published journal article

Network-based real option models

Publication Date

April 30, 2011

Associated Project

Large Scale Real Options Models for Network Investment Planning & Operational Risk Hedging

Author(s)

Joseph Chow, Amelia Regan

Areas of Expertise

Freight, Logistics, & Supply Chain

View published journal article

Abstract

Building on earlier work to incorporate real option methodologies into network modeling, two models are proposed. The first is the network option design problem, which maximizes the expanded net present value of a network investment as a function of network design variables with the option to defer the committed design investment. The problem is shown to be a generalized version of the network design problem and the multi-period network design problem. A heuristic based on radial basis functions is used to solve the problem for continuous link expansion with congestion effects. The second model is a link investment deferral option set, which decomposes the network investment deferral option into individual, interacting link or project investments. This model is a project selection problem under uncertainty, where each link or project can be deferred such that the expanded net present value is maximized. The option is defined in such a way that a lower bound can be solved using an exact method based on multi-option least squares Monte Carlo simulation. Numerical tests are conducted with the classical Sioux Falls network and compared to earlier published results.

Related Publications

Phd Dissertation | February 03, 2025

Flexible Management of Transportation Networks under Uncertainty

working paper

Incorporating Vehicular Emissions into an Efficient Mesoscopic Traffic Model: An Application to the Alameda Corridor, CA

Publication Date

January 31, 2011

Author(s)

Qi-Jian Gan, Jielin Sun, Wenlong Jin, Jean-Daniel Saphores

Areas of Expertise

Travel Behavior, Land Use, & the Built Environment Zero-Emission Vehicles & Low-Carbon Fuels

View working paper

Abstract

We couple EMFAC with a dynamic mesoscopic traffic model to create an efficient tool for generating information about traffic dynamics and emissions of various pollutants (CO2, PM10, NOX, and TOG) on large scale networks. Our traffic flow model is the multi-commodity discrete kinematic wave (MCDKW) model, which is rooted in the cell transmission model but allows variable cell sizes for more efficient computations. This approach allows us to estimate traffic emissions and characteristics with a precision similar to microscopic simulation but much faster. To assess the performance of this tool, we analyze traffic and emissions on a large freeway network located between the ports of Los Angeles/Long Beach and downtown Los Angeles. Comparisons of our mesoscopic simulation results with microscopic simulations generated by TransModeler under both congested and free flow conditions show that hourly emission estimates of our mesoscopic model are within 4 to 15 percent of microscopic results with a computation time divided by a factor of 6 or more. Our approach provides policymakers with a tool more efficient than microsimulation for analyzing the effectiveness of regional policies designed to reduce air pollution from motor vehicles.

working paper

Estimating Emissions Using an Integrated Traffic Model

Publication Date

January 31, 2011

Author(s)

Qi-Jian Gan, Jielin Sun, Wenlong Jin, Jean-Daniel Saphores

Areas of Expertise

Travel Behavior, Land Use, & the Built Environment Zero-Emission Vehicles & Low-Carbon Fuels

View working paper

Abstract

Regulators concerned with traffic related emissions on large networks should consider allowing modelers to use mesoscopic traffic models (such as the MCDKW model) that can adequately represent congestion along with appropriate emissions models. This would simplify regulatory analyses, reduce errors, and cut costs.

published journal article

High-Coverage Point-to-Point Transit: Study of Path-Based Vehicle Routing Through Multiple Hubs

Publication Date

December 31, 2010

Associated Project

High Coverage Point to Point Transit: A Public-Private Incrementally Implementable Mass Transit Strategy for Sustainability With Real-time Shared-ride Vehicles.

Author(s)

Jae Young Jung, R. (Jay) Jayakrishnan

Areas of Expertise

Public Transit, Shared Mobility, & Active Transportation

View published journal article

Abstract

This study focuses on the optimization and simulation modeling associated with the design of alternative transportation, the high-coverage point-to-point transit (HCPPT), which involves a sufficient number of deployed small vehicles with advanced-information supply schemes. This paper identifies the inefficiency of the existing heuristic rules for vehicle routing and proposes a new optimization approach for an HCPPT solution. A path-based model for routing through multiple hubs as opposed to a single pair of hubs is formulated to improve HCPPT operational schemes. This study also develops a simulation framework for the application of the proposed algorithm. To illustrate the system and computational performances of the proposed model, simulations are conducted with different sets of scenarios and model parameters. The path-based model shows reasonable performance over the various demand patterns in level of service and ride time index. It is also shown that, with the use of constraint-driven schemes and model parameters, the scale of the problem is reduced. The computational times are shown to be quite small, and demonstrate the viability in real-time operations.

Related Publications

Phd Dissertation | February 03, 2025

Shared-ride Passenger Transportation Systems with Real-time Routing

Phd Dissertation

Broadcasting in Vehicular Ad Hoc Networks

Publication Date

November 29, 2010

Author(s)

Rex Chen

Areas of Expertise

Intelligent Transportation Systems, Emerging Technologies, & Big Data

View Phd Dissertation

Abstract

Traffic congestion and accidents continue to take a toll on our society with congestion causing billions of dollars in economic costs and millions of traffic accidents annually worldwide. For many years now, transportation planners have been pursuing an aggressive agenda to increase road safety through Intelligent Transportation System initiatives. Vehicular Ad Hoc Network (VANET) based information systems have considerable promise for improving traffic safety, reducing congestion and increasing environmental efficiency of transportation systems. To achieve the future road safety vision, time-sensitive, safety-critical applications in vehicular communication networks are necessary. However, there are numerous technical hurdles for deploying VANET on the road network and its full potential will not be realized until the issues related to communication reliability, delay and security are solved. VANET is a specific type of mobile ad hoc network (MANET) with unique characteristics that are different from a general MANET. These attributes include the traffic conditions (network density), mobility model (vehicle movements) and the network topology (road layout) imposed by the underlying transportation system. When disseminating data in VANET the communication system is faced with the scalability problem in dense networks and the connectivity issue in sparse ones. In this dissertation, we study broadcasting for VANET that are applicable to traffic safety applications. We investigate ways to improve reliability and reduce delay under numerous traffic conditions (free flow and congested flow traffic scenarios). Further, we incorporate vehicular traffic information to increase the communication efficiency in dynamic vehicular networks while mitigating the broadcast storm problem. We believe that the contributions in this dissertation will be of interest for both the computer networking and transportation research communities.

Phd Dissertation

Epitaxis: A System for Deductive and Constructive Program Queries

Publication Date

December 30, 2010

Author(s)

James Benvenuto

Areas of Expertise

Other

View Phd Dissertation

Abstract

Modern computer hardware (multi-core, multi gigahertz processors with gigabytes of RAM and terabytes of disk) along with IDEs allows programmers to build computer programs which are bigger and more complex than they can understand or keep in their working memories. Additionally, the problems these programs are designed to model are ever more complicated. Consequently, programs are full of inconsistencies, mistakes, and incompleteness’s. These problems are difficult to detect, difficult to locate, and difficult to correct. Often a change is made by a programmer to fix a problem for which understanding all the repercussions of the change is difficult. Consequently, further bugs are introduced into the code base. Because of the pervasiveness of software in society and the potential severity of the consequences of bugs, software developers need ever better tools to help them understand, navigate, and follow the consequences of their development and maintenance activities. This dissertation presents a novel framework based on tree/graph searching and parsing, deductive retrieval, dynamic analysis, symbolic execution, aspect oriented programming, and an open interpreter to allow a software developer to navigate, locate features, find bugs, and abstract information in software. The system is designed to have a fast modify-test cycle such that the programmer can search and test the software as it is being edited without time consuming recompilation, reinstrumenting, or database repopulating each time an edit is made to the code base. The system is language independent, requiring only files to specify the language grammar, control flow graph transformation, and execution semantics. In addition, because of the flexibility and programmability of the system it is an excellent environment to perform further research on program analysis techniques such as dynamic analysis, symbolic execution and abstract interpretation. A prototype system has been built along with data files for the C programming language which demonstrates the feasibility of the system and its ability to scale to “modern-sized” programs.

research report

Transportation Management Center (TMC) Performance Measurement System

Publication Date

September 29, 2010

Associated Project

A Measurement-Based System for TMC Performance Evaluation

Author(s)

Will Recker, Craig Rindt

Areas of Expertise

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

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Abstract

This project developed a web-based application that addresses the problem of identifying the value of the TMC in managing disruptions to the transportation system by quantifying the delay savings that can be attributed directly to TMC actions. Using event data from TMC activity logs and traffic state data from the PeMS database, the system identifies the time-space impact of events in the activity database using a mathematical-programming formulation to match evidence of disruption to computed time-space bounds. Given this boundary, the actual delay associated with the impacted region is calculated. To compute the savings attributable to the TMC, the activity logs are used to identify when the direct disruption by the event is removed (e.g., when an accident is cleared) and models the increased delay that would occur if this clearance was delayed. Given these calculations, the system allows TMC managers to evaluate the performance of various bundles of TMC technologies and operational policies by mapping their effects onto events in the system that can be measured using existing surveillance systems and daily activity logs. The system is deployed atop the CTMLabs service-oriented architecture and is available as a application on the CTMLabs website for use by authenticated users.

research report

Online Freeway Corridor Deployment of Anonymous Vehicle Tracking for Real Time Traffic Performance

Publication Date

September 27, 2010

Associated Project

Online Freeway Corridor Deployment of Anonymous Vehicle Tracking for Real-Time Traffic Performance Measurement

Author(s)

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

Areas of Expertise

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

View research report

Abstract

The need for advanced, accurate and comprehensive traffic performance measures in increasingly saturated traffic networks is stretching the effectiveness of existing conventional point-based loop detector traffic data. This study had two objectives. The first was the evaluation of two emerging technologies – Sensys Magnetometers and Blade Inductive Signature System – to assess their potential in providing advanced traffic performance measures using vehicle signature data. The second was the expansion and deployment of the Real-time Traffic Performance Measurement System (RTPMS) to provide section-based traffic performance measures under actual operating conditions. As a part of this deployment, a communications framework was implemented to provide real-time communications of signature feature data between field units and a central vehicle re-identification server. A new improved online interactive web-user interface was also developed to provide users with real-time as well as historical traffic performance measurements.

conference paper

An Empirical Study of Inter-Vehicle Communication Performance Using NS-2

Publication Date

July 31, 2010

Associated Project

Theoretical and Simulation Studies of Information Throughput and Communication Delay of Inter-Vehicle Communication Networks

Author(s)

Jae Young Jung, Rex Chen, Wenlong Jin, R. (Jay) Jayakrishnan, Amelia Regan

Areas of Expertise

Intelligent Transportation Systems, Emerging Technologies, & Big Data

View conference paper

Abstract

In recent years, there has been increasing interest in inter-vehicle communications (IVC) based on wireless networks to collect and distribute traffic information in various Intelligent Transportation Systems applications. In this paper, we study the performance of IVC under various traffic and communication conditions by means of simulation analysis. We consider impacts of shock waves, transportation network, traffic densities, transmission ranges, and multiple information sources. We used a state-of-the-art communication network simulator ns-2 to measure the probability of success (success rate) and message delivery ratio (MDR) for flooding-based IVC communication. For reasonable realism in the deployment scenario, we assume that only a partial set of vehicles on the road are equipped with communication devices, according to the market penetration rate. A Monte-Carlo simulation method is used, with repeated random sampling of IVC-equipped vehicles. The results indicate how these parameters can impact the performance of IVC communications. By comparing the flooding-based approach (theoretical and simulation) and simulation results using AODV (Ad Hoc On-Demand Distance Vector), we conclude the importance of traffic environment and network protocol in determining the MDR for IVC communication.

research report

The Personal Travel Assistant (PTA): Measuring the Dynamics of Human Travel Behavior

Publication Date

July 31, 2010

Associated Project

The Personal Travel Assistant (PTA): Measuring the Dynamics of Human Travel Behavior

Author(s)

Will Recker, James Marca, Craig Rindt, Rina Dechter

Areas of Expertise

Intelligent Transportation Systems, Emerging Technologies, & Big Data Travel Behavior, Land Use, & the Built Environment

View research report

Abstract

A simple, continuously collected GPS sequence was investigated to determine whether it can be used to accurately measure human behavior. Hybrid Dynamic Mixed Network (HDMN) modeling techniques were applied to learn behaviors given an extended GPS data stream. A key design decision behind the proposed architecture was to use an Enterprise Service Bus (ESB) to provide a communication infrastructure among various components of the application. Personal Travel Assistants running on mobile devices like cell phones could help travelers change their travel plans when routes are affected by crashes or natural disasters.