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Transportation Network Modeling and Planning

Research

Anomalous Diffusion and the Structure of Human Transportation Networks

Researcher(s): Dirk Brockmann
Year: 2008

The dispersal of individuals of a species is the key driving force of various spatiotemporal phenomena which occur on geographical scales. It can synchronise populations of interacting species, stabilise them, and diversify gene pools [1–3]. The geographic spread of human infectious diseases such as influenza, measles and the recent severe acute respiratory syndrome (SARS) is essentially promoted by human travel which occurs on many length scales and is sustained by a variety of means of transportation [4–8]. In the light of increasing international trade, intensified human traffic, and an imminent influenza A pandemic the knowledge of dynamical and statistical properties of human dispersal is of fundamental importance and acute [7,9,10]. A quantitative statistical theory for human travel and concomitant reliable forecasts would substantially improve and extend existing prevention strategies. Despite its crucial role, a quantitative assessment of human dispersal remains elusive and the opinion that humans disperse diffusively still prevails in many models [11]. In this chapter I will report on a recently developed technique which permits a solid and quantitative assessment of human dispersal on geographical scales [12]. The key idea is to infer the statistical properties of human travel by analysing the geographic circulation of individual bank notes for which comprehensive datasets are collected at the online bill-tracking website www.wheresgeorge.com. The analysis shows that the distribution of travelling distances decays as a power law, indicating that the movement of bank notes is reminiscent of superdiffusive, scale free random walks known as L`evy flights [13]. Secondly, the probability of remaining in a small, spatially confined region for a time T is dominated by heavy tails which attenuate superdiffusive dispersal. I will show that the dispersal of bank notes can be described on many spatiotemporal scales by a two parameter continuous time random walk (CTRW) model to a surprising accuracy. To this end, I will provide a brief introduction to continuous time random walk theory [14] and will show that human dispersal is an ambivalent, effectively superdiffusive process.

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Crowdsourcing Service-level Network Event Monitoring

Researcher(s): David R. Choffnes, Fabián E. Bustamante, Zihui Ge
Year: 2010

The user experience for networked applications is becoming a key benchmark for customers and network providers. Perceived user experience is largely determined by the frequency, duration and severity of network events that impact a service. While today’s networks implement sophisticated infrastructure that issues alarms for most failures, there remains a class of silent outages (e.g., caused by configuration errors) that are not detected. Further, existing alarms provide little information to help operators understand the impact of network events on services. Attempts to address this through infrastructure that monitors end-to-end performance for customers have been hampered by the cost of deployment and by the volume of data generated by these solutions. We present an alternative approach that pushes monitoring to applications on end systems and uses their collective view to detect network events and their impact on services - an approach we call Crowdsourcing Event Monitoring (CEM). This paper presents a general framework for CEM systems and demonstrates its effectiveness for a P2P application using a large dataset gathered from BitTorrent users and confirmed network events from two ISPs. We discuss how we designed and deployed a prototype CEM implementation as an extension to BitTorrent. This system performs online service-level network event detection through passive monitoring and correlation of performance in end-users’ applications.

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Field Test of a Method for Finding Consistent Route Flows and Multiple-Class Link Flows in Road Traffic Assignments

Researcher(s): David Boyce,
Yu (Marco) Nie, Hillel Bar-Gera, Yang Liu, and Yucong Hu
Year: 2010

Road traffic assignment, or forecasting route and link flows corresponding to fixed matrices of origin-destination (OD) flows by vehicle class on a road network for a given time period, is commonly applied by transportation planning practitioners. The standard user-equilibrium traffic assignment method uniquely determines the total flow on each network link, subject to convergence errors. Multiple-class link flows and route flows, however, are indeterminate. To ensure that route and multiple-class link flows are uniquely determined, or consistent, an additional assumption is required. One option is that proportions of flow over alternative route segments with equal costs are the same for all drivers, regardless of origin or destination. Analyses based on the assigned link and route flows by vehicle class, such as select link, select zone and emissions analyses, are often performed without considering this issue. Although such analyses have become important in practice, no commercial software system currently considers the indeterminacy of these flows.

Traffic Assignment by Paired Alternative Segments (TAPAS) is a new algorithm offering the first practical way to address this issue. In this project six practitioners analyzed how route flows and/or multiple-class link flows generated by TAPAS compared with those found by the commercial software systems. A specialized tool VPAS was developed to compare the outputs of TAPAS and the practitioner software. The project team also undertook its own case study of the Chicago region with tools offered by four commercial software systems, which may be classified into two groups: link-based and quick-precision. Link-based tools applied in the project were CUBE, EMME, and TransCAD; quick precision tools applied were VISUM’s route-based method and TransCAD’s origin user-equilibrium (OUE) method. Findings of these applications may be summarized as follows:

  1. Select link results for link-based tools were approximately similar to those found by TAPAS; differences in flows through a selected link by OD pair were relatively small. However, small flows were observed in link-based solutions on non-equilibrium routes not found in the more precise TAPAS solutions. As a result, the number of OD pairs using a select link was often much larger for link-based tools than for TAPAS. Analyses of flows on pairs of equal-cost segments showed that link-based solutions tended to satisfy approximately the proportionality condition. Slow convergence, however, is a costly limitation of link-based tools. Even so, the findings suggest that link-based tools do provide approximately proportional solutions, which was not realized before this project.
  2. Select link results for quick-precision tools were very different from those produced by TAPAS. In particular, where TAPAS predicted positive flows, quick-precision tools often gave zero flow from an OD pair through a selected link. Analyses of flows on pairs of equal-cost segments showed that quick-precision tools produced solutions that violate the proportionality condition. In two-class assignments for pairs of alternative segments, the proportions of flow found by quick-precision solutions were also different by class.

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Hub-and-Spoke Network Alliances and Mergers: Price-Location Competition in the Airline Industry

Researcher(s): Nicole Adler, Karen Smilowitz
Year: 2007

This paper presents a framework to analyze global alliances and mergers in the airline industry under competition. The framework can help airlines identify partners and network structures, and help governments predict changes in social welfare before accepting or rejecting proposed mergers or alliances. The research combines profit-maximizing objectives to cost-based network design formulations within a game theoretic framework. The resulting analysis enables merging airlines to choose appropriate international hubs for their integrated network based on their own and their competitors’ costs and revenues in the form of best response functions. The results of an illustrative example suggest that some mergers may be more successful than others and optimal international gateway choices change according to the number of competitors remaining in the market. Furthermore, although the pressure on airlines would suggest a strong preference for mergers or alliances, perhaps surprisingly, the solution outcomes whereby all airlines merge or ally are not equilibria in the overall game.

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Improving Our Understanding of How Pricing and Congestion Affect Travel Demand

Researcher(s): Hani Mahmassani
Year: 2010

Dr. Mahmassani serves as co-PI on this study, awarded by the National Academy of Science to PB Americas, Inc. (with Northwestern University Transportation Center). The work plan can be conceptualized in three interconnected levels of behavioral rigor and practical application, with varying levels of sophistication:

Level 1 – Behavioral Foundations. The first level corresponds to behavioral models intended for a deep understanding and quantitative exploration of travel behavior. These models seek to address the full range of possible short and long‐term responses, but also may focus on select choice dimensions (for example, route and departure time choices, or usual workplace location choice).

Level 2 – Advanced Operational. The second level relates to relatively advanced, yet operational, Activity‐Based (AB) models, integrated with state of the art DTA (Dynamic Traffic Assignment) models. These models allows for the incorporation of a wide range of possible short‐ and long‐term responses that are embedded in the choice hierarchy.   The integrity of operational models requires that each and every choice dimension should be allocated a proper “slot” in the hierarchy, with upward and downward linkages to related choices.  Operational/computing time requirements often limit the total number of choice dimensions and alternatives, but this restriction is lessening with time.

Level 3 – Opportunities for Prevailing Practice. The third level relates to existing model systems used by most of MPOs and state DOTs, in the form of aggregate trip-based models (frequently referred to as 4-step models). Though rather restrictive in design, such models offer opportunities for meaningful and immediate contributions to the state of travel demand modeling practice. A serious restriction of 4‐step models is that these rely on static assignment procedures. Static assignments generate only crude average travel time and cost variables, and reliability can be incorporated only through certain proxies.

The SHRP 2 C04 project has completed an inventory of available datasets to support the research, and demonstrated an integrated application of user response models with a simulation-based DTA platform for the New York region Best Practice Model network.

Incorporating Reliability Performance Measures in Operations and Planning Modeling Tools

Researcher(s): Hani Mahmassani
Year: 2009

Dr. Mahmassani is one of three principal investigators on the team led by Delcan, Inc. to undertake this project.  Northwestern’s role focuses on the theoretical and methodological underpinnings of integrated supply-demand models that incorporate reliability.  The objectives are to advance the state of the art in planning and operations models to produce measures of reliability performance of proposed system changes, and determine how travel demand forecasting models can use reliability measures to produce more realistic estimates of travel patterns.  Project L04 draws on the quantitative measures of reliability as well as the impacts of reliability on route choice, time-of-day choice, and mode choice substantiated in “Improving Our Understanding of How Highway Congestion and Pricing Affect Travel Demand, SHRP2 C04”.

This project is developing approaches and tools to incorporate reliability as an input as well a key output in traffic models used for both operations and planning applications.  A unifying framework for reliability analysis is proposed, applicable in conjunction with any particle-based micro- or meso- simulation model that produces trajectories.  Vehicle trajectories are introduced and discussed as a central building block in this framework. The methodology is demonstrated using a simulation-based DTA platform.

In addition, to capture travel time variability introduced by random events, a repeatable framework is developed for modeling and evaluating incidents and events. A key variability-inducing phenomenon is traffic flow breakdown, which is modeled as an inherently stochastic phenomenon with structural dependence on state variables of the system.   Reliability-improving measures highlighted in the report include information supply and dynamic pricing, whose effectiveness increases considerably when applied in real-time on the basis of predicted conditions.

Finally, possible applications of travel time reliability in operations-oriented models are presented.

Incorporating Weather Impacts in Traffic Estimation and Prediction Systems

Researcher(s): Hani Mahmassani
Year: 2009

Dr. Mahmassani served as PI for this study conducted for FHWA under a subcontract to SAIC, Inc. The objectives of the project are to develop weather-sensitive traffic prediction and estimation models and incorporate them in existing traffic estimation and prediction systems. This includes enhancement of the capabilities in mesoscopic DTA tools to model traffic behavior under inclement weather, and capture user responses to inclement weather with and without the presence of advisory and control strategies.

As a result of this project, The DYNASMART TrEPS can now capture the effects of adverse weather on traffic patterns through both supply and demand side modifications to the model. New weather‐related features in DYNASMART include:

Weather Scenario Specification: DYNASMART allows users to specify various weather scenarios for the study network. It can be represented as either the network-wide weather condition or the link‐specific weather condition.

Weather Adjustment Factor:  Users can define the effect of weather on supply‐side traffic parameters such as free flow speed and capacity based on three weather condition parameters: visibility (mile), rain precipitation intensity (inch/hr) and snow precipitation intensity (inch/hr) by means of Weather Adjustment Factors (WAF). DYNASMART applies user‐specified WAF to 18 supply‐side traffic properties for links within the impacted region to simulate traffic conditions under the weather condition. WAF can be obtained based on calibrated weather‐traffic flow relation.

Modeling Traffic Advisory and Control via Variable Message Signs (VMS): DYNASMART provides three weather‐related VMS operation functionalities: (1) Speed Reduction Warning – via a VMS warning sign indicating low visibility (e.g., fog) or slippery road (e.g. rain and snow), speed reduction behavior under adverse weather can be simulated; (2) Optional Detour – VMS suggests that travelers re-evaluate their current route based on the generalized cost that includes travel penalties of the added delays caused by adverse weather; and (3) Variable Speed Limit (VSL) – in DYNASMART, vehicle speed can be regulated through the speed limits posted on VMS in correspondence with prevailing weather conditions.

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Methodology for Transportation System Redundancy Analysis in the Greater Baltimore Region

Researcher(s): Hani Mahmassani
Year: 2007

Dr. Mahmassani served as PI of this study, funded by the Baltimore Metropolitan Council. This study developed a regional dynamic network model for simulation-assignment applications to examine the ability of the transportation network and services to withstand shocks and disruptions resulting from natural or man-made hazards and events, ascertain the extent to which the system would be able to meet the mobility needs of the Greater Baltimore Region residents and businesses, and develop contingency measures and strategies to cope with the resulting travel demand patterns under constrained supply conditions. The project provides an example of how to build a large scale simulation platform given existing planning network model.

Network Design for Code Sharing

Researcher(s): Diego Klabjan
Year: 2010

An airline from an alliance faces the daunting task of code sharing its flights. The challenge mainly lies in the sheer size of the itineraries that can be sold on the entire network of all alliance partners. We developed a network design approach based on discrete choice modeling of passengers' utilities. The solution recommends flights to code share. In comparison to existing designs, our solution attains up to 2% improved profit, which was evaluated by a commercial profitability model.

Network Positioning from the Edge: An Empirical Study of the Effectiveness of Network Positioning in P2P Systems

Researcher(s): David R. Choffnes, Mario A. Sanchez, Fabian E. Bustamante
Year: 2010

Network positioning systems provide an important service to large-scale P2P systems, potentially enabling clients to achieve higher performance, reduce cross-ISP traffic and improve the robustness of the system to failures. Because traces representative of this environment are generally unavailable, and there is no platform suited for experimentation at the appropriate scale, network positioning systems have been commonly implemented and evaluated in simulation and on research testbeds. The performance of network positioning remains an open question for large deployments at the edges of the network.

This paper evaluates how four key classes of network positioning systems fare when deployed at scale and measured in P2P systems where they are used. Using 2 billion network measurements gathered from more than 43,000 IP addresses probing over 8 million other IPs worldwide, we show that network positioning exhibits noticeably worse performance than previously reported in studies conducted on research testbeds. To explain this result, we identify several key properties of this environment that call into question fundamental assumptions driving network positioning research.

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Optimal Short-Range Routing of Vessels in a Seaway

Researcher(s): I.S. Dolinskaya, M. Kotinis, M.G. Parsons, R.L. Smith, R. L
Year: 2009

An investigation of the optimal short-range routing of a vessel in a stationary random seaway is presented. The calculations are performed not only in head seas but also in oblique waves. The evaluation of the added drag is performed by computing the time average wave force acting on the vessel in the longitudinal direction. Subsequently, the added drag is superimposed on the steady drag experienced by the ship as it advances in calm water. In this manner, the fastest path between the origin point A and the destination point B can be evaluated, taking into account operational constraints. To obtain the fastest path between two points, the underlying structure and properties of the maximum mean attainable speed are analyzed. This detailed analysis allows us to demonstrate the fastest path for the problem without any operational constraints to be a straight line. Subsequently, the solution is reevaluated for scenarios where the original optimal path violates at least one of the operability criteria considered. For that case, a fastest path is found to be a path consisting of one waypoint, that is, a two line segment path. In addition to providing a closed-form fastest-path solution for the case of no operational constraints, a bound is provided for travel time error for more general speed functions in the case where a straight line path is followed.

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Providing Reliable Route Guidance Using Chicago Data

Researcher(s): Yu (Marco) Nie, Xing Wu
Year: 2009

New techniques offer the potential to improve travel reliability for motorists, freight carriers and parcel delivery firms. This project confronts challenges to the implementation of these techniques, and demonstrated their feasibility and benefits using real data from the Chicago metropolitan area, one of the largest transportation hubs in the US. Conceptually, the most reliable routes can be found by solving the Dynamic Shortest Path problem with On-Time arrival reliability (DSPOT). DSPOT has recently been formulated and solved using the dynamic programming technique. The proposed research addresses two important issues that currently preclude its implementation: 1) development of solution algorithms fast enough for on-line application, and 2) validation using real data. In this project, historical traffic data from the Gary-Chicago-Milwaukee 9GCM) traveler information system will be used to prepare dynamic probability mass functions of travel times, which are the key inputs to DSPOT. Then a prototype path search tool will be developed, which implements DSPOT based on GCM data. This toll will be made available to the public through the Artificial Intelligence Laboratory at the University of Illinois at Chicago. The ultimate goal of this project is to provide motorists and carrier with commercialized DSPOT products that will allow them to make tradeoffs between reliability and other costs and constraints. With the benefits and market value demonstrated through this project and further implementation stages, we believe that the related industries will be interested in adding DSPOT to their product offerings. These firms include but are not limited to the manufacturers of in-vehicle navigation systems, web companies that provide internet-based driving directions and software vendors that produce logistics for freight carriers.

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REORIENT: Implementing Change in the European Railway Area

Researcher(s): Hani Mahmassani
Year: 2006

Dr. Mahmassani led, with Dr. Elise Miller-Hooks of the University of Maryland, a $1.06Million effort as part of a $7.2M multi-national multi-partner consortium project. The REORIENT project assessed the process of transforming the European railways from nationally fragmented into internationally integrated rail operating systems as a consequence of the EC interoperability legislation. By so doing, it supported the EU policy of balancing modal split between road and rail freight transport.

The team led by Dr. Mahmassani, jointly with Dr. E. Miller-Hooks at the University of Maryland, had lead responsibility for developing and validating strategies for identifying and removing technological, cultural, social and managerial barriers facing the implementation of competitive intermodal rail freight services across national boundaries. As such, the team was in charge of developing the key recommendations that arose from the entire research effort.  The recommendations are necessarily based on a comprehensive understanding of the operational, institutional and political context surrounding freight service in Europe.  Sophisticated quantitative and qualitative analyses of the operational and social aspects of the freight system likewise compose another essential basis for essential basis for any recommendations. 

Dr. Mahmassani’s team also served as coordinator of all network modeling activities needed to support the project, and led the process of building the corresponding network models and associated freight flow processes through the rail network links and intermodal transfer points, as well as the demand models for short and long term freight flow in the study area.  This resulted in development of a novel network modeling platform to support evaluation of different strategies and measures intended to improve the prospects of rail freight in the corridor, as well as improvement of capacity and service levels. As such, the network modeling effort plays a critical role in supporting the business case development. In addition, the project led to development of novel ways of calibrating and estimating demand models combining various data sources at both macroscopic and microscopic levels. These activities cut across several other work packages led by other entities. The project also involves coming up with a collaborative decision-making framework by which different entities in different countries, including private service providers, can jointly manage complex systems in real time.

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Relationship between Proximity to Transit and Ridership for Journey-to-Work Trips in Chicago

Researcher(s): Lindsey Marshall, Joseph L. Schofer, Pablo Durango-Cohen, Kimberly A. Gray
Year: 2010

This circular summarizes discussions at a peer exchange of state department of transportation officials and other professionals that focused on data and information uses, management strategies, needs, and gaps in their organizations. The peer exchange examined the role of data and information in transportation decision making; identified information resources, gaps, and opportunities; and explored data, access, and analysis improvements for information resource programs. In addition, participants discusses possible strategies that the transportation community might use to implement such improvements.

Solving the Dynamic User Optimal Assignment Problem Considering Queue Spillback

Researcher(s): Yu Nie, H.M. Zhang
Year: 2007

This paper studies the dynamic user optimal (DUO) traffic assignment problem considering simultaneous route and departure time choice. The DUO problem is formulated as a discrete variational inequality (DVI), with an embedded LWR-consistent mesoscopic dynamic network loading (DNL) model to encapsulate traffic dynamics. The presented DNL model is capable of capturing realistic traffic phenomena such a queue spillback. Various VI solution algorithms, particularly those based on feasible directions and a line search, are applied to solve the formulated DUO problem. Two examples are constructed to check equilibrium solutions obtained from numerical algorithms, to compare the performance of the algorithms, and to study the impacts of traffic interacts across multiple links on equilibrium solutions.

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Stability of User-equilibrium Route Flow Solutions for the Traffic Assignment Problem

Researcher(s): Shu Lu, Yu Nie
Year: 2010

This paper studies stability of user-equilibrium (UE) route flow solutions with respect to inputs to a traffic assignment problem, namely the travel demand and parameters in the link cost function. It shows, under certain continuity and strict monotonicity assumptions on the link cost function, that the UE link flow is a continuous function of the inputs, that the set of UE route flows is a continuous multifunction of the inputs, and that the UE route flow selected to maximize an objective function with certain properties is a continuous function of the inputs. The maximum entropy UE route flow is an example of the last. On the other hand, a UE route flow arbitrarily generated in a standard traffic assignment procedure may not bear such continuity property, as demonstrated by an example in this paper.

Toward More Reliable Mobility: Improved Decision Support Tools for Transportation Systems

Researcher(s): Yu Nie
Year: 2010

The overarching goal of the project is to enhance travel reliability of highway users by providing them with reliable route guidance produced from newly developed routing algorithms that are validated and implemented with real traffic data. Phase I of the project (funded by CCITT in 2008) focused on demonstrating the value of reliable route guidance through the development of dissemination of Chicago Testbed for Reliable Routing (CTR). Phase II aims at bringing the implementation of reliable-routing technology to the next stage through initial deployment of CTR.

The first objective in Phase II is to create a travel reliability inventory (TRI) of Northeastern Illinois using CTR, by collaborating with public agencies such as the Illinois Department of Transportation (IDOT), Chicago Transit Authority (CTA) and Chicago Traffic Management Authority (CTMA). TRI documents travel reliability indices (e.g., 95 percentile route travel times) between heavily-traveled origins-destination pairs in the region, which are of interest not only to individual travel decision-making, but also regional transportation planning and traffic operations/management. The second objective is to perform and initial market test in order to understand users’ need for and response to reliability information and reliable route guidance.

To these ends, the following research activities are proposed to further develop CTR:

  • Implement and test latest reliable routing algorithms that are suitable for large-scale applications.
  • Develop a web-based version of CTR and host the service at Northwestern University’s Translab Website. A web survey will be designed and posted along with CTR in order to collect user feedback.
  • Explore the possibility of achieving a greater degree of data coverage of the study area. Specifically, archived automatic vehicle location (AVL) data of CTA’s bus fleet is considered an important data source to supplement GCM data and will receive a focal study.

Using Simulation to Test Traffic Incident Management Strategies: The Benefits of Preplanning

Researcher(s): John J. Wirtz, Joseph L. Schofer, David F. Schulz
Year: 2005

This study tested a dynamic traffic assignment model as a tool for pre-planning strategies for managing major freeway incidents. Incidents of various scales and durations were modeled in the northern Chicago, Illinois, highway network, and the impacts of incidents and response actions were measured in lane mile hours of highway links at Level of Service F and spread of congestion to alternate routes around the incident. It was found that the best response action to a given incident scenario was not necessarily intuitive and that implementing the wrong response could worsen congestion on the directly impacted freeway and its surrounding highway network. The simulation model showed that a full closure of the freeway caused congestion to spread to alternate parallel routes around the simulated incident. An event of this scale constitutes a major disruption that may warrant handing off traffic control authority from first responders to a corridor or regional traffic management center. Major arterials accessible from the impacted freeway sometimes need increased capacity to provide access to less congested parallel alternate routes during incidents. The simulation model showed that congestion increases with delayed response, underscoring the benefits of preplanning to speed the implementation of effective incident response actions. Regression analysis using data generated by the simulation demonstrates that incident scale and duration are statistically significant predictors of lane mile hours of congestion in the zone near the incident and on the expressway.

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