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IEEE ITSC 2017 IEEE 20th International Conference on Intelligent Transportation Systems
Yokohama, JAPAN.
October 16 - 19, 2017


1 Connected, cooperative and automated transport - from IEEE 802.11p towards 5G [PDF]
[Submit paper]
2 Humna Fators in Intelligent Vehicles [PDF]
[Web site]
[Submit paper]
3 Eco-drive at Intersections with Connected,Cooperative and Automated Vehicle [PDF]
[Submit paper]
4 Workshop on Modelling, Analysis and Control of Intelligent Mobility-on-Demand Systems [PDF]
[Web site]
[Submit paper]
5 Deep Learning for Autonomous Driving [Web site]
[Submit paper]
6 Artificial Transportation Systems and Simulation [Submit paper]
7 The Third International Workshop on Intelligent Public Transports - Toward the Next Generation of Urban Mobility [PDF]
[Submit paper]
8 Behavioural Change Support Intelligent Transportation Applications [PDF]
[Web site]
[Submit paper]
9 Transportation 5.0 [PDF]
[Submit paper]
10 International workshop on Large-Scale Traffic Modeling and Management [PDF]
[Submit paper]

Workshop details

1. Connected, cooperative and automated transport - from IEEE 802.11p towards 5G

Recent developments in telecommunication, sensor and information technologies have enabled substantial progress in the domain of automation of transport. Cooperative driving is technologically achievable today, but is only in a very early stage of deployment. Automated driving is on the horizon, and will still need substantial and longer-term development and testing to make even the high automation levels a reality in complex situations such as in urban environments, and in a transit period of only partial market penetration. Cooperative and automated transport are certainly complementary. They are expected to bring substantial benefits in terms of safety, comfort and (traffic and fuel) efficiency. Many challenges exist in this important domain. The workshop targets competing communication technologies, e.g. peer to peer (IEEE 802.11p), cellular network, and future 5G. The challenges of ITS applications towards automated driving (especially related to telecommunication) will be highlighted. Industry requirements will be analysed. 5G development status, especially from the perspective of automotive applications, will be updated. Innovation trends and topics for R&D cooperation will be addressed. The workshop is expected to be very interactive. Participants will have an excellent opportunity to discuss with, and to challenge distinguished speakers from industry.


2. Humna Fators in Intelligent Vehicles

The Workshop on Human Factors in Intelligent Vehicles (HFIV '17) aims to foster discussion on issues related to the analysis of human factors in the design and evaluation of intelligent vehicles (IV) technologies, in a wide spectrum of applications and in different dimensions. It is expected to build upon a proper environment to disseminate knowledge and motivate interactions among the technical and scientific communities, practitioners and students, allowing state-of-the-art concepts and advances to be further developed and enhanced.

3. Eco-drive at Intersections with Connected,Cooperative and Automated Vehicle Technology

Today's road traffic systems are facing challenges in cutting down congestion and contributing to environmental sustainability. Especially the urban environment is suffering from congested traffic and an inherent high level of emissions. Eco—driving systems aim at assisting drivers for vehicle operations can help improve fuel economy and consequently reduce emissions. The potential of eco-drive strategies for coping with these issues can be enlarged if combined with cooperative and connected systems based on communication technologies. Along these opportunities come a few challenges for authorities, industry, as well as scientific community. In terms of system design and control, current eco-drive systems need to be refined or even redesigned to better function under uncertainties in demand and mixed traffic conditions and to better cooperate with traffic signal control systems. From the performance assessment perspective, traffic flow models and simulation tools have been widely used to verify the performance of eco-drive systems, in particular taking into account the increasing trends in vehicle connectivity and automation. However, the validity of these models needs to be re-examined against field tests.This workshop focuses on eco-drive systems using connected, cooperative and automated vehicle technology, applied in a road network with intersections. The main goal is to share the state of the art in design, models, algorithms, simulation and field test of eco-drive systems, identify challenges and research needs, and encourage cross-disciplinary cooperation.

4. Workshop on Modelling, Analysis and Control of Intelligent Mobility-on-Demand Systems

After decades of little innovation, personal urban mobility is undergoing rapid transformations due to the introduction of disruptive technologies (e.g. connected and driverless cars), new IT applications (e.g. appbased services) but also due to changes in individual preferences and social behaviours, with a growing trend towards a shifting from car ownership to sharing. This gave new life to several mobility on demand (MOD) services which were ideated decades ago but never established themselves as viable mobility solutions and created new variations of them, such as ride-sharing, bike-sharing programs, car-pooling and car-sharing services, on-demand bus and delivery services, etc. The rapid growth and the forecasted (large) scale of these new mobility services is expected to radically change individual travel patterns, and conventional frameworks for the modelling, analysis, simulation and control of transportation systems are not appropriate any more. For instance, novel demand modelling tools are needed for measuring, modelling and predicting behavioural choice and individual preferences for the new mobility solutions, as well as forecasting the level of market uptake of the different mobility services. Similarly, new analytical models and simulation frameworks are required to accurately characterise the peculiar properties of MOD systems. Then, the insights obtained may serve as basic input to advanced optimization frameworks, which can provide decision tools for the planning and optimal operation of such systems. Key issues to address are infrastructure planning, fleet sizing and management, supply rebalancing, and efficient cooperation with other transportation modes (e.g. public transport). The goal of this workshop session is to provide a forum to exchange ideas, discuss solutions, and share experiences from industry, researchers and the public sector. We solicit original papers covering different aspects of MOD systems,

5. Deep Learning for Autonomous Driving

Deep learning has been progressing rapidly and disseminated via conferences like NIPS and CVPR. This workshop is an attempt to bridge the gap between latest research in Deep Learning and application to autonomous driving which is an active area of research in both academia and industry. The first success of Deep Learning was mainly in visual perception via CNNs which has enabled applications like semantic segmentation which wasn't deemed possible before and expanding into classical geometric vision problems like Optical Flow and Structure from Motion. The other application areas like motion planning, sensor fusion, etc are in early stages of research. There is also the ambitious side of solving autonomous driving by a single deep learning model (end-to-end learning) and its variant of modular end-to-end with auxiliary losses for semantics. From a deployment perspective, processing power is still a bottleneck and there is steady increase of computational power where next generation platforms are targeting 10-100 TOPS

6. Artificial Transportation Systems and Simulation

The aim of the ATSS Workshop is to foster the discussion on issues concerning the development of Artificial Transportation Systems and Simulation as a means to devise, test and validate ITS-based technologies. With the ability to integrate different transportation models and solutions in a virtual environment, ATSS serve as an aid to support decisions made by engineers and practitioners in a controlled and safe manner. They also provide a natural ground where new approaches can be experimented while avoiding natural drawbacks of dealing directly with real critical domains, such as ITS. On the basis of theories and methodologies borrowed from a wide spectrum of disciplines, such as the Social Sciences, Cloud Computing, Artificial Intelligence and Multi-agent Systems, Virtual Reality and many others, many important issues arise which challenge and motivate researchers and practitioners from multidisciplinary fields, as well as different technical and scientific communities.

7. The Third International Workshop on Intelligent Public Transports -Toward the Next Generation of Urban Mobility

The technical areas include but are not limited to the following:

  • intelligent and real-time PT control and operational management;
  • public transportation planning and management using BigData;
  • mobility-based data analytics and machine learning applications;
  • different modes of PT and their interactions (road, rail,air and water-based);
  • artificial PT systems and simulation;
  • trajectory mining and related applications;
  • data-driven preventive maintenance policies;
  • analysis of smart card data and mobile phone data to improve public transport reliability;
  • distributed and ubiquitous public transport technologies and policies;
  • travel demand analysis and prediction;
  • advanced traveler information systems using homogeneous/heterogeneous data sources;
  • intelligent mobility models/policies for urban environments;
  • smart architectures for vehicle-to-vehicle/vehicle-toinfrastructure communications;
  • agent-based models of public transport systems;
  • complex network theory applications in public transport;
  • automatic assessment and/or evaluation on the PT reliability;

8. Behavioural Change Support Intelligent Transportation Applications

This workshop invites researchers and practitioners to participate in exploring behavioral change support intelligent transportation applications. We welcome submissions that explore intelligent transportation systems (ITS), which interact with travelers in order to persuade them or nudge them towards sustainable transportation behaviors and decisions. Emerging opportunities including the use of data and information generated by ITS and users' mobile devices in order to render personalized, contextualized and timely transport behavioral change interventions are in our focus. We invite submissions and ideas from domains of ITS including, but not limited to, multi modal journey planners, advanced traveler information systems and in-vehicle systems. The expected outcome will be a deeper understanding on the challenges and future research directions with respect to behavioral change support through ITS.

9. Transportation 5.0

With the fast development and application of sensing, computing, and networking technologies, social media, wearable and mobile devices have produced huge volumes of real-time social and physical signals for transportation systems. Transportation 5.0, an emerging field of transportation research and applications, is based on Cyber-Physical-Social Systems (CPSS). Transportation systems, as one of the most complex man-made systems, face a number of complicated and cost/time/space-critical tasks. The goal of this workshop is to encourage people to solve or address these tasks by introducing CPSS based ITS, which can make better use of the pervasive real-time social signals as well as the physical signals. The main idea is to apply the CPSS based ITS technologies to conduct traffic planning, assignment, navigation, management, control and transportation analytics with lower cost, higher accuracy, faster speed, more agility and full response. We hope this workshop can attract transportation researchers and practitioners to join us along this promising new direction in ITS.

10. International workshop on Large-Scale Traffic Modeling and Management

Over decades, traffic models and control strategies based on disaggregated traffic flow models, which track individual vehicle movements on a second or sub-second basis, have been proposed and applied for isolated intersections or coordinated intersections in arterial roads. In contrast, macroscopic network traffic modeling (MFD or NFD) aims at simplifying the complex task of urban network modeling where the collective traffic flow dynamics of subnetworks capture the main characteristics of traffic congestion propagation, such as the evolution of traffic states in different regions of the city. This approach also offers great opportunities to facilitate efficient large-scale control in congested networks, e.g. perimeter control. This workshop follows this research direction, and encourages the recent advances in traffic modeling and management of large-scale (multimodal) urban networks, addressing both theoretical and empirical aspects.