working paper

A Statewide Optimal Resource Allocation Tool Using Geographic Information Systems, Spatial Analysis, and Regression Methods

Abstract

The overall objective of this project is to develop an optimal resource allocation tool for the entire state of California using Geographic Information Systems and widely available data sources. As this tool evolves it will be used to make investment decisions in transportation infrastructure while accounting for their spatial and social distribution of impacts. Tools of this type do not exist due to lack of suitable planning support tools, lack of efforts in assembling data and information from a variety of sources, and lack of coordination in assembling the data. Suitable planning support tools can be created with analytical experimentation to identify the best methods and the first steps are taken in this project. Assembly of widely available data is also demonstrated in this project. Coordination of fragmented jurisdictions remains an elusive task that is left outside the project. When this project begun we confronted some of these issues and embarked in a path of feasibility demonstration in the form of a pilot project that gave us very encouraging results. In spite of this pilot nature aiming at demonstration of technical feasibility, substantive conclusions and findings are also extracted from each analytical step.

In this project we have two parallel analytical tracks that are a statewide macroanalysis (called the zonal based approach herein) and an individual and household based microanalysis (called the person based approach herein). In the statewide macroanalysis we study efficiency and equity in resource allocation. Resources are intended as infrastructure availability and access to activity participation offered by the combined effect of transportation infrastructure and land use measured by indicators of accessibility. Stochastic frontiers are used to study efficiency and a particular type of inequality measurement called the Theil fractal inequality index is used to study equity in the macroanalysis. The outcome of this analysis are maps identifying places in California that enjoy higher levels of service when compared to the entire state and places which succeeded in allocating resources in a relatively better way than others. In the individual microanalysis we use the accessibility indicators from the macronalysis and expand them by defining a new set of indicators at a second level of spatial (dis)aggregation. Then we use them as explanatory factors of travel behavior with focus on the use of different travel models (e.g., driving alone, use of public transportation and so forth). As expected infrastructure availability and accessibility to activity opportunities has a significant and substantive effect on the use of different modes. Many resource allocation decisions, then, will impact behavior, which in turn influences the optimality and equity conditions. This implies that decisions about where and when to allocate resources in public and private transportation needs to account for changes in behavior in a dynamic fashion, using scenarios of accessibility provision and assessing their impact by studying activity and travel behavior changes.

working paper

Development of Hardware in the Loop Simulation and Paramics/VS-PLUS Integration

Abstract

The report describes three research efforts carried out under a project titled “Development of Hardware-in-the-Loop (HiL) Simulation and Paramics/VS-PLUS Integration” sponsored by the California Department of Transportation (Caltrans) under Task Order 5311. The first effort developed and evaluated traffic signal optimization with Hardware-in-the-Loop Simulation (HiLS), using the NIATT Controller Interface Device (CID) manufactured by McCain Traffic Supply to provide real-time linkage between the Paramics microscopic simulation and a NEMA TS1 controller. An adaptive control system incorporated the traffic flow prediction model to predict the traffic flows from the surrounding intersections, and an online signal optimization model was used to obtain the signal timing plan for the subsequent cycle, based on the traffic flows predicted in the previous cycle. The performance of the proposed adaptive control system was evaluated through a case study in which HiLS is applied to a small urban network in Logan, Utah. The second effort developed a Paramics plug-in that worked over a serial port connection to a specially modified 170 for HiL operation. After this initial development, the NIATT/McCain CID was configured to work as a Paramics plug-in with both 170 and 2070 controllers, and experiments were carried out to compare the performance of Paramics simulations with the UC Irvine Paramics signal controller plug-in with HiLS. In the third effort, investigation and evaluation of integrated Paramics/VS-PLUS software was carried out, resulting in a user’s guide for use of the integrated Paramics/VS-PLUS simulation software.

Phd Dissertation

Operational Strategies for Single-Stage Crossdocks

Publication Date

October 27, 2008

Abstract

Because of the growing importance of hub-and-spoke operations in the trucking industry, crossdocking has become an important and effective tool to transfer freight. Companies like Wal-Mart, Costco and Home Depot are using this kind of facility in their logistics operations. In these crossdocks, efficiently operating them, thereby reducing unnecessary waiting and staging congestion for freight and workers is an important issue for managers.

This dissertation uses real-time information about the contents of inbound and outbound trailers and the locations of pallets to schedule unloading for waiting trailers or assign destinations for unloading pallets: we choose a waiting trailer that will need the least time for its pallets and existing pallets; and we may assign an alternate destination for a pallet if its primary destination is expected to encounter congestion. Two dynamic trailer scheduling and four alternate destination strategies are proposed and compared with baseline scenarios.

Our simulation results suggest that:

1. Our strategies are effective. The two time-based trailer scheduling algorithms can save cycle times as much as 64%, 57% and 30% in the 4-to-4, 4-to-8 and 8-to-8 crossdock scenarios, respectively; the four alternate destination strategies can save cycle times as much as 34% in the 8-to-8 staging crossdock scenarios. In addition, these strategies can raise throughputs for crossdocks. These effects should result in noticeable improvements in supply chain networks, including shorter transportation lead-times, more reliable on-time deliveries and lower inventory costs.

2. In our alternate destination strategies, even if a destination-change results in extra time for value-added services for freight, the strategies are still worth adopting.

3. The combination models of our trailer scheduling algorithms and alternate destination strategies work better than solely implementing an alternate destination strategy when trailer arrivals are dense.

4. A higher flexibility in choosing alternate destinations can bring higher performance for crossdocks.

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

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

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

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)

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

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

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.