Connected and Autonomous Vehicles (CAV) An Innovation Hub to Future-Proof Connected and Autonomous Technologies

2007-2008 Projects

Research Information

Start Date: 2008/2/15
Status: Completed
Total Dollars: $50,000
Source Organization: Purdue University, West Lafayette
Principal Investigator: Srinivas Peeta, Purdue University

Summary of Research

This research explored vehicle-to-vehicle information networks to understand the interplay between the information communicated and traffic conditions on the network. As a long-term goal, researchers developed a decision support tool for processing and storing large amounts 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.

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Research Information

Start Date: 2008/2/15
Status: Completed
Total Dollars: $47,097
Source Organization: Purdue University, West Lafayette
Principal Investigator: Fred Mannering, Purdue University

Summary of Research

Travel-time reliability is a key performance measure in any transportation system. It observes the quality of travel-time experienced by transportation system users and reflects the efficiency of the system to serve citizens, businesses, and visitors. Travel-time reliability is critical to travelers, shippers, receivers, and carriers for trip decisions and on-time arrivals. In this study, an extensive amount of data was gathered from interstates in Indiana. This data was 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 goal of this 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.

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Research Information

Start date: 2008/2/15
Status: Completed
Total Dollars: $53,004
Source Organization: Purdue University, West Lafayette
Principal Investigator: William Buttlar, University of Illinois at Urbana-Champaign
Co-Principal Investigator: Glaucio H. Paulino, University of Illinois at 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. The main deliverable of this project is a user-friendly, computationally efficient program which could be used to analyze and design against thermal cracking in asphalt pavements. Unlike previous cracking prediction models, the developed model can explicitly consider interactions between vehicles (highway, air passenger, freight) and new and rehabilitated pavement systems which can be directly integrated with asset management systems.

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Research Information

Start date: 2008/2/15
Status: Completed
Total Dollars: $36,562
Source Organization: Purdue University, West Lafayette
Principal Investigator: Mark R. McCord, Ohio State University
Co-Principal Investigator: Prem Goel, Ohio State University

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 (i) developed an efficient way to use it on a widespread, repeated basis in an operational setting; (ii) demonstrated the improved accuracy in AADT estimates in a large-scale, controlled study; and (iii) evaluated the performance of this method to produce AADT estimates for cars and trucks separately.

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Research Information

Start Date: 2008/2/15
Status: Completed
Total Dollars: $50,000
Source Organization: Purdue University, West Lafayette
Principal Investigator: Srinivas Peeta, Purdue University

Summary of Research

This research addressed real-time operational needs in the context of the evacuation response problem by providing a capability to dynamically route vehicles 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 and the available road infrastructure in the aftermath of a disaster. 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 (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 addressed such integration for generating realistic and effective evacuation strategies.

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Research Information

Start Date: 2008/3/1
Status: Completed
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 failure of non-emergency vehicle drivers to identify an approaching emergency vehicle in time to react and yield the right-of-way. Over 13,601 emergency vehicle crashes occurred in Michigan over the past five years (as of 2007). The purpose of this research was 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.

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Research Information

Start date: 2008/2/15
Status: Completed
Total Dollars: $44,875
Source Organization: Purdue University, West Lafayette
Principal Investigator: Benjamin Coifman, Ohio State University

Summary of Research

This research developed a reliable length-based vehicle classification algorithm for single loop detectors in which traffic would be sorted into three (or more) bins based on length. The approach is an extension of dual loop detector-based vehicle classification employed by many state departments of transportation (DOT); 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 operation detector stations. This project aimed to enable such an extension to existing detector stations.

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Research Information

Start Date: 2008/2/15
Status: Completed
Total Dollars: $50,000
Source Organization: Purdue University, West Lafayette
Principal Investigator: Srinivas Peeta, Purdue University
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. 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 (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 aimed to develop a mechanism to strategically deploy vehicle detectors to infer network origin-destination (O-D) demands using limited link traffic count data.

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Research Information

Start date: 2008/2/15
Status: Completed
Total Dollars: $52,439
Source Organization: Purdue University, West Lafayette
Principal Investigator: Erol Tutumluer, University of Illinois at Urbana-Champaign

Summary of Research

The objectives of this research were to (i) develop 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; (ii) compare and verify SOFTSYS results with those of the nonlinear ILLI-PAVE Finite Element (FE) solutions; and (iii) 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.

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Research Information

Start date: 2008/2/15
Status: Completed
Total Dollars: $39,505
Source Organization: Purdue University, West Lafayette
Principal Investigators: Rabi Mishalani, Ohio State University
Prem Goel, Ohio State University

Summary of Research

In response to developments in pavement inspection technologies, the optimization problem for condition sampling for a single facility was recently addressed. This project involved 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 was also refined leading to a more robust definition of infrastructure networks.

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Research Information

Start date: 2008/2/15
Status: Completed
Total Dollars: $61,020
Source Organization: Purdue University, West Lafayette
Principal Investigator: Imad Al-Qadi, University of Illinois at Urbana-Champaign

Summary of Research

The main objective of this research was to evaluate the mechanism of load distribution for dual and wide-base tires on secondary road pavements. The research team simulated vehicle loading and predicted pavement response utilizing the finite element (FE) method. Investigators developed the necessary finite element models to simulate secondary roads using a three-dimensional (3D) approach. Almost all aspects of the model were 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 an advanced constitutive model for hot-mix asphalt into the FE model, and validating the developed FE models as related to available experimental measurements.

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Research Information

Start Date: 2008/2/15
Status: Completed
Total Dollars: $331, 505 (Year 1)
Source Organization: Purdue University, West Lafayette

Informational Video: Campus Transit Lab Video
Principal Investigators: Mark McCord, Ohio State University
Rabi Mishalani, Ohio State University
Prem Goel, Ohio State University

Summary of Research

NEXTRANS investigators, various OSU entities, and Clever Devices, Inc., are currently upgrading OSU’s Campus Area Bus Service (CABS) with a state-of-theart “smart bus” system. This new system includes advanced automatic vehicle location (AVL), automated passenger counting (APC), and a passenger information system. It also creates an infrastructure for research and education: the OSU Campus Transit Lab (CTL). Activities will include researching operations and service planning questions, developing a simulation tool, and studying passenger perceptions.

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Research Information

Start date: 2008/2/15
Status: Completed
Total Dollars: $51,171
Source Organization: Purdue University, West Lafayette
Principal Investigator: Yangeng Ouyang, University of Illinois at 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 information technologies and multimodal network modeling techniques to monitor and manage complex freight transportation systems. This project (i) investigated the possibility of combining various off-the-shelf sensors to improve granularity and accuracy of traffic data; (ii) developed an analytical framework to quantify the benefits and costs of deploying (multiple types of) sensors to major freight transportation modes; and (iii) developed discrete network optimization models to select sensor locations and communication configuration.

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Research Information

Start date: 2008/2/15
Status: Completed
Total Dollars: $74,312
Source Organization: Purdue University, West Lafayette
Principal Investigator: Rahim F. Benekohal, University of Illinois at 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 knowledge from regular sections of highway. Such extension may not be suitable for WZ traffic conditions. This study investigated traffic flow characteristics in intelligent WZ and determined methods for computing delay, speed, capacity, and user cost. A theoretical relationship was developed based on understanding the complexity of traffic flow characteristics in breakdown/recovery mode in WZ bottlenecks, and field data was collected and used to examine the validity of the theory. The findings from this research helped to reduce congestion and improve safety in WZ.

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Research Information

Start Date: 2008/2/15
Status: Completed
Total Dollars: $50,000
Source Organization: Purdue University, West Lafayette
Principal Investigator: Wallace Tyner, Purdue University
Co-Principal Investigator: Frank Dooley, Purdue University

Summary of Research

The 2007 energy bill calls for the U.S. to produce 36 billion gallons of ethanol by 2022; restrictions exist on the number of gallons able to come from corn or biodiesel. Meaning, legislators envision moving from no cellulose ethanol production today to approximately 20 billion gallons by 2022. In this project, researchers estimated the transport system impacts of different levels of cellulose production in Indiana. A scenario approach was 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. Investigators used an integer programming model to locate and size cellulosic plants in Indiana. This model optimized plant location given the potential cellulosic production from corn stover and other cellulosic inputs in each part of the state. Cellulose supply curves were developed for each sub-region in the state. The research produced different scenarios of cellulose development to compare with the base case of no cellulosic ethanol production.

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Research Information

Start Date:2008/2/15
Status: Completed
Total Dollars: $50,000
Source Organization: Purdue University, West Lafayette
Principal Investigator: Samuel Labi, Purdue University

Summary of Research

This project developed a methodology for multi-program selection and tradeoff analysis of alternative sets of transportation projects, based on the benefits and costs of each alternative in terms of various performance measures. Complementing an ongoing study, the research involved the uncertainty perspective, a variety of new analytical tools from literature, and an algorithm for the developed methodology. The developed algorithm was implemented in the existing asset management software package developed at Purdue University in 2004. Data on candidate projects from at least one state was used to validate the algorithm. The research product will help fulfill national needs for integrating infrastructure renewal decisions and help to achieve the goal of maximizing utilization of limited resources. 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.

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