Projects

An interdisciplinary team of UT faculty members have been awarded a $399,793 grant by the National Science Foundation (NSF). The team, comprised of Asad Khattak, Subhadeep Chakraborty, and Shashi Nambisan, was selected by NSF’s Division of Civil, Mechanical, and Manufacturing Innovation for their research proposal titled “Study of Driving Volatility in Connected and Cooperative Vehicle Systems.”

Recent technological advances enable vehicle-to-vehicle and vehicle-to-infrastructure communications. These technologies allow wireless exchange of critical safety and operational data between and among vehicles and infrastructure system elements. These include location, heading, speed, and acceleration data attributes. The research aims to study the role of wireless connectivity and how information from modern sensors can be integrated, processed, and disseminated to offer innovative solutions to address major societal challenges related to safety, mobility, energy, and emissions.

The proposed activities are important to advancing knowledge and understanding in areas such as travel behavior, control systems, information technology, and complex transportation systems.

The research will integrate educational and outreach activities, and will also provide interdisciplinary training to students, with special efforts made to recruit minority students through the Tickle College of Engineering’s Office of Diversity Programs.

Relevant Papers:

• Liu J. & A. Khattak. Delivering Improved Alerts, Warnings, and Control Assistance Using Basic Safety Messages Transmitted between Connected Vehicles, Conditionally accepted for publication in Transportation Research, Part C, 2016.

Collisions at highway-rail grade crossings with vehicles, pedestrians, bicyclists, and other users are a continuing societal concern. However, a growing concern is trespassing pedestrian collisions with trains. The objective of this study is to investigate injuries and fatalities to trespassing pedestrians that occur along rail-lines (and at highway-rail grade crossings).

The scope of the study will be restricted to analysis of relevant crash and inventory data obtained from Federal Railroad Administration. The relevant crash and inventory data for at least a three year period will be downloaded and linked together. The data will be analyzed using descriptive analysis and rigorous modeling techniques to quantify factors associated with injuries/fatalities in pedestrian-rail crashes. The associated factors will include rail-track area attributes as well as other characteristics of the train, pedestrian age, and socio-demographic variables of the area where the crash occurs, e.g., levels of unemployment or age of housing stock or proximity of tracks to schools and similar land uses.

The investigation will provide insights into countermeasures that are appropriate in specific situations. The study will recommend education, engineering, enforcement, or encouragement countermeasures based on factors associated with higher likelihood of fatality vs. non-fatal injury. The study will provide insights on improving the safety of pedestrians along rail tracks and at highway-rail crossings.

Relevant Papers:

• Wang, X., Liu, J., Khattak, A. J., & Clarke, D. (2016). Non-crossing rail-trespassing crashes in the past decade: A spatial approach to analyzing injury severity. Safety Science, 82, 44-55.
• Liu, J., Khattak, A. J., Richards, S. H., & Nambisan, S. (2015). What are the differences in driver injury outcomes at highway-rail grade crossings? Untangling the role of pre-crash behaviors. Accident Analysis & Prevention, 85, 157-169.
• Zhang, M., A. Khattak, J. Liu, & D. Clarke, A comparative study of rail-pedestrian/bicyclist trespassing crash injury severity at highway-rail grade crossings and non-crossings. Presented at the 2015 Road Safety & Simulation International Conference, Orlando, FL.

With increasing amounts of information generated by electronic sensors from various sources that include travelers, vehicles, infrastructure, and the environment coupled with social, economic, and spatial data, integrating and processing datasets has become complex.

Collectively the databases are referred to as “big data,” which can be fragmented, disorganized, and difficult to analyze. Yet, they represent an opportunity for innovation in transportation system planning, design, operation, and maintenance, and moving toward achieving safety and mobility goals.

In this project, we propose that big data derived from new and conventional transportation sources can be used to enhance highway safety. The objective of this MRI is to develop innovative programs to monitor, assess, and improve safety using big data. The tools and products to be developed will be used to enhance safety in pre-crash, during crash, and post-crash situations. The framework and programs developed for big data should consider multiple transportation modes.

Key Objectives:

• Generate new frameworks for acquisition and use of big data to facilitate safety monitoring, assessment, and improvement.
• Visualize and analyze big data and develop tools and products that can be used (e.g., in transportation management centers) to improve safety and facilitate the integration of safety performance in transportation system planning, design, and operation.
• Take advantage of opportunities arising from big data to create safety products and tools and create new knowledge.

Papers Published:

• Liu J., A. Khattak & X. Wang. The role of alternative fuel vehicles: Using behavioral and sensor data to model hierarchies in travel. Transportation Research Part C: Emerging Technologies, 55, 379-392. Chicago
• Wang X, A. Khattak, J. Liu, G. Masghati-Amoli & S. Son. What is the Level of Volatility in Instantaneous Driving Decisions? Transportation Research Part C: Emerging Technologies, 2015. DOI: 10.1016/j.trc.2014.12.014

With the publication of the Highway Safety Manual (HSM), there is a now a formal document that can be used to link roadway design with safety consequences. Part C of HSM provides prediction models that can be used for project level analysis to assess the safety impacts of alternative designs. Crash modification factors (CMFs), which provide an estimate of the safety effectiveness of specific treatments, are available for selected treatments from Part D of HSM. However, there are many treatments for which reliable CMFs are not available. The proposed initiative will develop CMFs for high priority engineering treatments.

Simulation has evolved into a productive tool for predicting and evaluating safety on roadways and street networks. Simulation aptly defines human actions, addresses the effectiveness of roadway design and traffic operations on transportation safety, and helps to develop surrogate safety measures. Judicious and creative implementation of simulation tools holds great promise for enhancing the HSM methodologies and approaches.

The southeastern United States has among the highest roadway incident and injury rates in the country. While this disparity in roadway safety has been explored numerous times, these studies most often investigate the physical design characteristics of the transportation infrastructure.

Some studies focus on the weather, government policies (e.g., speed limits, seat belt law), and the role of human factors in designing the infrastructure or vehicles. When socio-demographic characteristics are considered in other studies, they are typically limited to gender, age, and race or ethnicity. The results from these studies have not provided a comprehensive picture or convincing explanation for regional safety performance differences.

The effort we propose will expand this limited set of characteristics to include socio-demographic characteristics, risk-taking and health characteristics, land use patterns, and other measures that consider the culture and values of the population as potential explanatory factors.

This project aims to quantify the impacts of growth and technology strategies at the regional level by using modeling, simulation, and visualization tools, with the overall goal of enhancing livability and sustainability.

The most important research outcome is the creation of a modeling and simulation system capable of addressing interactions between land use, transportation, and emissions as the foundation for research on sustainable urban development strategies, e.g., compact growth and eco-friendly transportation information delivery.

It is clear that such systems will be of interest to state and regional planning agencies as they attempt to reduce gasoline consumption and emissions. The noticeable outcomes of the project will thus include the development of a modeling framework for evaluation of strategies that encourage alternative mode usage and provide eco-information to travelers.

The framework will be applied to a test-case (Hampton Roads region in Virginia), and the results will be documented in a technical report, academic papers, and presentations at transportation conferences.

The outcomes of the project include planning tools that encourage the consideration, evaluation and implementation of more robust growth and eco-friendly transportation strategies.

Published or Presented Papers:

• Wang, X., A. Khattak & Y. Zhang, Is smart growth associated with reductions in CO2 emissions? Published in Transportation Research Record: Journal of the Transportation Research Board, 2375, 2013, pp. 62-70. Presented at 2013 Transportation Research Board Annual meeting
• Wang X., A. Khattak, J. Liu, G. Amoli, S. Son, What is the Level of Volatility in Instantaneous Driving Decisions? Presented at the Transportation Research Board 2014 annual meeting (TRB Paper 14-2780). Plenary Session Invited Talk, 13th COTA International Conference of Transportation Professionals, CICTP, Shenzhen, China, August 2013; presented at Hong Kong University of Science and Technology, and at PacTrans Seminar Series at University of Washington.
• Liu J., X. Wang, A. Khattak, Generating Real-Time Driving Volatility Information. Presented at ITS World Congress 2014 conference (Detroit, Sep 7–11).
• Bandeira, J., D. Carvalho, P. Fernandes, T. Fontes, S. Pereira, N. Rouphail, A. Khattak, M. Coelho, Empirical Assessment of Route Choice Impact on Emissions Over Different Road Types, Traffic Demands, and Driving Scenarios. International Journal of Sustainable Transportation, 2013. 10.1080/15568318.2014.901447 doi.
• Bandeira J., P. Fernandes, T. Fontes, S. Pereira, A. Khattak, & M. Coelho, Assessment of Eco-Traffic Assignment Strategies in an Urban Corridor. Under review.
• Bandeira J., S. Pereira, T. Fontes, P. Fernandes, A. Khattak, M. Coelho, An Eco-Traffic Management Tool, Computer-based Modeling and Optimization in Transportation, Advances in Intelligent Systems and Computing, Volume 262, 2014, pp 41-56.
• Son S., A. Khattak & K. Choi, Comparing Travel Behavior Between Transit-Oriented Developments and Automobile-Oriented Developments: Matched Pair Analysis, TRB Paper 14-2327, Presented at the Transportation Research Board, National Academies, Washington, DC, 2014.

Transportation planners always need ‘good’ data elements that are readily available, up-to-date, accurate, and relevant. Quickly obtaining such data can be a challenge. This project seeks to identify such unmet planning data needs and develop solutions for how users can acquire quality data.

In addition to conducting a literature review of planning data needs and solutions other states have implemented, key tasks for this project will include identifying planning-related data needs of Virginia Department of Transportation and planners at metropolitan planning organizations and planning district commissions; existing data sources that meet these needs and are accessible either now or expected to become accessible in the near term (one to two years); and potential short-term solutions for addressing these data needs.

The research and educational activities for this project focus on developing vehicle purchase and use choice models in China to estimate sustainability impacts of various growth scenarios and vehicle technologies and inform a sustainable policy response.

This research will include of two major activities: 1) Vehicle purchase and use behavior will be characterized to identify general personal transportation values and potential motorization pathways. This work will use a combination of stated and revealed preference choice modeling methods to quantify characteristics that people choose now, and potential technologies that could be adopted in the near-term. This would ultimately be used to build motorization scenarios with different fuels and technologies, under various economic and policy frameworks.

2) Vehicle growth scenarios will be extended to quantify environmental impacts through life-cycle assessment (LCA) methods. Each scenario (technological and economic) will have varied impacts from an environmental perspective, leading to policies that could minimize environmental impacts within the bounds of other policy objectives. The project will characterize transportation choice behavior in a systematic way, across major Chinese cities, which has not been done before at this scale.

This insight will quantify factors, beyond national GDP, that influence motorization, leading to more robust vehicle purchase and mode choice modeling. To this end, viability of alternative fuels will be assessable and the sustainability implications quantifiable.

The educational activities will target several audiences, including K-12 students, undergraduate and graduate students. Activities will include a K-12 outreach programs, a freshman seminar, content for new graduate courses, and international experiences at universities in China. The educational activities will be integrated into the research component by engaging undergraduate and graduate students in the data collection, model development, and policy analysis.

This project will be interdisciplinary, so students with varied educational backgrounds will have an opportunity to learn from and teach others to successfully analyze a topic as interdisciplinary as sustainability and transportation choice. The broader impacts of this project include the development of an internationally minded transportation workforce, capable of operating in diverse and challenging environments; the recruitment and inclusion of underrepresented groups in engineering; and the improved understanding of sustainability implications of motorization pathways in China, leading to policy that can reduce local air pollution, greenhouse gas emissions, and energy use. This award is co-funded by OISE-China.