Abstract: Automatic Vehicle Following Systems (AVFS) have been investigated for the past seventy years and have recently been deployed in passenger vehicles in the form of Adaptive Cruise Control (ACC) Systems. AVFS have two important components –choice of a spacing policy and an associated control system. Spacing policy dictates the desired following distance at any given speed while the control system is concerned with regulating the following distance at its desired value with the available information. AVFS couple the motion of vehicles by feedback and consequently, errors in maintaining a desired following distance and velocity can propagate in a collection of vehicles employing AVFS. Depending on the underlying information flow graph, amplification of errors in spacing can occur and often result in chain collisions or pileups. The topic of string stability in automatic vehicles is concerned with propagation of spacing errors in a collection of vehicles and is the central focus of my talk. In this talk, I will relate how vehicle models, information flow among vehicles and spacing policies play an important role in the propagation of errors by considering various types of information flow graphs.

Bio: Swaroop Darbha received his Bachelor of Technology from the Indian Institute of Technology - Madras in 1989, M. S. and Ph. D. degrees from the University of California in 1992 and 1994 respectively. He was a post-doctoral researcher at the California PATH program from 1995 to 1996. He has been on the faculty of Mechanical Engineering at Texas A&M University since 1997, where he is currently a professor. He is a fellow of ASME and IEEE. His current research interests lie in the development of vehicle control and diagnostic systems for Autonomous Ground Vehicles, development of planning, control and resource allocation algorithms for a collection of Unmanned Aerial Vehicles.

Abstract: Over the last few years, we are seeing a convergence of technology, data, analytics and new modeling approaches in transportation systems. This trend is expected to continue with rapid advances in technology, growth of connected and self driving cars/communities and our ability to collect high velocity spatio-temporal data. In the transportation network modeling community, many investigations have explored the potential of these technologies especially as they relate to smarter mobility in cities. With the rapid convergence of these technologies, there is a need to develop new modeling frameworks and advance opportunities that exist in this space. This talk with present ongoing research on how network science approaches, data driven techniques and connected/autonomous vehicles are (re) shaping the smart mobility arena. This talk will discuss the speaker’s experience with various big data sources (taxi cab, social media, cell phone, camera data, etc), new network modeling approaches and autonomous vehicle models for making cities smarter and resilient.

Bio: Dr. Satish V. Ukkusuri is a Professor in the Lyles School of Civil Engineering at Purdue University since July 2014 where he teaches courses in transportation systems and freight and logistics planning. Previously, he was an Associate Professor at Purdue University from 2009-2014 and on the faculty of the Department of Civil and Environmental Engineering at the Rensselaer Polytechnic Institute from August 2005 - August 2009. Dr. Ukkusuri is a member of the Transportation and Infrastructure group at Purdue. Dr. Ukkusuri is a co-lead of the Building Sustainable Communities cluster hire at Purdue University with a goal of hiring seven faculty in this interdisciplinary area.

Bio: C. S. Shankar Ram is currently an associate professor in the Department of Engineering Design, Indian Institute of Technology Madras, Chennai, India. He received his Bachelor of Engineering (B. E.) in Mechanical Engineering from MotilalNehru Regional Engineering College, Allahabad, India and his M. S. and Ph. D. from Texas A&M University, USA. He was awarded the 'Young Faculty Recognition Award' by IIT Madras and the 'INAE Young Engineer Award' by the Indian National Academy of Engineering (INAE). His research interests are in the areas of dynamics and control with applications to automotive and transportation systems.

Abstract: This talk would start of by identifying the need for a collision avoidance system in heavy road vehicles such as buses and trucks. The challenges involved in designing such a system would be discussed from the perspective of heavy road vehicle dynamics. The overall process involved in designing the collision avoidance algorithm by controlling the vehicle braking would be presented. Related work that has been carried out would be highlighted along with the evaluation of the algorithm in a Hardware-in-Loop experimental system. A method for incorporating the heterogeneity of traffic in the collision avoidance algorithm would be discussed.