research report

Experimental Studies of Traffic Incident Management with Pricing, Private Information, and Diverse Subjects

Phd Dissertation

Land Use, Land Value, and Transportation : Essays on Accessibility, Carless Households, and Long-distance Travel

Publication Date

September 15, 2016

Author(s)

Abstract

During the last two decades, a large body of empirical research has focused on the relationship between land use and travel behavior, and also on the impacts of transportation accessibility on land value. However, significant gaps remain in our understanding of these relationships. In this dissertation, I present three essays on accessibility, carless households, and long-distance travel that will enhance our understandings of relationships among land use, land value, and transportation. (Abstract shortened by ProQuest.).

Phd Dissertation

Integration of Information of Transportation Flows in Disaster Relief Logistics Modeling

Abstract

Disasters, specifically earthquakes, result in worldwide catastrophic losses annually. The first seventy-two hours are the most critical and so any reduction in response time is a much-needed contribution. This is especially true in cases where parts of the communication infrastructure are severely damaged. Traditional disaster relief logistics models tend to rely on the assumption that information flow is continuous throughout the system following the onset of a natural disaster. A new integrated framework for disaster relief logistics that optimizes the movement of critical information along with physical movements is proposed in order to alleviate post-disaster conditions in a more accurate and timely manner. The framework consists of an information network and a transportation network with interrelationships. The framework was applied to the Irvine Golden Triangle Network and the Knoxville Network for up to three different cases. The DYNASMART-P simulation program performance was compared against the Time Dependent Network Simplex paths approach combined with the information updating feedback loop. The average total travel times of vehicles travelling to the trauma center in the study areas were compared in order to quantify the improvements of the integrated solution framework. The results show a significant reduction of average total travel times for vehicles transporting injured patients to the trauma center.

Phd Dissertation

An optimization Framework for Shared Mobility in Dynamic Transportation Networks

Publication Date

July 15, 2016

Author(s)

Abstract

Recent advances in communication technology coupled with increasing environmental concerns, road congestion, and the high cost of vehicle ownership have directed more attention to the opportunity cost of empty seats traveling throughout the transportation networks every day. Peer-to-peer (P2P) ridesharing is a good way of using the existing passenger-movement capacity on the vehicles, thereby addressing the concerns about the increasing demand for transportation that is too costly to address via infrastructural expansion.

This dissertation is dedicated to the optimization of the matching process between the participants in a ridesharing system. More specifically, focus of this dissertation is on multi-hop matching, in which riders have the possibility of transferring between vehicles. Different algorithms have been presented for various implementation strategies of ridesharing systems. Multiple case studies assess the important role ridesharing can play as a separate mode, or in conjunction with other modes of transportation, in multi-modal settings.

research report

Analyzing the 2012 California Household Travel Survey using R: Summary

Abstract

The 2010-12 CHTS, which resulted from a statewide, collaborative effort, enabled the collection of travel information from 42,560 Californian households. This rich dataset has helped update regional and statewide travel and will help update environmental models.
In 2014, the Institute of Transportation Studies at Irvine (ITS) and Caltrans initiated the “Enhancing the Value of the 2010-12 California Household Travel Survey (CHTS)” contract. This contract was motivated by the idea that potential value of the CHTS is not always well understood by Caltrans staff and that some Caltrans staff from the Office of Travel Forecasting and Analysis may benefit from updating their knowledge of statistical modeling to comfortably query CHTS data and to estimate some common transportation econometrics models.
The this document provides numerous examples of how to perform various types of statistical analysis on the CHTS. In chapter 2, we discuss the computation of statistical weights for various subpopulations in the CHTS—a critical component of any analysis involving the CHTS. In chapter 3, we cover the creation of a “linked trip” dataset, which provides a means for analyzing CHTS data in a manner that is compatible with conventional 4-step, trip based models. Finally, chapter 4 describes the solution of a number of statistical queries that were answered under task 4 statistical support tasks.

Phd Dissertation

Computational Models for Scheduling in Online Advertising

Publication Date

June 30, 2016

Author(s)

Abstract

Programmatic advertising is an actively developing industry and research area. Some of the research in this area concerns the development of optimal or approximately optimal contracts and policies between publishers, advertisers and intermediaries such as ad networks and ad exchanges. Both the development of contracts and the construction of policies governing their implementation are difficult challenges, and different models take different features of the problem into account. In programmatic advertising decisions are made in real time, and time is a scarce resource particularly for publishers who are concerned with content load times. Policies for advertisement placement must execute very quickly once content is requested; this requires policies to either be pre-computed and accessed as needed, or for the policy execution to be very efficient. We formulate a stochastic optimization problem for per publisher ad sequencing with binding latency constraints. Within our context an ad request lifecycle is modeled as a sequence of one by one solicitations (OBOS) subprocesses/lifecycle stages. From the viewpoint of a supply side platform (SSP) (an entity acting in proxy for a collection of publishers), the duration/span of a given lifecycle stage/subprocess is a stochastic variable. This stochasticity is due both to the stochasticity inherent in Internet delay times, and the lack of information regarding the decision processes of independent entities. In our work we model the problem facing the SSP, namely the problem of optimally or near-optimally choosing the next lifecycle stage of a given ad request lifecycle at any given time. We solve this problem to optimality (subject to the granularity of time) using a classic application of Richard Bellman’s dynamic programming approach to the 0/1 Knapsack Problem. The DP approach does not scale to a large number of lifecycle stages/subprocesses so a sub-optimal approach is needed. We use our DP formulation to derive a focused real time dynamic programming (FRTDP) implementation, a heuristic method with optimality guarantees for solving our problem. We empirically evaluate (through simulation) the performance of our FRTDP implementation relative to both the DP implementation (for tractable instances) and to several alternative heuristics for intractable instances. Finally, we make the case that our work is usefully applicable to problems outside the domain of online advertising.

research report

Experimental Studies for Traffic Incident Management

Abstract

39 subjects each controlled a simulated vehicle through a simple road network: one freeway, one alternate route with two traffic lights. All subjects traveled simultaneously (share the road) and in the same direction to their destination. Each participants started with $14.00 endowment that decreases at $0.15 per second until they reached their destination. Each subject began on the freeway, and were given one opportunity each round to switch to the alternate route. The simulation has a Changeable Message Sign (CMS) within 8 seconds before alternate route off-ramp is reached. The CMS varied based on the each scenario being tested. The sessions presented the subjects with information that used publicly or privately visible vehicle identifiers to target the diversion recommendation at specific individuals. Another session presented standard Caltrans CMS information, and one of the sessions presented a dynamically updated desired diversion rate. Detailed statistical analyses of all treatments were completed, including the estimation of models describing the learning processes and behavioral changes of subjects in response to CMS content and the outcomes of previous route choices.

Phd Dissertation

Modified Cell Transmission Model for Bounded Acceleration

Abstract

Modeling capacity is an integral component towards multiple traffic engineering objectives such as design and evaluation of control strategies. Traffic dynamics at bottlenecks, both on freeways and on arterial networks, influenced by bounded acceleration and lane-changing, affect the capacity in intriguing ways. This research attempts to capture these impacts of the bounded acceleration behavior and its interplay with lane-changing, by constructing a modeling framework that accurately models traffic dynamics at bottlenecks.Towards this goal, first a modified Cell Transmission Model (CTM) is proposed, by substituting the traditionally constant demand function with a linearly decreasing function for congested traffic. The jam-density discharge flow-rate is introduced as an additional parameter to characterize the macroscopic bounded acceleration effects. Analytically the new model is shown to reproduce observed features in the discharge flow-rate and headway at signalized intersections. Calibration with observations from existing studies, as well as new observations, further suggests that the model can reasonably capture all traffic queue discharge features.The demand function is further modified by integrating macroscopic lane-changing effects on capacity. The Lane Changing Bounded Acceleration CTM (LCBA-CTM) thus developed, is shown to realistically model the capacity drop phenomenon at active freeway lane-drop bottlenecks in stationary states. The capacity drop magnitude is determined by macroscopic bounded acceleration and lane-changing characteristics. Constant loading problems are analytically solved to reveal the onset and recession processes of congestion.An addition to the framework connects microscopic acceleration profiles of vehicles to modified demand functions. This completes the framework presented by offering a mechanism to start from any acceleration model. Finally, two applications of the modified CTM are presented illustrating the use of the framework: a) to model impacts of improved vehicle acceleration on traffic dynamics at intersections; and b) to create Macroscopic Fundamental Diagrams (MFDs) for arterial networks and compare their accuracy with traditional CTM methods.This dissertation offers a systematic approach to incorporating bounded acceleration and lane-changing into the CTM demand functions. Such an approach is shown to capture important static and dynamic features at critical bottlenecks, including lost time and queue discharge features at signalized intersections, as well as capacity drop magnitude and the onset of capacity drop at active freeway bottlenecks. The consistency between the modified demand function and microscopic bounded acceleration models is also established.

research report

Infill Dynamics in Rail Transit Corridors: Challenges and Prospects for Integrating Transportation and Land Use Planning

Abstract

Although local and regional planning entities have attempted to direct growth into transit corridors to achieve the sustainability goals of California Senate Bill 375 (SB 375), little is known about the complexity of near-transit infill dynamics. This project aims to enhance the authors understanding of the relationship between transit investment and urban land use change through a systematic investigation of parcel-level land use in Southern California with a focus on the first phase of the Gold Line, opened in 2003. The authors multinomial logistic regression results indicate that vacant parcels within the vicinity of new transit stations are more likely to be developed not only for residential but also for other urban purposes, than those with limited transit accessibility. Although relatively small in terms of magnitude, the presence of long-term (or indirect) effects is also detected, suggesting that continuing investment in a transit system can benefit both new and existing station areas by promoting the utility of the overall public transit service. Transit stations with low ridership, however, tend to generate smaller land use impacts, indicating the importance of the vitality of transit service. Transit investment’s impacts on industrial site reuse also appears to be less evident, while transit investment seems to function as a facilitator of the site redevelopment for multi-family housing and urban open space.