Breakout 14: Enhancing the Validity of Traffic Flow Models with Emerging Data

Breakout 14: Enhancing the Validity of Traffic Flow Models with Emerging Data

Tuesday, July 11, 1:30 PM – 5:30 PM
Continental 7


  • Meng Wang, Delft University of Technology, chair
  • Xiaopeng (Shaw) Li, University of South Florida, co-chair
  • Samer, Hamdar, George Washington Unversity, co-chair
  • Haizhong Wang, Oregon State University
  • Soyoung Ahn, University of Wisconsin – Madison
  • Mark Brackstone, TSS -Transport Simulation Systems
  • Danjue Chen, University of Massachusetts Lowell
  • Steven Mattingly, University of Texas Arlington
  • Alexander Skabardonis, University of California, Berkeley
  • Michael Levin, University of Minnesota

Session description

This breakout session provides an opportunity to bring together the cyber-physical, communications, vehicle and traffic flow communities to better understand the fundamental characteristics of traffic flow with varying levels of automation and identify the research needs for developing models to assess real-world mobility and environmental sustainability implications of connected automated vehicles (CAV).

This breakout session will focus on discussion of innovative traffic flow modeling techniques and simulation tools to quantify the mobility and environment impacts of CAV and their implications on highway capacity and freeway operations and designs. Special attention will be given to insights into behavioral differences in terms of lane-changing (lane choice, lane change execution) and car-following (following gap, reaction time, acceleration distribution) maneuvers and validation of existing and new CAV traffic flow models according to empirical data from CAV field tests.

Invited representatives from road authorities, industry, and academia will share state-of-the-art research findings and challenges for this growing interdisciplinary field and the whole group will discuss data needs, data availability, and validation and calibration methods for CAV traffic flow models, plausible scenarios to be modeled with different vehicle classes, facilities and market penetration rates. The breakout session will provide opportunities for collaboration across research communities.

This breakout session will generate session presentations, research needs statements, discussion group notes, and a chapter of the symposium proceedings.


1:30 PM – 1:40 PM: Welcome (AHB45(3) Goals and Activities)
Meng Wang, Delft University of Technology

1:40 PM – 3:50 PM: Panel: Data and Test-Beds Examples: An International Overview
Moderator – Meng Wang, Delft University of Technology
Steve Mattingly, University of Texas Arlington (Co-Moderator and Questions)
Xiaopeng (Shaw) Li, University of South Florida (Co-Moderator)
Michael Levin, University of Minnesota (Note Taking)

The role of data collected in Australian deployments and pilots to inform how humans want to interact with technology

  • Rita Excell, Australia and New Zealand Driverless Vehicle Initiative

Connected and Automated Vehicular Flows: Modeling Framework and Data Availability

  • Jiaqi Ma, Leidos, Inc.

Selected Field Experiments on the Chang'an University CAV Testbed

  • Zhigang (David) Xu, Chang’an University, China

Recent findings from micro-simulation of traffic impacts of cooperative longitudinal control systems

  • Steven Shladover, PATH Berkeley, University of California

Control of traffic with a small number of automated vehicles

  • Daniel Work, University of Illinois at Urbana Champaign

3:50 PM – 4:00 PM Break

4:00 PM – 5:00 PM Panel discussion


  • Rita Excell, Australia and New Zealand Driverless Vehicle Initiative
  • Jiaqi Ma, Leidos, Inc.
  • Zhigang (David) Xu, Chang’an University, China
  • Steven Shladover, PATH Berkeley, University of California
  • Daniel Work, University of Illinois at Urbana Champaign

5:00 PM – 5:30 PM Reporting and conclusing


Rita Excell, Australia and New Zealand Driverless Vehicle Initiative (Executive Director)
Title: The role of data collected in Australian deployments and pilots to inform how humans want to interact with technology.

This presentation will outline the numerous activities being undertaken in Australia and how a coordinated approach is facilitating the sharing of lessons learnt and next steps in Australia and beyond. In 2015 the Australian Road Research Board formed a collaboration of like minded organisations to work together to rapidly progress the introduction of driverless vehicles onto Australian roads. As we approach the second year of the Australia and New Zealand driverless vehicle initiative the collaboration has grown to over 100 partners and active deployment of research and trials of connected and automated vehicles taking place across Australia and in New Zealand. Data being generated and collated from these pilots and research projects will be explained and how this collaborative approach is supporting a customer and end user centric deployment strategy in Australia.

Rita Excell is the Executive Director of the Australia and New Zealand Driverless Vehicle Initiative (ADVI) Centre for Excellence and is responsible for delivering ADVI’s contribution to the safe and successful introduction of driverless vehicle technologies into Australia and New Zealand.

Her prior roles include Regional Manager of ARRB Group’s South Australian office, where she managed key strategic policy projects for State Road Authorities and organisations that manage public and private road infrastructure.

Rita is a qualified Civil Engineer with over 25 years’ experience, which has included roles in Local Government and more than 13 years with RAA - where she worked on strategic transport planning, road safety and advocacy. She is currently the President of the IPWEA South Australia and sits on the Australasian board of IPWEA, as well as the Port Adelaide Development Assessment Panel”.

Jiaqi Ma, Leidos, Inc. [Research Scientist and Project Manager]
Title: Connected and Automated Vehicular Flows: Modeling Framework and Data Availability

Advanced connected automated vehicle (CAV) technologies enable us to modify driving behavior and control vehicle trajectories, which have been greatly constrained by human limits in existing manually-driven highway traffic. Understanding and modeling automated vehicle driving behavior is critical to evaluating transportation system performance under different CAV deployment scenarios. This presentation firstly introduces a general CAV analysis, modeling and simulation (CAV AMS) framework currently under development by Federal Highway Administration (FHWA). Then, data needs and available datasets to calibrate these models are discussed. Lastly, data collection efforts through field experiments using CAVs and connected infrastructure at the FHWA Saxton Transportation Operations Lab are discussed. These projects include cooperative adaptive cruise control, cooperative merge, eco approach and departure and eco-driving on rolling terrains.

Dr. Jiaqi Ma is a Research Scientist and Project Manager with Leidos, Inc., working at the FHWA Turner Fairbank Highway Research Center. He received his Ph.D. degree from the Department of Civil and Environmental Engineering at the University of Virginia. His areas of expertise include connected automated vehicles, Intelligent Transportation Systems, traffic modeling and simulation, network optimization, planning for operations, travel demand forecasting, and data mining. He has managed and participated in many research projects funded by USDOT and state DOTs, covering a wide range of areas including vehicle automation-based Speed Harmonization, Cooperative Adaptive Cruise Control, bottleneck identification and mitigation, and Benefit/Cost analysis of Traffic Incident Management Strategies, etc. He has published more than 30 articles in prestigious peer-review journals and over 30 papers published and presented at top conferences. He is a Member of the TRB Standing Committee on Vehicle-Highway Automation, a member of the TRB Subcommittee on Travel Time Speed and Reliability, and a member of the American Society of Civil Engineers.

Zhigang (David) Xu; Chang’an University, China
Title: Selected Field Experiments on the Chang'an University CAV Testbed

Abstract: Chang'an University (CU) CAV testbed (CU-CAVTest) is located on Weishui Campus of CU, which occupies 282,000 square meters (about 70 acres). It includes a 2.4 kilometer high-speed circular test track with 2 lanes and an extra 1.1 kilometer straight 4-lane test road with 4 kinds of pavement (asphalt, concrete, bricks, and dirt). It is furnished with a fleet of connected and autonomous vehicles and smart infrastructure, including five heterogeneous wireless networks, a UWB-based high precision positioning system and high performance computing resources. Overall, this testbed is one of the few large-scale CAV test sites around the world with comprehensive smart highway systems under a fully controlled environment. 4 field experiments conducted on this testbed will be introduced, including 1) 4G-LTE vs. DSRC field performance comparison; 2) aggregated fuel consumption estimation using connected vehicle data; 3) trajectory tracking algorithms for AV; and 4) trajectory optimization for CAV platoons.

Dr. Zhigang Xu is currently an Associate Professor of the College of Information Engineering, Chang’an University, China. He is also the vice director of the Joint Lab of Internet of Vehicles Sponsored by China Mobile and Ministry of Education. He is also the Secretary General of China Innovation Alliance of Connected and Automated Vehicles Testing (CAVTest) and the Chair of Connected and Automated Vehicle Committee under World Transport Convention (WTC). He received his M.S. and Ph.D. degrees in Traffic Information Engineering & Control from Chang’an University, respectively. He had worked at the University of California, Davis as a visiting scholar in 2015.

Dr. Xu’s research focuses on the Connected and Automated Vehicles, Nondestructive Testing on Transportation Infrastructure and Image Processing. He led the construction of the first large-scale Cooperative Vehicle-Infrastructure System (CU_CVIS) among China Universities, which is also among the first few of its kind around the world. He conducted joint research projects with several famous domestic IT giants such as China Mobile, Datang Mobile and Neusoft. He has published more than 40 articles in peer-reviewed journals and 15 patents. He was invited to make presentations and keynote speeches at a number of international conferences such as TRB,COTA,TRC、ICTIM. He organized a team named “Xinda” on developing autonomous cars and participating grand challenges. Dr. Xu won 1 National and 2 Provincial Scientific and Technological Progress Awards in China for his research contribution on testing the performance of vehicles and transportation infrastructure.
Prof. Zhigang Xu, School of Information Engineering, Chang’an University, The middle section of the S. 2nd Ring-road, Xi’an, Shaanxi, P. R. China,710064,

Steven Shladover; PATH, UC Berkeley
Recent findings from micro-simulation of traffic impacts of cooperative longitudinal control systems

This presentation presents state-of-the-art simulation results representing the microscopic interactions between manually driven vehicles and vehicles that use automatic longitudinal control systems, both autonomous (ACC) and cooperative (CACC). The models representing the automated car following behavior of the ACC and CACC systems are derived directly from the experimental responses of full-scale vehicles equipped with these systems, so they are much more realistic than previous theoretical models that have over-estimated traffic flow benefits of ACC. The models of manual driving include details of lane changing interactions on multi-lane highways, and have been calibrated using field data from a complex freeway corridor. Results from this simulation study show the effects on highway throughput of various operational strategies including both continuous and limited access managed lanes for the equipped vehicles, limitations on discretionary lane changing, and limitations on the lengths of coordinated strings of vehicles, with varying levels of on-ramp and off-ramp traffic and for various market penetrations of equipped vehicles.

Dr. Steven Shladover has been researching road vehicle automation systems for more than forty years, beginning with his masters and doctoral theses at M.I.T. in the 1970s. He is the Program Manager, Mobility at the California PATH Program of the Institute of Transportation Studies of the University of California at Berkeley. He led PATH’s pioneering research on automated highway systems, including its participation in the National Automated Highway Systems Consortium from 1994-98, and has continued research on fully and partially automated vehicle systems since then. This work has included definition of operating concepts, modeling of automated system operations and benefits, and design, development and testing of full-scale prototype vehicle systems. His target applications have included cooperative adaptive cruise control, automated truck platoons, automated buses and fully-automated vehicles in an automated highway system.

Dr. Shladover joined the PATH Program in 1989, after eleven years at Systems Control, Inc. and Systems Control Technology, Inc., where he led the company’s efforts in transportation systems engineering and computer-aided control engineering software products. He chaired the Transportation Research Board Committee on Intelligent Transportation Systems from 2004-2010, and currently chairs the TRB Committee on Vehicle-Highway Automation. He was the chairman of the Advanced Vehicle Control and Safety Systems Committee of the Intelligent Transportation Society of America from its founding in 1991 until 1997. Dr. Shladover leads the U.S. delegation to ISO/TC204/WG14, which develops international standards for “vehicle-roadway warning and control systems”.

Daniel Work; University of Illinois at Urbana Champaign, USA
Title: Control of traffic with a small number of automated vehicles

Traffic control via mobile actuation is now viable thanks to recent and significant improvements in self-driving and connected vehicle technologies, and may offer new traffic management opportunities beyond today’s fixed control systems such as variable speed limits. As a motivating example, we show experimental evidence suggesting that careful control of a small number of autonomous vehicles in the traffic stream is sufficient to completely eliminate “phantom” traffic jams caused by human driving. We build on the seminal demonstration conducted by the Mathematical Society of Traffic Flow, in which 22 human-driven vehicles that initially drive smoothly around a circular track eventually degrade into substantial stop-and-go traffic. These experiments resolved a long-standing discussion in transportation science, namely that traffic waves can in fact arise without any external causes, but did not offer a solution to prevent it. We repeat the 22 vehicle experiments with the modification that one intelligently controlled autonomous vehicle replaces a single human-piloted vehicle. A series of experiments in Tucson, Arizona are conducted to measure the influence of the carefully controlled AV on human-piloted vehicles. Our main experimental result indicates that even when the penetration rate of autonomous vehicles is as low as 5%, stop and go traffic can be eliminated. The elimination of waves allows significant improvements in the total traffic fuel efficiency and safety, and is achievable long before the majority of vehicles are automated.

Daniel Work is an assistant professor in the Department of Civil and Environmental Engineering, the Department of Electrical and Computer Engineering (courtesy), the Coordinated Science Laboratory, and the National Center for Supercomputing Applications at the University of Illinois at Urbana-Champaign. Prof. Work earned a B.S. (2006) from the Ohio State University, and an M.S. (2007) and Ph.D. (2010) from the University of California, Berkeley, each in civil engineering. Prior to joining the faculty at Illinois, Work was a research intern at Nokia Research Center, Palo Alto from 2008-2009, and a guest researcher at Microsoft Research Redmond in 2010. Prof. Work has research interests in control, estimation, and optimization of transportation cyber physical systems. Prof. Work has received a number of honors and awards including selection to participate in the National Academy of Engineering’s 2016 EU-US Frontiers of Engineering Symposium, being named a UIUC CEE Excellence Faculty Fellow in 2016, the 2015 UIUC ASCE Outstanding Professor Award, and the CAREER Award from the National Science Foundation in 2014.

Session facilitators

  • Note taker: Michael Levin
  • Research needs statements writers: Samer Hamdar, Meng Wang, Xiaopeng Li, Stephen Mattingly

Breakout 14 / 25