehicle. Together, the results reveal the significant potential of this inductive sensor technology in providing a more comprehensive commercial vehicle data profile based on a unique ability to extract both axle configuration information as well as high fidelity undercarriage profiles within a single sensor technology to provide richer insight on commercial vehicle travel statistics.

working paper

Commercial Vehicle Classification using Vehicle Signature Data

Publication Date

August 30, 2008

Author(s)

Hang Liu, Shin-Ting (Cindy) Jeng, Andre (Yeow Chern) Tok, Stephen Ritchie

Areas of Expertise

Freight, Logistics, & Supply Chain Intelligent Transportation Systems, Emerging Technologies, & Big Data

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Abstract

Knowledge of vehicle classes is especially useful for monitoring commercial vehicles (CVs). Accurate CV class information will enhance truck traffic surveillance and fleet management, such as in port areas by providing information for environmental impact investigations. From an implementation perspective, it is recognized that there are often significant advantages to use the existing inductive loop infrastructure. However, inductive loops are not always the most practical surveillance technology considering the required implementation effort and cost. In this regard, this study explored the potential of adopting a new vehicle signature detection technology – wireless magnetic sensors – for CV classification. The vehicle signature data used for the development of the wireless sensor based models was collected from the University of California, Irvine (UCI) Commercial Vehicle Study Test-bed in San Onofre, California. Vehicle signatures from round inductive loop sensors were also collected for refining an existing round loop based model and for comparison purposes. Significant dropped data was observed in the wireless sensor signatures, which required the implementation of a dual sensor data recovery procedure to reconstruct the signatures, which would otherwise have been unusable. The results indicate that the single wireless sensor vehicle classification model, which is based on multi-layer perceptron neural network, successfully distinguished single-unit and multi-unit trucks with 93.5% accuracy. The double wireless sensor vehicle classification model, which adopted a K-means clustering and discriminant function, achieved 73.6% accuracy, while the round loop based model produced even better performance (85%) in testing, both according to the FHWA scheme F with 13 classes.

conference paper

Tradeoffs among Free-flow Speed, Capacity, Cost, and Environmental Footprint in Highway Design

Publication Date

August 27, 2008

Associated Project

Costs and Effectiveness of Lower-Speed, Environmentally-Friendly Urban Highway Designs

Author(s)

Chen Ng, Kenneth Small

Areas of Expertise

Infrastructure Delivery, Operations, & Resilience

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Abstract

This paper investigates differentiated design standards as a source of capacity additions that are more affordable and have smaller aesthetic and environmental impacts than expressways. We consider several tradeoffs, including narrow versus wide lanes and shoulders on an expressway of a given total width, and high-speed expressway versus lower-speed arterial. We quantify the situations in which off-peak traffic is sufficiently great to make it worthwhile to spend more on construction, or to give up some capacity, in order to provide very high off-peak speeds even if peak speeds are limited by congestion. We also consider the implications of differing accident rates. The results support expanding the range of highway designs that are considered when adding capacity to ameliorate urban road congestion.

Phd Dissertation

Urban location models with amenities, agglomeration economies, congestion, and open space

Publication Date

June 29, 2008

Author(s)

Chen Ng

Areas of Expertise

Travel Behavior, Land Use, & the Built Environment

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Abstract

This dissertation contains two standalone essays in which urban location models are developed to analyze various issues in urban and transportation economics related to commuting distances, location patterns, and urban sprawl. The first essay examines possible reasons for ‘wasteful’ or ‘excess’ commuting, whereby observed commuting distances generally exceed those predicted by standard models of household location choice. It is likely that households are willing to accept a longer commute to work if proximity to certain amenities is important to them. To examine this issue, a model with two job centers, a central business district (CBD) and a subcenter, is developed. Households are assumed to either have preferences for amenities (which are located in the CBD), or they do not, regardless of job location. It is shown that households who work in the subcenter but who like the amenities in the CBD may be willing to locate further from their jobs in order to be closer to the amenities (thus increasing average commuting distance in the city), especially when proximity to the amenities is highly valued. The second essay focuses on urban sprawl and the effects of different anti-sprawl policies on welfare and urban structure. A model with heterogeneous households and firms that can locate anywhere in the city is developed. The main features of the model are traffic congestion and household preferences for open space, both of which are closely associated with urban sprawl. The model also includes agglomeration economies, providing a more complete picture of how firms choose locations. Numerical results show equilibrium location patterns, rents, and wages under different model specifications. The model is then used to analyze the impacts of two popular anti-sprawl policies: congestion tolling and an urban growth boundary. The results suggest that congestion tolls may decrease welfare if unsubsidized agglomeration economies are very high, because higher travel costs lead to the decentralization of firms. Meanwhile, the urban growth boundary increases the amount of open space but reduces the supply of land for residences and offices, and is welfare-improving only if household preferences for open space are very strong.

Phd Dissertation

Essays in transportation economics

Publication Date

June 14, 2008

Author(s)

Vivek Pai

Areas of Expertise

Transportation Economics, Funding, & Finance

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Abstract

This dissertation uses industrial organization and econometric techniques in the analysis of transportation issues. The first chapter, titled “The Impact of Regional Jets on Airline Networks” examines the impact of a new technology, in the form of regional jets, on the US airline industry. Similar to large jets, Regional Jets have a lower threshold for providing profitable service. The chapter develops a theoretical framework that predicts passengers with high schedule-delay costs (i.e., business travelers) would take a direct flight that uses a regional jet. Data from 1997 to 2005 are then analyzed to see the impact of regional jet use on hub-spoke and point-to-point service. The second chapter, “Factors that Affect Airline Flight Frequency and Aircraft Size,” assesses the determinants of aircraft size and frequency of flights on airline routes by considering market demographics, airport characteristics, airline characteristics, and route characteristics. The chapter shows that frequency and aircraft size increase with population, income, and runway length. An increase in the proportion of managerial workers in the labor force or the proportion of population below the age of 25 results in greater frequency with the use of small planes. Slot constrained airports and an increase in the number of nearby airports lead to lower flight frequency with the use of smaller planes. Hubs and low cost carriers are associated with larger plane sizes and higher frequency, while regional airline ownership leads to higher frequency and the use of smaller planes. An increase in distance between the endpoints leads to lower frequency with the use of larger planes. As airport delay rises, airlines reduce frequency and use smaller planes, though when airport cancellations rise, flight frequency increases with the use of larger planes. This finding suggests airlines utilize frequency and aircraft size to hedge against flight cancellations. The third chapter, titled “Road Congestion Tolling under Competition,” introduces a tolled road that congests the un-tolled alternative to the model proposed by Verhoef, Nijkamp and Rietveld (1996) and analyzes the toll and welfare outcomes under a social planner’s prospective.