Special Sessions

We are pleased to announce that the following Special Sessions will integrate the Technical Program of ITSC 2016.


Special Session details:


SS01: “Designing and Managing Communication in Intelligent Transportation Systems”

Special Session Code: me35g

Organizers: Cristiano Maciel Silva (UFSJ, Brazil), Andreas Pitsillides (U. Cyprus, Cyprus)

E-mails: cristiano@ufsj.edu.br, andreas.pitsillides@ucy.ac.cy

Scope and Goals:

The special session “Designing and Managing the Communication in Intelligent Transportation Systems” proposes the exploration of the design and the management of the data communication network supporting Intelligent Transportation Systems. Since Intelligent Transportations Systems are typically critical mission systems, and the decision making is highly dependent upon the data collected from the network, properly designing and managing the communication network is an essential step before deploying any ITS application. Otherwise, there is reduced confidence in the availability and robustness of the ITS system.
The topics of interest have been carefully selected in order to allow a comprehensive look into the most significant issues on Developing the Communication in Intelligent Transportation Systems. For example, a thorough comprehension of the urban and rural mobility is certainly a crucial aspect for the development of ITS communication. An in-depth understanding of urban and rural mobility enables us to design, develop evaluate and validate more realistic ITS models in terms of algorithms, analytic formulations, optimization models, and probabilistic approaches.
More sophisticated ITS Models support the development of better strategies for Planning & Managing the Communication in intelligent Transportation Systems. Furthermore, better ITS Models combined with a better understanding of the role played by mobile networks may even allow new insights on the application of the Internet of Things, Cloud-based services, and Software Defined Networks (SDNs), allowing the development of more sophisticated services and applications. The management aspects of SDN, IoTs and clouds are certainly of current interest and crucially important in the development and wide deployment of these networks. Their adoption in ITS systems is also vitally important for their wider applicability and real deployment.
Furthermore, the use of social networking and crowd sourcing strategies may also represent a valuable source of management information for Intelligent Transportation Systems. Handling large amounts of data from mobile devices in order to infer interesting knowledge and/or patterns may provide a turning point in terms of the ITS technology, and several research projects are investigating the benefits and potential of this collaborative crowd sourcing based approach, in general.

Topics of Interest:

  • Network Management & Communication in ITS
  • Vehicular Networks
  • Experience Reports & Experimental Testbeds
  • Privacy, Authentication, Reputation for ITS
  • Clouds, SDN
  • Traffic prediction and mobility models
  • Social Networks for ITS
  • Algorithms, optimisation models, and probabilistic approaches
  • Green ITS & Economic issues
  • Legal and regulative issues


SS02: “Machine Learning for Autonomous Driving”

Special Session Code: vcfym

Organizers: Senthil Yogamani (Valeo Vision Systems, Ireland)

E-mails: senthil.yogamani@valeo.com

Scope and Goals:

Machine learning has played a key role in realizing Autonomous Driving exemplified by the success of Google’s self-driving car. There are several successful demonstrations of the potential of end-to-end learning of a statistical model (eg: DeepDriving). Deep Learning has demonstrated outstanding results in supervised learning problems and probabilistic graphical models can capture the strong priori information present in automotive environments. In spite of this success, the state-of-the-art machine learning models have not been exploited fully in ITS. For instance, classical Kalman filters are still the norm for tracking and fusion instead of the more generic Bayesian networks. The computational power available (eg: Nvidia DrivePX2) has increased rapidly to leverage these more sophisticated models. Additionally, the advancements in semantic 3D digital maps (eg: TomTom RoadDNA) has made the problem more tractable.
This special session aims to bring together the latest results of machine learning applied to various research problems in Autonomous Driving and commercial Driver Assistance systems. We are soliciting ontributions in (but not limited to) the following topics:

Topics of Interest:

  • Applications of Deep Learning ranging from object detection to end-to-end learning.
  • Probabilistic Graphical Models like dynamic Bayesian networks (DBNs) for SLAM and sensor fusion.
  • Machine learning for sparse sensors like LIDAR and RADAR.
  • Reinforcement learning for Trajectory and Route Planning.
  • Machine learning based multi-sensor fusion algorithms.
  • Real-time system implementations on embedded platforms.


SS03: “Traffic Data Mining and Knowledge Discovery in ITS”

Special Session Code: 7au8k

Organizers: Javier J. Sanchez-Medina (ULPGC, Spain), Luís Moreira-Matias (NEC Laboratories Europe, Germany)

E-mails: javier.sanchez.medina@ieee.org, luis.matias@neclab.eu

Scope and Goals:

Recently, we are witnessing a new way to approach ITS based on the use of the massive data we that that is being recorded by in any modern transportation vehicle. Every public transport, as well as many private vehicles and/or pedestrians are equipped with pervasive computing and distributing sensing devices e.g. smartphones/bluetooth, RFID readers, floating car data, plate recognition (video cameras), induction loops, handovers on telecommunications, AVL, APC/AFC, etc. All that devices can be faced as rich information sources for traffic and mobility managers in general. However, the volume of information is way too big that we need to be able to dig deep down in order to discover useful and hence nontrivial knowledge. The range of potential applications of that knowledge is wide. Mobility planners and/or traffic managers may get to know accurate demand patterns. Based on those, we may develop accurate estimations on its future states. Following this path, we may detect anomalies (e.g. malfunctioning layouts or accidents) on early stages or even before they happen. These insights may serve as basic input to advanced simulation and/or optimization frameworks, which can provide solutions, recommendations and key advices able to support optimal decisions in this context.
Consequently, this kind of technologies is fully loaded with potential applications for the sake of a smarter, cleaner and safer mobility in our cities. With this Special Session, we just want to visualize and group together recent developments in this field, fostering fruitful conversation and interchange for a specific and increasingly frequent community within ITSCs conferences, computer and data scientists and engineers, that sometimes are not given their fitted forum.

Topics of Interest:

  • Big Data, Data Mining, and Knowledge Discovery
  • Traffic Management and Highway Control
  • Traffic flow Forecasting
  • Drivers’ Behavior
  • (OD) Demand Estimation, and Occupancy Estimation
  • Smart Mobility


SS04: “Wireless Vehicular Communications”

Special Session Code: sq265

Organizers: Li Zhu (Beijing Jiaotong University, China), F. Richard Yu (Carleton University, Canada), Tao Tang (Beijing Jiaotong University, China), Bin Ning (Beijing Jiaotong University, China)

E-mails: zhulibjtu@gmail.com, richard.yu@carleton.ca, ttang@bjtu.edu.cn, bning@bjtu.edu.cn

Scope and Goals:

This special session aims to gather the relevant results of on-going works about all aspects of the design and optimization of wireless vehicular communication systems, including vehicle to roadside communication systems, rail transit communication systems, vehicle to vehicle communication systems, etc. The special session on “Wireless Vehicular Communications” provides a forum for discussions of all these most up-to-date developments and brings together industry and academia, engineers and researchers.

Topics of Interest:

  • Communications and protocols in ITS
  • Rail traffic management
  • Network management


SS05: “Recent Advances in Motorway Traffic Control”

Special Session Code: 6c563

Organizers: Claudio Roncoli (TU Crete, Greece), Silvia Siri (U. Genova, Italy)

E-mails: croncoli@dssl.tuc.gr, silvia.siri@unige.it

Scope and Goals:

Motorway traffic congestion represents a significant challenge particularly for large and growing metropolitan areas. Besides the construction of new infrastructures, it has been shown that the application of control strategies to mitigate congestion has a strong potential for an improvement of traffic conditions in motorway traffic networks, reducing delays, alleviating environmental pollution, and increasing traffic safety. Therefore, the definition of models for the prediction of motorway traffic behaviour and the development of estimation and control methodologies for motorway traffic systems have been relevant research topics for several decades and present still challenging issues to be investigated. In particular, due to the technological developments in measurement, communication and computing devices, conventional models and control approaches need to be revised in order to fully exploit the potential of new technologies.
The goal of this Special Session is to bring together representatives from academia to share and discuss ideas on the state of the art, novel theoretical approaches, and practical applications within the field of motorway traffic control. The papers submitted within this Special Session will cover different aspects of motorway traffic, including modelling, optimisation, control, and estimation methodologies. This Special Session will be open to both papers on theoretical investigations of these aspects and papers based on field applications of motorway traffic control schemes.

Topics of Interest:

  • Theoretical investigations of estimation and control techniques for motorway networks
  • Local or network-wide estimation and control strategies
  • Motorway traffic estimation and control in the presence of connected/automated vehicles
  • Traffic control approaches for sustainable mobility in motorway networks
  • Innovative models for control design in motorway networks
  • Field applications and case studies


SS06: “Ensuring and Validating Functional Safety for Automated Vehicles”

Special Session Code: m8esq

Organizers: Torben Stolte (TU Braunschweig, Germany), Andreas Reschka (TU Braunschweig, Germany), Gerrit Bagschik (TU Braunschweig, Germany), Markus Maurer (TU Braunschweig, Germany)

E-mails: {stolte, reschka, bagschik, maurer}@ifr.ing.tu-bs.de

Scope and Goals:

Automated vehicles corresponding to SAE levels 4 and 5 are operated in open environments with a non-quantifiable amount of possible driving situations and, simultaneously, without human supervision. Reaching functional safety in any situation is one of the major challenges heading towards series deployment of automated vehicles in public traffic. Despite its importance, functional safety is still a niche topic in the ITS community – at least in our reception. Hence, this Special Session aims at promoting scientific exchange in this field by encouraging and concentrating contributions with respect to functional safety of automated vehicles.
Developing functionally safe systems requires a holistic consideration of development processes. For instance, this is addressed in the international ISO 26262 standard, the most recent standard available regarding functional safety in the automotive domain. The scope of proposed Special Session is on selected aspects during the development of automated vehicle functionalities.
Following a safety-by-design paradigm as proposed by the ISO 26262 standard, first scope of the proposed Special Session is the concept phase for developing automated vehicle functionality. Still, the suitability of existing methodologies, approaches and concepts for ensuring functional safety must be examined regarding automated vehicles. So far, these appear to be not sufficient. This is due to the driver vanishing as important part in safety concepts, as deployed in vehicles operating up to SAE level 3.
Another very important step for series deployment of automated vehicles is validation of the functional safety concept. Due to the non-quantifiable amount of possible driving situations, it is impossible to validate the system’s behaviour in any possible driving situation. Thus, methodologies must be found in order to generate convincing statements that the vehicle automation system is capable of dealing with any driving situation.

Topics of Interest:

  • System modeling
  • Hazard identification
  • Safety analysis
  • Metrics for risk and safety
  • Safety concepts
  • Handling of challenging/critical scenarios
  • Functional safety of environment perception
  • Ensuring safety under uncertainty
  • Safety validation
  • Standardization


SS07: “Cooperative ITS for Public Transport”

Special Session Code: e94ev

Organizers: Marcin Seredynski (Luxembourg Institute of Science and Technology, Luxembroug), Umberto Guida (International Association of Public Transport, Belgium), Francesco Viti (U. Luxembourg, Luxembourg)

E-mails: marcin.seredynski@list.lu, umberto.Guida@uitp.org, francesco.viti@uni.lu

Scope and Goals:

High-capacity Public Transport (PT) is the only option for urban corridors with high mobility demand. As PT is one of the key components of sustainable urban mobility, increase of its market share is an important worldwide objective. The PTx2 action of the International Association of Public Transport (UITP) sets a goal of doubling PT’s market share by 2025 compared to 2005. PT systems are constantly evolving to address new environmental and mobility challenges. The new concepts of bus operations such as Bus Rapid Transit (BRT) emerge. At the same time growing number of high-capacity electric buses is observed. However, the existing methods supporting the PT efficiency in operations are insufficient, as they were designed for old, less complex and demanding PT systems dominated by diesel buses and simple punctuality objective. Moreover, these methods use old technologies, which limit their scope to simple and isolated strategies such as slack time management and signal priority. Cooperative ITS (C-ITS) allows to bypass the existing limitations and to develop an innovative system approach influencing the entire PT ecosystem in a comprehensive way. Its concept of connectivity assumes communication between vehicles and between vehicles and the stationary infrastructure such as traffic signals. Together with the open data connectivity brings to PT systems collective intelligence. However, new research is necessary to introduce these innovations into the PT industry.

Topics of Interest:

  • Traffic management for electric/hybrid buses
  • Link-level PT priority measures (with-flow lanes, contra-flow lanes, etc.) and junction-based measures such (transit signal priority, queue relocation, pre-signals techniques, etc.);
  • Real-time passenger information systems
  • Automated PT operations
  • Open Data
  • Simulation and modeling of PT systems
  • Personalised mobility/Demand Responsive Transport (DRT)
  • Cooperative systems and connected vehicles for PT
  • Advanced driver assistance systems/Eco-driving


SS08: “Cooperative (de-)centralized traffic management”

Special Session Code: 49mq6

Organizers: Bernhard Friedrich (TU Braunschweig, Germany), Jörg P. Müller (TU Clausthal, Germany), Fidler Markus (Leibniz Universität Hannover, Germany)

E-mails: friedrich@tu-bs.de, joerg.mueller@tu-clausthal.de, markus.fidler@ikt.uni-hannover.de

Scope and Goals:

The aim of this Special Session is to present and discuss new research results methods and applications of decentralized, cooperative traffic management, that are enabled by new technological trends and developments such as Vehicle-to-X communication. The session will focus on the interplay of centralized management in the sense of classical traffic control, and decentralized management in the sense of the local goals of individual traffic participants. The session aims at an interdisciplinary audience including behavioral aspects of traffic participants, societal objectives, technical, and algorithmic foundations of communication, interaction, and dynamic geo-information, as well as models and methods of cooperative, (de)centralized traffic management, including traditional physical dynamics, multiagent systems, game-theoretic, autonomic systems models, and hybrid approaches trying to integrate the aforementioned. It is expected that the approaches presented in this session will advance the field towards solutions that will enable us to realistically describe dynamic cooperative traffic systems, and to evolve and optimize such systems in accordance with societal objectives.

Topics of Interest:

  • Autonomic methods and models for self-organizing traffic systems
  • Centralized and decentralized architectures and models for traffic management
  • Cooperative multimodal mobility
  • Emerging applications and use cases of cooperative traffic control
  • Human-centered models and approaches for cooperative traffic control
  • Intelligent cooperative traffic signal control
  • Interacting autonomous vehicles and traffic control
  • Multiagent systems for traffic management and control
  • Smart information services (digital maps, guidance, …) for cooperative traffic systems
  • Vehicle-2-X communication and traffic management


SS09: “2nd Special Session on Human Factors in Intelligent Transportation Systems (HFITS)”

Special Session Code: gry44

Organizers: Cristina Olaverri Monreal (UAS Technikum Wien, Austria), Fernando Garcia (University Carlos III, Spain)

E-mails: olaverri@technikum-wien.at, fegarcia@ing.uc3m.es

Scope and Goals:

The second edition of the “Human Factors in Intelligent Transportation Systems” (HFITS) Special Session follows up previous editions of Workshops on Human Factors in Intelligent Vehicles (HFIV) held at IEEE IV Conferences, which have been supported and promoted by the IEEE ITS Society’s HFITS, and ATSS Technical Activities Committees (TC).
The aim of the HFITS series is to foster the discussion on issues related to the analysis and understanding of human factors in the design and evaluation of Intelligent Transportation System (ITS) technologies, in a wide spectrum of applications and in different dimensions. It is expected to build up a proper environment to disseminate knowledge related to the theories, principles, data and methods for designing transportation systems in order to (1) optimize human well-being and overall system performance, (2) motivate interactions among the technical and scientific communities, practitioners and students, and (3) facilitate the state-of-the-art concepts and advances to be further developed and enhanced.
ITS technologies have experienced a great improvement in the last couple of decades, turning vehicles into more interactive counterparts in transportation and mobility systems. However, the impact of such technologies on traffic awareness of the drivers, driver behavior towards improving driving performance and reducing road accidents, as well as driver psycho and physical exhaustion, still demands proper tools and approaches to be better investigated. Whereas the feasibility of incorporating new technology-driven functionalities to vehicles has played a central role in the automotive design, not always safety issues related to interaction with the new in-vehicle systems have been taken into consideration. Additionally, some other aspects are also important and need to be analyzed, such as the impacts of the technologies supporting specific driving functions on the primary task of driving, and the overall performance of transportation systems. Besides current industrial achievements of a number of important driving assistance systems, the perspective of autonomous driving vehicles populating urban areas pose even more challenging issues. Also, the information and functionalities that rely on new ways of communication have to be presented in a non-intrusive way while complying with specific design requirements.
Whereas workshops aim primarily at discussing in an informal environment about the trends, the work in progress and new ideas related to Human Factors in Intelligent Transportation Systems, special sessions are intended to be focused on specific achievements, topics and problems within the field. In this second edition of the HFITS Special Session, we encourage and welcome contributions reporting new developments of Human Factors and Human System Interaction to support the better design of transportation systems with improved efficiency, comfort, and user satisfaction, and to build a safer driving environment.

Topics of Interest:

  • Intelligent user interfaces
  • Interaction with autonomous vehicles
  • Human-machine interaction
  • Human-in-the-loop simulation
  • Cognitive aspects of driving
  • Human behavior and capability, affecting system design and operation
  • Modelling and simulation of driving performance
  • Behavioral modelling and validation methodologies
  • Tools and approaches to human factors analyses
  • Ergonomics of traveler information systems
  • Anthropometric layout of vehicular technical systems
  • Cross-Cultural Design
  • Augmented Cognition
  • User Experience and Usability
  • Computer Aided Ergonomics Analysis
  • Effects of in-vehicle systems on driver performance
  • Tools and methodologies for usability assessment
  • Input/output modalities in system ergonomic design
  • Leaning, Anticipation, and Adaptation balance
  • Driving Education and Training Methodologies
  • Driver and pedestrian behavior, affecting driving safety
  • Accident or driving scenario modeling in naturalistic driving environment
  • Multimodal human-vehicle interaction
  • Vehicle inside and outside state monitoring
  • Driver support systems in limited ability autonomous driving