Research
Research In Progress
2008-2009 Projects
Effect of Friction on Rolling Tire-Surface Interaction
Research Information
Start Date: 2009/6/15
Status: Active
Total Dollars: $74,575
Source Organization: Purdue University, West Lafayette
Principal Investigator: Ilinca Stanciulescu, University of Illinois, Urbana-Champaign
Co-Principal Investigator: Imad Al-Qadi, University of Illinois, Urbana-Champaign
Summary of Research
The research will focus on the development of nonlinear finite element frictional contact models. The tire-road interfacial behavior will be investigated. Models for contact simulations with coefficient of friction dependent on the sliding velocity will be developed and implemented in a mortal contact formulation framework. These models will be used to accurately determine the contact tractions distribution on the road surface. As part of the research, parametric studies will be performed that will help us determine the ideal combination of mechanical and tribological properties of the tire and the pavement leading to shorter breaking distances and a safer driving environment.
Traffic Signal Coordination and Queue Management in Oversaturated Intersections
Research Information
Start Date: 2009/8/14
Status: Active
Total Dollars: $66,189
Source Organization: Purdue University, West Lafayette
Principal Investigator: Rahim Benekohal, University of Illinois, Urbana-Champaign
Summary of Research
Traffic signal coordination can improve intersection traffic operation and safety, however, traffic management in congested networks is much more complex and requires in-depth understanding of the traffic flow characteristics. The current knowledge about optimizing traffic flow in congested networks is very limited and most of it a simple expansion of the knowledge for undersaturated networks. The majority of traffic signal coordination methods use the concept of delay minimization. Delay minimization works well in undersaturated conditions where queue spillbacks do not back the adjacent lanes or nearby intersections; however, is not the most appropriate method because delay is not the best performance measure for oversaturated conditions. Queue minimization is more appropriate method for oversaturated conditions where queue spillbacks commonly occur. This study will develop a signal coordination methodology based on the concept of queue minimization in a network of oversaturated intersections. The study will use three search and optimization techniques: a) Dynamic Programming (DP), b) Genetic Algorithms (GA), and c) Evolutionary strategies (ES). In this study, we will compare GA results to the solutions from ADP and ES. The solutions from the three methods will also be compared to field or simulated data, when it is possible. This research would help to advance the basic understanding of congestion management in urban networks. It will provide a methodology for calculating signal coordination
Determining Queue and Congestion in Highway Work Zone Bottlenecks
Research Information
Start Date: 2009/8/14
Status: Active
Total Dollars: $69,566
Source Organization: Purdue University, West Lafayette
Principal Investigator: Rahim Benekohal, University of Illinois, Urbana-Champaign
Summary of Research
There is very little study in shockwave propagation in work zone bottlenecks. Traffic flow characteristics in work zones are different from normal highways. Often the traffic operates in stop-and-go condition and this creates multiple shockwaves that interact with each other. This study will investigate shockwave and queue formation in congested work zones (WZ) where traffic flow break down, and will validate the theory using field data. The theoretical aspect of this research is to look at the shockwave formation and propagation in work zone bottleneck. This research would help to advance the basic understanding of queue formation and dissipation in work zones as well as finding ways of managing the adverse effects it. The real-time application of the results work require integration of communication, computing, and vehicle sensing techniques into on-line queue management strategy. This study is a combination of advanced (exploratory) and applied research that addresses the issue of work zone congestion choke points. The findings from this research will help practicing engineers to design and operate the work zones in safer and more efficient ways. This research supports the theme of NEXTRANS by finding solutions that are innovative, relying on basic research and understanding of traffic flow principles, integrating technology in managing congestion in chokepoints, and improving the understanding of queue and congestion growth and dissipation in highway WZ.
Thermal Cracking Performance Prediction and Asset Management Integration
Research Information
Start Date: 2009/8/14
Status: Active
Total Dollars: $46,200
Source Organization: Purdue University, West Lafayette
Principal Investigator: William Buttlar, University of Illinois, Urbana-Champaign
Co-Principal Investigator: Glaucio Paulino, University of Illinois, Urbana-Champaign
Summary of Research
Low-temperature cracking of hot-mix asphalt (HMA) pavements continues to be a leading cause of premature pavement deterioration in cold regions. While recent modeling advances have led to new insights into cracking mechanisms, there remains the challenge of implementing these models into a standalone, practitioner-friendly program. Furthermore, the theme of the NEXTRANS Center is to develop integrated solutions to transportation problems by explicitly capturing the interactions between the vehicle, driver/traveler, and the infrastructure. Following the successful first phase of the National Pooled Fund Study on Low Temperature Cracking, a second phase will be initiated in mid-2007 and continue for two to three years. The proposed supplemental study will extend the scope of the existing pooled fund study to more explicitly capture the interactions between vehicles and the infrastructure (Pillar 2 of NexTrans). The main deliverable of this project would be a user-friendly, computationally efficient program which could be used to analyze and to design against thermal cracking in asphalt pavements. New tools to be included in the software under this project include: Implementation of tailored nonlinear cohesive zone fracture model; Integration of computational model with integrated climate model; Integration of model with probabilistic crack distribution model; Final model verification, and; Development of user-friendly interface (with inputs from participation DOT panel members form pooled fund study). Integration of new tool with IDOT asset management software will be performed in conjunction with Prof. Yanfeng Ouyang. Case studies will then be performed for IDOT and for the Pooled Fund Study using this comprehensive asset management tool.
Machine Vision Inspection of Railroad Track
Research Information
Start Date: 2009/8/14
Status: Active
Total Dollars: $37,800
Source Organization: Purdue University, West Lafayette
Principal Investigator: J. Riley Edwards, University of Illinois, Urbana-Champaign
Co-Principal Investigators: Christopher Barkan, University of Illinois, Urbana-Champaign
Narendra Ahuja, University of Illinois, Urbana-Champaign
Summary of Research
The objective of this research project is to develop new methods to increase the efficiency and effectiveness of railroad track inspection through the application of machine vision, and advanced visual sensing technology. This objective will be accomplished by recording images of railroad track from a moving vehicle using digital video and imaging technology then using advanced machine vision algorithms to detecting broken or defective infrastructure components. Trend analyses will be performed using the data acquired. The results will ultimately be able to be wirelessly communicated to the railroad infrastructure management centers and personnel to enable more effective and efficient repair and maintenance scheduling. Results from initial machine vision-based track inspection algorithms have proven the feasibility of automated recognition and inspection of certain track components through the capture and analysis of digital images. In addition to further refinement of the track component algorithms the work proposed here will include development of railroad infrastructure condition assessment protocols and algorithms for additional components of interest that have been identified by railroad industry infrastructure experts as promising candidates for machine vision inspection. This work, as described in the full NEXTRANS research proposal seeks to expand the breadth and depth of this research and provide further benefit to the railroads in terms of safe and efficient operation of their infrastructure.
A Multi-scale Approach For Near Surface Pavement Cracking and Failure Mechanisms
Research Information
Start Date: 2009/8/14
Status: Active
Total Dollars: $75,166
Source Organization: Purdue University, West Lafayette
Principal Investigator: C. Armando Duarte, University of Illinois, Urbana-Champaign
Co-Principal Investigator: Imad Al-Qadi, University of Illinois, Urbana-Champaign
Summary of Research
Major distress modes of flexible pavements initiate at or near the pavement surface, including longitudinal cracking, hot-mix asphalt (HMA) permanent deformation, and thermal cracking. High thermal gradients and non-uniform high tire-pavement contact stresses can trigger near-surface failure mechanisms. In addition to repeated thermal and tire loading, pavement material characteristics and structure capacity also have a significant effect. The objective of this study is to investigate near surface failure and cracking mechanisms by means of advanced recently emerged numerical techniques. The outcome of this study will be a multi-scale digital HMA pavement model that will allow distress predictions related to near surface failure and cracking mechanisms with simplified user inputs. The pavement model that will be developed in this study will enable improved understanding the near surface failure mechanisms with simplified user inputs. Integration of these models into the design procedure will help in developing long-lasting and cost effective flexible pavements.
Development of Carrier-Carrier Collaboration and Transfer Location Models for Less Than Truckload Freight Logistics
Research Information
Start Date: 2009/7/1
Status: Active
Total Dollars: $50,000
Source Organization: Purdue University, West Lafayette
Principal Investigator: Srinivas Peeta, Purdue University,West Lafayette
Summary of Research
With the upward trajectory in fuel prices due to the increased demand and lack of proportionally increasing supply, freight transportation systems (many of which already operate inefficiently) will either cease to exist or suffer further service level decline. This is especially true for the small- to medium-sized freight carrier firms that form the bulk of the less than truckload (LTL) industry. It motivates the need for innovative solutions. One potential approach is to enable carrier-to carrier collaboration in the LTL industry that can leverage the (utilization of) existing transportation infrastructure and advances in information and communication technologies (ICT). Thereby, the LTL carriers can employ a new generation of strategies that exploit synergies (e.g. sharing excess capacity) which form the basis for some sort of collaboration while competing. This study seeks to address the carrier-to carrier collaborative paradigm as an innovative sustainable transportation solution concept. It will focus on the small-to medium trucking firms in the LTL industry, where competition and operational inefficiencies can significantly affect the viability of the companies. The study aims to propose dynamic models of carrier-carrier collaboration and consequent models for the identification of efficient transfer locations. The transfer location problem has implications for collaborative intermodal freight logistics in terms of building or renewing intermodal terminals.
Development of a Mobile Probe-Based Traffic Data Fusion and Flow Management Platform for Innovative Public-Private Information-Based Partnerships
Research Information
Start Date: 2009/7/15
Status: Active
Total Dollars: $100,000
Source Organization: Purdue University, West Lafayette
Principal Investigator: Srinivas Peeta, Purdue University, West Lafayette
Co-Principal Investigator: Xuesong Zhou, University of Utah
Summary of Research
Most existing traffic information provision and control systems are deployed and maintained by public agencies, and are built on centralized management architectures. To maximize the value of emerging mobile probe data from private sector vendors, the proposed research aims to exploit innovative data collection, traffic management, and road pricing/crediting mechanisms that can encourage mutually beneficial information-sharing under successful public-private sector partnerships. Based on a unified data mining system that can synthesize different data sources to estimate traffic network states, this study will systemically quantify the value of information from different data sources and provide a decision support system to optimize sensor locations under different levels of data availability. Further, the study will utilize emerging mobile probe data to evaluate point sensor quality for state DOTs, identify major freeway and arterial bottlenecks, and assess travel time variability and reliability for major commuter routes. Finally, innovative Internet-connected GPS navigation-enabled traffic flow management mechanisms will be developed and evaluated to balance the network traffic load by fully integrating various traffic information provision and pricing/crediting strategies.
Transportation and Socioeconomic Impacts of Bypasses on Communities: An Integrated Synthesis of Spatial Econometric Methods and Agent-Based Simulation
Research Information
Start Date: 2009/1/12
Status: Active
Total Dollars: $50,065
Source Organization: Purdue University, West Lafayette
Principal Investigator: Jon Fricker, Purdue University, West Lafayette
Summary of Research
The construction of a bypass can have long-term and far-reaching effects. If planned properly, a bypass can constitute a "win-win" public-private partnership, benefiting the affected community, through travelers, and industry. The research should provide a suitable means of determining impacts of bypasses and finding mutually agreeable solutions to minimize adverse impacts of bypasses for all stakeholders involved. Combining the models with a GIS software package can be used to convey potential impacts to the public. A standard suite of bypass impacts estimation models can reduce the subjective element of the sometimes-controversial issue of bypasses.
The project will consist of two components: (1) Statistical analysis of socioeconomic data and (2) Modeling the landowner and owner-managed business decision-making process. A number of different statistical approaches, combining spatial econometrics, panel data, and multilevel regression, will be used to predict regional economic impacts. Agent-based simulation models will be developed to predict the individual decision-making process to capture what actions may be taken by landowners once the construction of a bypass is announced. The project will take an integrated approach in considering the following goals related to a bypass: (A) enhancing mobility and safety by diverting through trucks and other traffic (agency perspective) (B) maintaining or restoring the economic vitality of the affected community’s central business district (local perspective) and (C) minimizing transportation costs (private sector perceptive). The research will be multidisciplinary in nature, tying together transportation engineering, economics, statistics, entrepreneurship, consumer behavior, urban and regional planning, economic development, and public policy.
The findings of the research will help to promote partnerships between local community organizations and the private sector. Community officials can use the bypass as a selling point to attract and retain industry. Officials can establish dialogue with potential retailers who wish to locate along the bypass to ensure mobility and transportation efficiency is preserved while providing an opportunity for commerce. The construction of a bypass will provide the community with an opportunity to renew its downtown and infrastructure.
System Methods for Uncovering Economic, Technological, and Policy Enablers of an "On-demand air service" Regional Passenger Transportation Solution
Research Information
Start Date: 2009/3/1
Status: Active
Total Dollars: $50,000
Source Organization: Purdue University, West Lafayette
Principal Investigator: Daniel DeLaurentis, Purdue University, West Lafayette
Co-Principal Investigator: Srinivas Peeta, Purdue University, West Lafayette
Summary of Research
This project pursues an integrated, systems-oriented search for innovative solutions to regional passenger mobility, embodied in the idea of a commercial "On-demand air service", ODAS. Our hypothesis is that if ODAS can deliver levels of speed and flexibility in door-to-door transportation not available today via commercial airline service or other modes then it would in turn generate significant economic benefits in the Midwest for moderate investment. Research will be conducted to explore what are the multimodal resource (air and ground), transportation policy, and economic variables that are likely to enhance "doorstep-to-destination" mobility for citizens seeking personal and business trips.
Public Private Partnerships (PPP's) in Highway Reconstruction, Rehabilitation, and Operations
Research Information
Start Date: 2009/1/12
Status: Active
Total Dollars: $40,000
Source Organization: Purdue University, West Lafayette
Principal Investigator: Samuel Labi, Purdue University, West Lafayette
Co-Principal Investigator: Kumares Sinha, Purdue University, West Lafayette
Summary of Research
Traditionally, private sector participation in transportation project management has been limited to only the planning, design or construction phases of transportation asset management. Also, contracts for each phase have been awarded separately. Over the last decade, a relatively new project delivery approach, public-private partnerships (PPPs), is increasingly being adopted for project delivery not only to include the other phases in transportation asset management (operations and preservation) but also for a collection of phases in a single contract. PPPs are contractual agreements formed between a public agency and private sector entity, thus allowing for greater private sector participation in the delivery of transportation projects. Past research suggests that expanding the private sector role allows the public agencies to tap private sector technical, management and financial resources in new ways to achieve certain public agency objectives such as greater cost and schedule certainty, supplementing in-house staff, innovative technology applications, specialized expertise, or access to private capital. Also, the private partner can expand its business opportunities in return for assuming the new or expanded responsibilities and risks. Generally in project management, it is desired to allocate risks to the party that is the best equipped to manage them. As such, PPP contracts typically include incentives that reward private partners for mitigating risk factors. It has been suggested that agencies could benefit from a decision-support framework that can help identify that conditions that are appropriate for each alternative of project delivery, and the quest for such a framework has been stymied by the complexity of the risk assessment and transfer process. The proposed study intends thus will establish the project characteristics that are most appropriate for each type of project delivery, on the basis of cost-effectiveness to the agency. Application of the framework to specific parochial (but common encountered) scenarios will yield a set of decision matrices from which a simple excel-based electronic expert system will be developed. The expert system will help the agency’s decision-makers select appropriate project delivery approach for a given project on the basis of project characteristics, and the possible consequences of that approach.
Financial and Technical Feasibility of Dynamic Congestion Pricing as a Revenue Generation Source in Indiana − Exploiting the Availability of Real-Time Information and Dynamic Pricing Technologies
Research Information
Start Date: 2009/1/12
Status: Active
Total Dollars: $50,000
Source Organization: Purdue University, West Lafayette
Principal Investigator: Samuel Labi, Purdue University, West Lafayette
Co-Principal Investigator: Kumares Sinha, Purdue University, West Lafayette
Summary of Research
One of the several financing initiatives that can be considered in Indiana and other states is congestion pricing (CP). CP is the establishment of a direct out-of-pocket charge to road users, through spatial or temporal variations in price of roadway use. CP not only generates revenue but also harnesses the power of the market to increase efficiencies in transport infrastructure use. In exploiting the fact that the majority of rush hour drivers on a typical urban highway are not commuters, CP discourages overuse during rush hours by motivating people to travel by other modes such as carpools or transit, or by traveling at other times of the day. Most economists agree that congestion pricing represents the single most viable and sustainable approach to reducing traffic congestion and also can be a viable means of generating some revenue for highway agencies. With currently available sensing and information technologies, highway agencies such as INDOT can, in real-time, determine prices, traffic controls and information strategies in an adaptive manner and in a manner that is based on current and anticipated state of the system. Against the background of limited funding and growing congestion, and the opportunities for technological solutions, this study focuses on the feasibility of dynamic congestion pricing (DCP). Using DCP, tolls can be continually adjusted according to traffic conditions to maintain a free-flowing level of traffic. Under this system, prices increase when the tolled lane(s) get relatively busy and decrease when the tolled lane(s) get less busy. At any time, the prevailing price is displayed on electronic signs located at the approaches to the tolled section. DCP is more complex and less predictable than using a fixed-price table, but its flexibility can help greatly to consistently maintain the optimal traffic flow. Motorists are usually guaranteed that they will not be charged more than a pre-set maximum price under any circumstances. Using inventory and hypothetical future traffic data, the study will carry out numerical experiments to ascertain the technical and economic feasibility of dynamic pricing in separate hypothetical scenarios. The experience of other highway agencies will be reviewed and documented to identify any threats or opportunities to dynamic congestion pricing implementation.
Using Detector Data to Identify and Examine Crashes and Incidents on Freeways
Research Information
Start Date: 2009/1/12
Status: Active
Total Dollars: $24,966
Source Organization: Purdue University, West Lafayette
Principal Investigator: Peter T. Savolainen, Wayne State University
Summary of Research
The Michigan Intelligent Transportation systems (MITS) Center monitors traffic along five freeways in southeastern Michigan using closed circuit television cameras, probe vehicles, and a telephone hotline while continuously collecting traffic flow data. One of the primary objectives of the MITS Center is to improve freeway operations by reducing the delay caused by incidents, including crashes, vehicle breakdowns, and the presence of debris in the roadway. To meet this objective, the MITS Center can alert a Freeway Courtesy Patrol (FCP) vehicle to respond to each incident and alert upstream traffic of the incident through a series of dynamic message signs (DMS). The purpose of this study is to use the available traffic flow, FCP, DMS, and crash data to evaluate freeway operations in metro Detroit. Specifically, this research aims to identify those factors which affect FCP response times and incident clearance times. The result of this study will provide the MITS Center with timely information that, combines with recently proposed "quick clearance" legislation aimed at removing crash-involved and disabled vehicles from the roadway, creates the potential to improve freeway operations and safety. This study will also examine what incident-related factors lead to secondary crashes and seek to determine whether the DMS messages have a significant impact on downstream traffic flow characteristics.
Incorporating Image-Based Traffic Information for AADT Estimation: Operational Developments for Agency Implementation and Theoretical Extensions to Classified AADT Estimation
Research Information
Start Date: 2009/8/14
Status: Active
Total Dollars: $84,113
Source Organization: Purdue University, West Lafayette
Principal Investigator: Mark McCord, Ohio State University
Co-Principal Investigator: Prem Goel, Ohio State University
Summary of Research
State Departments of Transportation (DOTs) commit substantial resources to collecting the data used to estimate annual average daily traffic (AADT) on an ongoing basis. These data are traditionally collected from "on the road" sensors that can disrupt traffic and expose traffic crews to potential danger. A method has been developed to combine information in existing air photos with traditional ground-based traffic counts to produce AADT estimates that are more accurate than those presently produced. In this project, investigators will work with the Ohio DOT toward transforming this method into an operational system that can be used on a routine basis by state DOTs. Investigators will also investigate the potential of extending this method to the estimation of classified AADT, for truck and car, separately.
Smart Campus Transit Laboratory for Research and Education
Research Information
Start Date: 2009/8/14
Status: Active
Total Dollars: $444,599
Source Organization: Purdue University, West Lafayette
Principal Investigator: Rabi Mishalani, Ohio State University
Co-Principal Investigators: Prem Goel, Ohio State University
Mark McCord, Ohio State University
Summary of Research
Through a joint effort from various OSU entities and Clever Devices, Inc., the information system of the Campus Area Bus Service (CABS) is being replaced with an advanced, commercial-grade system currently in the final stages of implementation and testing as part of the development of the Campus Transit Lab (CTL). The information technologies include advanced automatic vehicle location (AVL), automatic passenger count (APC) sensors on buses, and a passenger information system. Some activities from year 1 continue, and new ones are initiated to further exploit the CTL infrastructure. Specifically, the activities include: (1) continue developing a vehicle-level bus transit operations simulation tool, estimate and integrate simulation components using CTL generated data, and use the simulation to investigate various data collection and transit operations research questions; (2) address operations and service planning research questions based on CTL generated data; (3) study passenger perceptions and satisfactions by administering surveys and analyzing the responses; (4) further explore ideas to exploit the CTL for educational activities at OSU and across NEXTRANS partner universities; and (5) continue to work with CABS and Clever Devices on system implementation and operational analyses.
Innovative Vehicle Classification Strategies: Doing More for Less
Research Information
Start Date: 2009/8/14
Status: Active
Total Dollars: $68,603
Source Organization: Purdue University, West Lafayette
Principal Investigator: Benjamin Coifman, Ohio State University
Summary of Research
This proposed research continues on from a NEXTRANS Year 1 grant, "Length based vehicle classification on freeways from single loop detectors," to develop less expensive vehicle classification systems. This proposal consists of two complementary thrusts: use the existing infrastructure more effectively, and second, investigating less expensive alternatives for vehicle classification. The first thrust builds on our preceding NEXTRANS work to extend classification coverage to single loop detectors and non-invasive detectors that emulate single loop detectors, thereby enabling (a) classifying vehicles from detectors already deployed for ITS applications (leveraging existing investments) and (b) classifying vehicles at dual loop detector based classification stations even when one of the loops fail (improving reliability). The second thrust will examine alternatives to conventional classification systems. One promising alternative is using LIDAR to monitor passing vehicles. Such an installation could be permanent or temporary, and would cost significantly less than a comparable in-pavement system. These two thrusts are combined because in each case the most labor intensive component is generating ground truth classification data.
Optimal Condition Sampling of Infrastructure Networks
Research Information
Start Date: 2009/8/14
Status: Active
Total Dollars: $80,824
Source Organization: Purdue University, West Lafayette
Principal Investigator: Rabi Mishalani, Ohio State University
Co-Principal Investigator: Prem Goel, Ohio State University
Summary of Research
Infrastructure systems consist of spatially extensive sets of interconnected facilities with long life spans, which are usually constructed through public, private, or joint endeavors for public or commercial use. In response to the developments in infrastructure inspection technologies, the question of optimizing condition sampling for a single facility has bee recently addressed. This project involves addressing the extension of the single facility level problem to the system and network levels whereby the uncertainty due to condition sampling is captured and its related decision variables are included in the inspection maintenance and rehabilitation decision-making process. In doing so, both statistical and network modeling treatments are necessary. As such, the actual definition of the network becomes essential and, therefore, is investigated as part of this project.
Impact of Public Transit Market Share on Energy Consumption and the Environment: Developing Statistical Models for Validation and Gross Predictions
Research Information
Start Date: 2009/8/14
Status: Active
Total Dollars: $72,001
Source Organization: Purdue University, West Lafayette
Principal Investigator: Prem Goel, Ohio State University
Co-Principal Investigator: Rabi Mishalani, Ohio State University
Summary of Research
The primary objective of this study is to develop a set of empirically derived statistical relationships aimed at quantifying the impacts of market shares and capacity distributions across passenger transport modes on energy consumption and the environment for the purpose of assessing and validating the accuracy of "mechanistic" transportation model systems and their ability to capture these impacts. Such empirical relationships are too gross to be able to support the development of detailed policy design and evaluation, but validated and accurate mechanistic transportation model systems based on these empirical models are expected to provide better answers to policy questions. A secondary objective is to use the developed empirical relationships to arrive at some gross indications of potentially effective policies, and to bracket the type of results that could be achieved by certain policies before any detailed analysis and evaluation are carried out.
2007-2008 Projects
A Decision Support Tool for Vehicle Infrastructure Integration: Understanding Information Effects and Advancing Data Fusion Algorithms for Traffic Management Applications
Research Information
Start Date: 2008/2/15
Status: Active
Total Dollars: $50,000
Source Organization: Purdue University, West Lafayette
Principal Investigator: Srinivas Peeta, Purdue University, West Lafayette
Summary of Research
This research seeks to explore vehicle-to-vehicle information networks to understand the interplay between the information communicated and traffic conditions on the network. A longer-term goal is to develop a decision support tool for processing and storage of large amount of real-time (probe) data for advancing the state of the art in Vehicle Infrastructure Integration (VII). The fundamental concept in VII is that the (probe) vehicles serve as data collectors and anonymously transmit traffic information to transportation agencies to facilitate proactive strategies for traffic management and safety. In the long-term, the project will develop new route guidance strategies and new data fusion algorithms for travel time estimation which will provide a clear representation of the benefit of information exchange between vehicles. In addition, this work will have impacts on congestion management (using technological advances in sensor and wireless technologies) by obtaining macroscopic relationships for congestion estimation.
Analysis of Travel Time Reliability on Indiana Interstates
Research Information
Start Date: 2008/2/15
Status: Active
Total Dollars: $47,097
Source Organization: Purdue University, West Lafayette
Principal Investigator: Fred Mannering, Purdue University, West Lafayette
Summary of Research
Travel-time reliability is a key performance measure in any transportation system. It is a measure of quality of travel time experienced by transportation system users and reflects the efficiency of the transportation system to serve citizens, businesses and visitors. Travel-time reliability (the variability in travel times on the same route at the same time from one day to the next) is critical to travelers, shippers, receivers and carriers for trip decisions and on-time arrivals at destinations. In this study, extensive amounts of data will be gathered from interstates in Indiana (specifically Indianapolis-area interstates where extensive real-time data are collected). These data will be used to develop statistical models to estimate travel-time reliability based on explanatory variables (weather, accidents, etc.) as well as time-varying elements associated with recurrent congestion. The eventual goal of this line of research is to move toward a level-of-service (LOS) concept for travel-time reliability. Thus, in addition to the Highway Capacity Manual definition of LOS, roadways may eventually have a separate travel-time reliability rating similar to the traditional A through F scale used to measure LOS. It is hoped that this research will provide valuable information that can be used as a basis for such a rating.
Integrating Supply and Demand Aspects of Transportation for Mass Evacuation under Disasters
Research Information
Start Date: 2008/2/15
Status: Active
Total Dollars: $50,000
Source Organization: Purdue University, West Lafayette
Principal Investigator: Srinivas Peeta, Purdue University, West Lafayette
Summary of Research
This study seeks to address real-time operational needs in the context of the evacuation response problem by providing a capability to dynamically route vehicles (including commercial trucks) under evacuation, thereby being responsive to the actual conditions unfolding in real-time in the traffic network, both in terms of the evolving traffic patterns (demand-side) and the available road infrastructure in the aftermath of the disaster (supply-side). A key aspect in evacuation operations which is not well-understood is the interplay between route choice behavior and its effect on traffic and supply dynamics (i.e., composition of evacuation traffic, changes in roadway capacities, etc.). Evacuation traffic has historically been quantified with descriptive surveys characterizing the behavioral aspects from social or psychological contexts. Integration of these behavioral aspects into traffic and/or supply-side models has been limited. This study seeks to address such integration for generating realistic and effective evacuation strategies.
Network Origin-Destination Demand Estimation using Limited Link Traffic Counts: Strategic Deployment of Vehicle Detectors through an Integrated Corridor Management Framework
Research Information
Start Date: 2008/2/15
Status: Active
Total Dollars: $50,000
Source Organization: Purdue University, West Lafayette
Principal Investigator: Srinivas Peeta, Purdue University, West Lafayette
Co-Principal Investigator: Shou-Ren Hu, National Cheng Kung University, Taiwan
Summary of Research
In typical road traffic corridors, freeway systems are generally well-equipped with traffic surveillance systems such as vehicle detector (VD) and/or closed circuit television (CCTV) systems in order to gather timely traffic information for traffic control and/or management purposes. However, other highway facilities in the corridor, especially arterials and surface streets in the vicinity of the freeway, mostly lack detector/sensor systems. Yet, most traffic management and control methods/frameworks in the literature assume the availability of time-dependent traffic measures (such as counts, flows, speeds, etc.) on all links of the corridor. Hence, there is a critical disconnect between the practical reality and methodological expectations in terms of detection capabilities. This research seeks to develop a mechanism to strategically deploy vehicle detectors to infer network origin-destination (OD) demands using limited link traffic count data. It leads to the problem of the identification of "optimal" locations for installing detectors so that maximum system observability is achieved with a limited monetary budget. From an integration standpoint, it addresses the question of where to locate detectors on the non-freeway facilities so that, in conjunction with the installed detectors on freeways, the entire corridor can be managed effectively by obtaining the maximum possible accurate information on traffic conditions.
Transportation Infrastructure Implications of Changing Grain, Ethanol and DDGS Transportation Flows for Indiana
Research Information
Start Date: 2008/2/15
Status: Active
Total Dollars: $50,000
Source Organization: Purdue University, West Lafayette
Principal Investigator: Wallace Tyner, Purdue University, West Lafayette
Co-Principal Investigator: Frank Dooley, Purdue University
Summary of Research
The 2007 energy bill calls for the US to produce 36 billion gallons of ethanol by 2022 of which no more than 15 billion would come from corn and 1 billion of biodiesel. Thus, the legislation envisions moving from no cellulose ethanol production today to 20 billion gallons by 2022. In this research project, we will estimate the transport system impacts of different levels of cellulose production in Indiana. A scenario approach will be used for the transport of cellulosic materials to central plants. Transporting cellulose materials to a central processing plant requires more bulk material than for a corn ethanol plant. We will use an integer programming model to locate and size cellulosic plants in Indiana. This model will optimize plant location given the potential cellulosic production from corn stover and other cellulosic inputs in each part of the state. Cellulose supply curves will be developed for each sub-region in the state. We will be able to introduce different scenarios of cellulose development to compare with the base case of no cellulosic ethanol production.
Uncertainty-Based Tradeoff Analysis Methodology for Integrated Transportation Investment Decision-Making
Research Information
Start Date:2008/2/15
Status: Active
Total Dollars: $50,000
Source Organization: Purdue University, West Lafayette
Principal Investigator: Samuel Labi, Purdue University
Summary of Research
The research project will develop a methodology for multi-program selection and trade-offs analysis of alternative sets of transportation projects, based on the benefits and costs of each alternative in terms of the various performance measures. In complementing an ongoing Indiana Department of Transportation (INDOT) sponsored study, the project will involve the uncertainty perspective, a variety of new analytical tools from the literature, and an algorithm for the developed methodology. The developed algorithm, together with the risk-based algorithm developed from the sister INDOT study, will then be implemented in the existing asset management software package developed at Purdue University in 2004. Data on candidate projects in at least one state will be used to validate the algorithm. The research product will help fulfill the national needs for integrating infrastructure renewal decisions and help achieve the goal of maximizing utilization of limited resources. This fits well into at least one level of the NEXTRANS theme and addresses elements of the NEXTRANS dimensions in varying degrees. Furthermore, the research findings are expected to provide a theoretical foundation for future studies that would involve higher levels and dimensions of infrastructure decision-making
Investigation of Emergency Vehicle Crashes in the State of Michigan
Research Information
Start Date: 2008/3/1
Status: Active
Total Dollars: $24,954
Source Organization: Purdue University, West Lafayette
Principal Investigator: Peter Savolainen, Wayne State University
Summary of Research
Emergency vehicle involved crashes are a substantial problem nationwide. One common cause of such crashes is the failure of non-emergency vehicle drivers to identify an approaching emergency vehicle in time to react and yield the right-of-way. An evaluation of an emergency vehicle alert system (EVAS) aimed at addressing this particular problem has recently been completed. This project supplements the previous research by providing a comprehensive investigation of emergency vehicle crashes in the State of Michigan to identify other factors contributing to crash occurrence and resultant injuries. Emergency vehicle crashes are particularly problematic in Michigan, which is among four states that account for 37.5% of the country's ambulance-involved fatalities. Over 13,601 emergency vehicle crashes occurred in Michigan over the past five years. Unfortunately, the causal factors associated with many of these crashes are unclear. The purpose of this research is to conduct an evaluation of emergency vehicle crashes and to identify driver, vehicle, and environmental characteristics affecting both emergency vehicle crash frequency and resultant injury severity. This evaluation will allow for the identification of engineering, education, and enforcement countermeasures to be integrated into a comprehensive action plan aimed at addressing emergency vehicle crashes.
Research and Education from a Smart Campus Transit Laboratory
Research Information
Start Date: 2008/2/15
Status: Active
Total Dollars: $331, 505 (Year 1)
Source Organization: Purdue University, West Lafayette
Principal Investigators: Mark McCord, Ohio State University, University Transportation Center
Rabi Mishalani, Ohio State University, University Transportation Center
Prem Goel, Ohio State University Department of Statistics
Summary of Research
For almost a decade, investigators have been monitoring Ohio State University's Campus Area Bus Service (CABS), which transports three to four million passengers every year. Up until now, this system has operated with a "homemade" communications and information system called BLIS (Bus Location and Information System), which utilizes GPS-based automatic vehicle location (AVL). Through a joint effort with OSU's Transportation and Parking (T&P) department, College of Engineering, Department of Civil and Environmental Engineering and Geodetic Science, and Clever Devices, Inc., NEXTRANS investigators are currently working to replace BLIS with a state-of-the-art "smart bus" system. This new system will include advanced automatic vehicle location (AVL), automated passenger counting (APC), and passenger information systems capabilities. It also provides a unique opportunity to develop an infrastructure for transportation research and educational activities: the OSU Campus Transit Lab (CTL). The research and educational activities of the CTL will relate to the role and impacts of applying emerging information technologies to optimize the performance of public transit systems. Simulating bus route operations allows for analysis and improvement of various transit functions, including performance monitoring, operating strategy development, and service provision. Estimating transit passenger OD flows from AVL and APC data provides an opportunity to enhance the quality of transit network design, service planning, route frequency determination, and schedule coordination. Results from this research will provide insights on how to achieve improved transit planning and operations in a cost-effective manner. Such improvements will attract increased ridership to this efficient and sustainable mode of passenger transportation. In addition to research, educational activities are aimed at encouraging CTL site visits for NEXTRANS funded students, and incorporating CTL data into existing OSU courses including civil engineering, statistics, and data analysis for arts and science majors.
Length Based Vehicle Classification on Freeways from Single Loop Detectors
Research Information
Start date: 2008/2/15
Status: Active
Total Dollars: $44,875
Source Organization: Purdue University, West Lafayette
Principal Investigator: Benjamin Coifman, Ohio State University, University Transportation Center
Summary of Research
This research seeks to develop reliable length based vehicle classification algorithm for single loop detectors (and for non-invasive detectors that emulate single loop detectors) in which traffic would be sorted into three (or more) bins based on length. While single loop detectors are the most common vehicle detectors, they can only estimate vehicle speed and thus, length. By conventional means these estimates are too noisy to be used for accurate vehicle classification. Key to this work is estimating individual vehicle speeds accurately. After which point, the approach is an extension of dual loop detector based vehicle classification employed by many state departments of transportation (DOTs) (dual loop detectors can measure vehicle speed directly, avoiding the problems encountered at single loop detectors). Single loop detectors promise to be an inexpensive alternative to spread classification coverage through the existing count stations and through mixed use of existing traffic operations detector stations. The proposed research seeks to enable such an extension to these existing detector stations.
Optimal Condition Sampling of Infrastructure Networks
Research Information
Start date: 2008/2/15
Status: Active
Total Dollars: $39,505
Source Organization: Purdue University, West Lafayette
Principal Investigators: Rabi Mishalani, Ohio State University, University Transportation Center
Prem Goel, Ohio State University, Department of Statistics
Summary of Research
In response to the developments in pavement inspection technologies, the optimization problem for condition sampling for a single facility was addressed recently. This project involves addressing the condition sampling optimization problem for a network of facilities, under budgetary constraints. In this regard, a precise definition of the infrastructure network becomes essential. An existing methodology to do so will be refined leading to a more robust definition of infrastructure networks.
Estimating AADT from Combined Air Photos and Ground-Based Data: System Design, Prototyping, and Testing
Research Information
Start date: 2008/2/15
Status: Active
Total Dollars: $36,562
Source Organization: Purdue University, West Lafayette
Principal Investigator: Mark R. McCord, Ohio State University, University Transportation Center
Co-Principal Investigator: Prem Goel, Ohio State University, Department of Statistics
Summary of Research
This project developed a method that combines traditional ground-based traffic data with traffic information contained in recent air photos in a statistically justified manner to produce more accurate estimates of Annual Average Daily Traffic (AADT). In two limited empirical studies, the project has demonstrated the improved accuracy in AADT estimates using Ohio DOT data. To enable the implementation of this promising method, this project will (a) develop an efficient way to use it on a widespread, repeated basis in an operational setting; (b) demonstrate the improved accuracy in AADT estimates in a large-scale, controlled study; and (c) evaluate the performance of this method to produce AADT estimates for cars and trucks separately.
Traffic Flow Characteristic and Capacity in Intelligent Work Zones
Research Information
Start date: 2008/2/15
Status: Active
Total Dollars: $74,312
Source Organization: Purdue University, West Lafayette
Principal Investigator: Rahim F. Benekohal, University of Illinois, Urbana-Champaign
Summary of Research
Intelligent work zones (WZ) may operate differently than regular WZ due to motorist interaction with ITS technologies. A fundamental understanding of traffic flow characteristics and capacity under ITS conditions is lacking. Most of the current knowledge about WZ traffic flow is a simple extension of the knowledge from the regular section of highways. Such extension may not be suitable for WZ traffic conditions. This study would investigate the traffic flow characteristics in Intelligent WZ and will determine methods for computing delay, speed, capacity, and user's cost. A theoretical relationship will be developed based on understanding the complexity of traffic flow characteristics in breakdown/recovery mode in WZ bottlenecks, and field data will be and collected and used to examine the validity of the theory. The findings from this research will help to reduce congestion and improve safety in WZ. This research supports the theme of NEXTRANS by finding solutions that are innovative, relying on basic research and understanding of traffic flow principles, integrating technology in managing congestion in chokepoints, and improving the understanding of the flow breakdown and recovery in highway WZ.
Sensor Network Design for Multimodal Freight Transportation Systems
Research Information
Start date: 2008/2/15
Status: Active
Total Dollars: $51,171
Source Organization: Purdue University, West Lafayette
Principal Investigator: Yangeng Ouyang, University of Illinois, Urbana-Champaign
Summary of Research
With increasing demand for freight transportation infrastructure, ensuring efficiency and sustainability of transportation networks becomes a major challenge. This highlights the need for an integrated, systems-level framework that incorporates cutting-edge information technologies and advanced multimodal network modeling techniques to monitor and manage complex freight transportation systems. This project will (1) investigate the possibility of combining various off-the-shelf sensors to improve granularity and accuracy of traffic data; (2) develop an analytical framework to quantify the benefits and costs of deploying (multiple types of) sensors major freight transportation modes; and (3) develop discrete network optimization models to select optimal sensor locations and communication configuration.
Pavement Damage Due to Different Tire and Loading Configurations on Secondary Roads
Research Information
Start date: 2008/2/15
Status: Active
Total Dollars: $61,020
Source Organization: Purdue University, West Lafayette
Principal Investigator: Imad Al-Qadi, University of Illinois, Urbana-Champaign
Summary of Research
The main objective of the proposed research is to evaluate the mechanism of load distribution for dual and wide-base tires on secondary road pavements. The research team will simulate vehicle loading and predict pavement response's utilizing the finite element (FE) method. The research project will develop the necessary finite element models to simulate secondary roads using a three-dimensional (3D) approach. Almost all aspects (model dimensions, element types and thickness, far field simulation, etc.)of the proposed model will be optimized to approach near actual behavior of pavement systems including the use of dynamic analysis. This includes simulating tread patterns for dual and wide-base tire configurations, incorporating advanced constitutive model for hot-mix asphalt into the FE model, and validating the developed FE models as related to available experimental measurements.
Development of a Finite Element Based Thermal Cracking Performance Prediction Model
Research Information
Start date: 2008/2/15
Status: Active
Total Dollars: $53,004
Source Organization: Purdue University, West Lafayette
Principal Investigator: William Buttlar, University of Illinois, Urbana-Champaign
Co-Principal Investigator: Glaucio H. Paulino, University of Illinois, Urbana-Champaign
Summary of Research
Low-temperature cracking of hot-mix asphalt (HMA) pavements continues to be a leading cause of premature pavement deterioration in cold regions. While recent modeling advances have led to new insights into cracking mechanisms, there remains the challenge of implementing these models into a stand alone, practitioner-friendly program. Furthermore, the theme of the NEXTRANS Center is to develop integrated solutions to transportation problems by explicitly capturing the interactions between the vehicle, driver/traveler, and the infrastructure. Following the successful first phase of the National Pooled Fund Study on Low Temperature Cracking, a second phase will be initiated in mid-2007 and continue for two to three years. The proposed supplemental study will extend the scope of the existing pooled fund study to more explicitly capture the interactions between vehicles and the infrastructure (Pillar 2 of NEXRANS). The main deliverable of this project would be a user-friendly, computationally efficient program which could be used to analyze and to design against thermal cracking in asphalt pavements. Unlike previous cracking prediction models, the proposed can explicitly consider the interactions between vehicles (highway/air passenger/freight) and new and rehabilitated pavement systems which can be directly integrated with asset management systems.
Nondestructive Pavement Evaluation using Finite Element Analysis Based Soft Computing Models
Research Information
Start date: 2008/2/15
Status: Active
Total Dollars: $52,439
Source Organization: Purdue University, West Lafayette
Principal Investigator: Erol Tutumluer , University of Illinois, Urbana-Champaign
Summary of Research
The objectives of the proposed NEXTRANS research are to: (1) develop the framework for an innovative methodology called Soft Computing Based Pavement and Geomaterial System Analyzer (SOFTSYS) for evaluating in-service flexible pavements with the purpose of determining pavement layer thicknesses as well as the layer properties from nondestructive Falling Weight Deflectometer (FWD) data without the need for pavement coring, (2) compare and verify SOFTSYS results with those of the nonlinear ILLI-PAVE Finite Element (FE) solutions, and, (3) validate SOFTSYS for determining pavement thicknesses and layer properties with actual field data where nondestructive Ground Penetrating Radar (GPR) tests can be performed for layer interface locations and/or cores can be collected from existing highway pavements in coordination with the nondestructive FWE testing and pavement evaluation activities of state highway agencies.
Community Research Into Transportation Issues
Research Information
Start date: 2008/5/01
Status: Active
Total Dollars: $25,000
Source Organization: Purdue University, West Lafayette
Principal Investigator: Algeania Freeman
Co-Principal Investigator: Gloria Ameny-Dixon, Dennis Jackson
Summary of Research
As a partner with Purdue University's NEXTRANS project, Martin University is developing a research proposal that seeks to identify innovative solutions to transportation concerns related to mobility, safety, and infrastructure for problems arising in the Martindale Brightwood community. As Martin University students become involved in this research project during the 2008-09 and subsequent academic years, they will explore career opportunities related to transportation. Students' participation in the project will also allow them to become familiar with transportation careers that require the collection, analysis, and interpretation of social and environmental data and the utilization of such data in local and national social policy decisions.
