Workshop on Intelligent Transportation Systems (ITS)
Workshop Date: 3rd January 2018
The fourth workshop on Intelligent Transportation Systems (ITS) will be held in conjunction with COMSNETS 2018. This interdisciplinary workshop aims to bring together researchers from various disciplines, and will focus particularly on interdisciplinary approaches to solving urban transportation problems. The workshop invites original papers that make contributions to modeling and control of urban transportation systems. We welcome papers involving any combination of theory, analytical modeling and optimization, numerical simulations, real-world data-driven approaches, experimentation, advanced deployment and case studies. Studies involving economic, behavioral and environmental aspects are equally welcome.
Domains of interest include, but are not limited to:
- Traffic theory for ITS
- Modelling, control and simulation
- Emissions, noise, environment
- Multi-modal and public transportation management
- Economic considerations
- V2V and V2I theory and applications
- Human factors and human behavior
- Dynamic characterizations and emergent phenomena
- Emergencies and accidents: phenomena, management and mitigation
- Sensors and Big data and ITS
- ITS field tests, deployment and experimentation
- Design and evaluation of machine learning models on IoT data
- Automated Vehicles
- Submissions must be no greater than 6 pages in length including all figures, tables, and references and must be a PDF file. A minimum number of 3 pages are required.
- Reviews will be single-blind: authors name and affiliation should be included in the submission.
- Submissions must follow the formatting guidelines as given on IEEE Website.
- All workshop papers (full papers - both regular and invited) will appear in conference proceedings and submitted to IEEE Xplore as well as other Abstracting and Indexing (A&I) databases.
- All papers must be in Adobe Portable Document Format (PDF) and submitted through the ITS Workshop submission site on EDAS.
- Papers can also be submitted through EDAS directly : Click Here
|Paper Submission||27th November 2017 9:00 AM IST|
|Notification of Acceptance||1st December 2017|
|Camera-ready Submission||8th December 2017|
|Workshop Date||3rd January 2018|
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.
Ramakalyan Ayyagari, NIT Trichy, India
Pravesh Biyani, IIIT Delhi, India
Lili Du, Illinois Institute of Technology, USA
Samiul Hasan, University of Central Florida, USA
Krishna Jagannathan, IIT Madras, India
D. Manjunath, IIT Bombay, India
Jayakrishnan Nair, IIT Bombay, India
Rahul Nair, IBM Research, Ireland
Manoj Panda, Amrita University, India
Arun Prakash, MIT, USA
Gaurav Raina, IIT Madras, India
Shaunak Sen, IIT Delhi, India
Shankar Subramaniam, IIT Madras, India