We are pleased to announce that the following Workshops integrate the Technical Program of ITSC 2016. Workshops will take place on November 1, 2016.

Workshop details:

WS01: “8th International Workshop on Planning, Perception and Navigation for Intelligent Vehicles – A bridge between Robotics and ITS technologies” (Website, PDF)

Workshop Code: 95vpj

Organizers: Christian Laugier (INRIA, France), Philippe Martinet (Ecole Centrale of Nantes, France), Urbano Nunes (Coimbra University, Portugal), Christoph Stiller (KIT, Germany)


Scope and Goals:

The purpose of this workshop is to discuss topics related to the challenging problems of autonomous navigation and of driving assistance in open and dynamic environments possibly populated by human beings. Technologies related to application fields such as unmanned outdoor vehicles or intelligent road vehicles will be considered from both the theoretical and technological point of views. Several research questions located on the cutting edge of the state of the art will be addressed. Among the many application areas that robotics is addressing, transportation of people and goods seem to be a domain that will dramatically benefit from intelligent automation. Fully automatic driving is emerging as the approach to dramatically improve efficiency while at the same time leading to the goal of zero fatalities. This workshop will address robotics technologies, which are at the very core of this major shift in the automobile paradigm. Technologies related to this area, such as autonomous outdoor vehicles, achievements, challenges and open questions would be presented and discussed.

Topics of Interest:

  • Perception: Lane detection & lane keeping, Feature extraction & selection, Pedestrian & vehicle detection, Moving objects Detection & Tracking, Objects classification, Real-time perception and sensor fusion, etc.
  • Road scene understanding: Environment perception & understanding, Vehicle localization for autonomous navigation, SLAM in dynamic environments, Mapping & Semantic maps for navigation, Robust sensor-based 3D reconstruction, Prediction techniques, etc.
  • Planning & Decision-making for navigation: Real-time motion planning in dynamic environments, Advanced driver assistance systems, Autonomous navigation, Cooperative navigation & perception techniques, Behavior modeling & learning, Modeling & Control of mobile robots and vehicles, Collision prediction & avoidance, Human-Robot Interaction, etc.

Program (November 1, 2016)

8:40-8:50 Workshop Opening
08:50-10:30 Session I: Perception & Situation Awareness

Keynote: On the Use of Maps for Automated Driving

Abstract: Vehicle automation is among the most fascinating trends in automotive electronics. We investigate the information needed by automated vehicles. The augmentation of sensor information by prior knowledge from digital maps is elaborated. We show that cognitive and autonomous vehicles with a few close-to-market sensors are feasible when prior information is available from maps. Vision plays the dominant role in our autonomous vehicle. We completely avoid bulky on-roof mounted sensors. The sensor suite enables the vehicle to perceive its environment and automatically navigate through everyday’s traffic. Automated mapping as well as real-time automated decision-making and trajectory planning methods are outlined. Extensive experiments are shown in real world scenarios from our AnnieWAY vehicle, the winner of the 2011 and second winner of the 2016 Grand Cooperative Driving Challenge, and from the Bertha vehicle that drove autonomously on the 104 km of the Bertha Benz memorial route from Mannheim to Pforzheim through a highly populated area of Germany.

Biography: Christoph Stiller studied Electrical Engineering towards Diploma degree in Aachen, Germany and Trondheim, Norway. In 1988 he became a Scientific Assistant at Aachen University of Technology. After completion of his Dr.-Ing. degree (Ph.D.) in 1994 he spent a PostDoc year at INRS in Montreal, Canada. In 1995 he joined the Corporate Research and Advanced Development of Robert Bosch GmbH, Hildesheim, Germany. In 2001 he became chaired professor at Karlsruhe Institute of Technology, Germany. In 2010 he spent three months by invitation at CSIRO in Brisbane, Australia. In 2015 he spent a four month sabbatical with Bosch RTC and Stanford University in California.

Dr. Stiller served as President of the IEEE Intelligent Transportation Systems Society (2012-2013) and was a Vice President before since 2006. He served as Editor-in-Chief of the IEEE Intelligent Transportation Systems Magazine (2009-2011) and as Associate Editor for the IEEE Transactions on Image processing (1999-2003), for the IEEE Transactions on Intelligent Transportation Systems (2004-2015), for the IEEE Intelligent Transportation Systems Magazine (2012-ongoing) and as Senior Editor for the IEEE Transactions on Intelligent Vehicles (2015-ongoing).

His Autonomous Vehicle AnnieWAY has been Finalist in the Urban Challenge 2007 in the USA, Winner of the Grand Cooperative Driving Challenge 2011, collaborated with Daimler on the automated Bertha-Benz-memorial-tour in 2013 and was second Winner of the Grand Cooperative Driving Challenge 2016 in the Netherlands.

C. Stiller

Increasing the Convergence Domain of RGB-D Direct Registration Methods for Vision-based Localization in Large Scale Environments
R. Martins, P. Rives
3D Object Tracking in Driving Environment: a short review and a benchmark dataset
P. Girão, A. Asvadi, P. Peixoto, U. Nunes
The Development of an Ontology for Context Modelling for Driving Context Modelling and Reasoning
Z. Xiong, V. Dixit, S. Travis Waller
10:30-11:00 Coffee Break
11:00-12:30 Session II: Mapping, Localization and Dynamic Scenes simulation

Keynote: Real Time Pedestrian Tracking, Prediction, and Navigation

Abstract: As autonomous robots and vehicles get widely deployed, one key challenge is to develop robust technologies that can automatically detect and safely navigate through moving pedestrians. While humans are naturally equipped to observe and predict the trajectories of other pedestrians and crowds, there are still many open challenges for current autonomous systems. In this talk, I give an overview of our work of developing novel algorithms and systems for automatic pedestrian identification, tracking, trajectory prediction, and safe navigation. We use a combination of off-line deep learning models and online pedestrian dynamics and combing them techniques from computer vision and physics-based simulation. We have evaluated their performance in sparse as well as dense pedestrians videos and observe considerable improvement in accuracy and performance. Our approach can perform all these computations in realtime in streaming videos and we highlighted their performance on real-world benchmarks as well as simulated scenarios.

Biography: Dinesh Manocha is currently the Phi Delta Theta/Mason Distinguished Professor of Computer Science at the University of North Carolina at Chapel Hill. He received his Ph.D. in Computer Science at the University of California at Berkeley 1992. Along with his students, Manocha has also received 14 best paper awards at the leading conferences. He has published more than 400 papers and some of the software systems related to collision detection, GPU-based algorithms and geometric computing developed by his group have been downloaded by more than 150,000 users and are widely used in the industry. He has supervised 30 Ph.D. dissertations and is a fellow of ACM, AAAS, and IEEE. He received Distinguished Alumni Award from Indian Institute of Technology, Delhi.

Dinesh Manocha

Occupancy Grid based Urban Localization Using Weighted Point Cloud
L. Guo, M. Yang, B. Wang, C. Wang
Cooperative Localization via DSRC and Multi-Sensor Multi-Target Track Association
A. Hamdi Sakr, G. Bansal
12:20-14:00 Lunch
14:00-15:40 Session III: Behaviors Modeling and Learning, Motion Prediction and Decision-Making

Keynote: Deep Learning for Robot Perception and Navigation

Abstract: Autonomous robots are faced with a series of learning problems to optimize their behavior. In this presentation I will describe recent approaches developed in my group based on deep learning architectures for perception and navigation. In particular, I will discuss approaches to object recognition, body part segmentation from RGB(-D) images, terrain classification, and mobile robot navigation. For all approaches I will describe the underlying network architectures as well as the required data augmentation techniques. I will present the results of expensive experiments quantifying in which way the corresponding algorithm extends the state of the art.

Biography: Wolfram Burgard is a professor for computer science at the University of Freiburg and head of the research lab for Autonomous Intelligent Systems. His areas of interest lie in artificial intelligence and mobile robots. His research mainly focuses on the development of robust and adaptive techniques for state estimation and control. Over the past years he and his group have developed a series of innovative probabilistic techniques for robot navigation and control.

He has published over 300 papers and articles in robotic and artificial intelligence conferences and journals. In 2009, Wolfram Burgard received the Gottfried Wilhelm Leibniz Prize, the most prestigious German research award. In 2010, he received an Advanced Grant of the European Research Council. He is fellow of the ECCAI, the AAAI, and the IEEE.

Wolfram Burgard

High-speed highway scene prediction based on driver models obtained from demonstrations
D. Sierra González, J. Steeve Dibangoye, C. Laugier
Functional Discretization of Space Using Gaussian Process for Road Intersection
M. Barbier, C. Laugier, J. Ibanez Guzman, O. Simonin
15:40-16:00 Coffee Break
16:00-17:40 Session IV: Planning and Navigation

Keynote: Sensor based Navigation

Abstract: It is known that 3D based autonomous navigation requires accurate and reliable maps and the use of accurate and robust localization techniques. 3D accurate sensors are costly and for some of them, doesnt insure the same reliability everywhere causing propagation of uncertainties. Sensor based mapping is based on the general technique of teaching by showing which is very well known in Visual servoing community. It doesn’t require strong assumption on global mapping as long as a topological level is used. Sensor based topological navigation is using a sensor based mapping technique in order to replay what have been learnt before. It allows to avoid all accumulation of errors (during mapping and/or global localization), and is using local measurements. We will illustrate some applications done in the field of autonomous navigation in inner cities.

Biography: Philippe Martinet graduated from the CUST, Clermont-Ferrand, France, in 1985, and received the Ph.D. degree in electronics science from the Blaise Pascal University, Clermont-Ferrand, France, in 1987. From 1990 until 2000, he was assistant Professor with CUST in the Electrical Engineering Department,Clermont-Ferrand. From 2000 until 2011, he has been a Professor with Institut Francais de Mécanique Avancée (IFMA), Clermont-Ferrand. In 2006, he spent one year as a visiting professor in ISRC at the Sungkyunkwan university in Suwon, South Korea. He was the leader of the group GRAVIR (over 74 persons) from 2001 till 2006. From 1997 until 2011, he led the Robotic and Autonomous Complex System team (over 20 persons). In September 2011, he moves to IRCCyN, Ecole Centrale de Nantes. His research interests include Robot Visual Servoing, Autonomous Guided Vehicle Control, Modeling/Identification and Control of complex MAChines, Redundancy Control and Autonomy of Humanoid, Active Vision and Sensor Integration, Visual Tracking, and Parallel Architecture for Visual Servoing Applications. From 1990, he is author and co-author of more than three hundred references. He is currently the coordinator of the Erasmus Mundus Master EMARO+. Since 2015, he is deputy director of the GdR Robotique. He is the corresponding chair of the RAS techinal Committee on AGV and ITS.

Philippe Martinet (Co-Authors: Gaetan Garcia, Salvador Dominguez Quijada and Olivier Kermorgant)

Optimal Trajectory Planning for Autonomous Driving Integrating Logical Constraints: a MIQP perspective
X. Qian, F. Altché, P. Bender, C. Stiller, A. de La Fortelle
Autonomous Personal Mobility Scooter for Multi-Class Mobility-on-Demand Service
H. Andersen, Y. Hong Eng, W.K. Leong, C. Zhang, H.X. Kong, S. Pendleton, M. H. Ang Jr., D. Rus
Autonomous parking using a sensor based approach
D. Pérez-Morales, S. Dominguez Quijada, O. Kermorgant, P. Martine
17:40-17:50 Closing

WS02: “6th International Workshop on Artificial Transportation Systems and Simulation” (Website, PDF)

Workshop Code: g7r1q

Organizers: Alberto Fernandez (URJC, Spain), Fenghua Zhu (CAS, China), Shuming Tang (CAS, China)


Scope and Goals:

The Workshop on Artificial Transportation Systems and Simulation (ATSS) is part of a series of workshops and special sessions promoted by IEEE ITS Society’s ATSS Technical Activities Sub-Committee. The 2016’s Edition of the ATSS Workshop is the 6th in the series, following the successful previous editions held in Shanghai (2004), in Toronto (2006), in Beijing (2008), in Madeira (2010), and in Qingdao (2014). Therefore, the ATSS Workshop series has been established as an event of reference held regularly at IEEE ITS Conferences. We are confident this year’s edition will be as successful as the previous ones. Alternately, also being offered regularly, the Special Sessions on ATSS have also been organised at IEEE ITS Conferences. Whereas workshops aim primarily at discussing in an informal environment trends, work in progress and new ideas related to Artificial Transportation Systems and Simulation, Special Sessions are intended to be focused on specific developments and topics or problems within the field, based on sound results or projects already in an advanced stage of development.
The aim of the ATSS Workshop series 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, Distributed Computing, Artificial Intelligence and Multi-agent Systems, Virtual Reality and many others, many important issues arise which challenge and motivate many researchers and practitioners from multidisciplinary fields, as well as different technical and scientific communities.

Topics of Interest:

  • Agent-based modelling and social simulation in MAS-T (multi-agent systems applied to traffic and transportation)
  • Real-world agent architectures
  • Hardware-, software-, and human-in-the-loop simulation
  • Agent-human interactions
  • Environment modelling and interaction protocols
  • Learning and adaptation, collaboration, cooperation, competition, coalitions in traffic and transportation models
  • Multi-resolution simulation, simulator interoperability, simulation as a service, cloud-based simulation
  • Growing artificial societies in artificial transportation systems
  • Large scale simulation, calibration and validation of agent-based models for traffic and transportation
  • New trends and inspirational metaphors for artificial transportation systems

Program (November 1, 2016)

9:00-9:10 Workshop Opening
9:10-10:30 Session I
A Framework of Future Innovative Urban Transport
Xisong Dong, Bin Hu, Gang Xiong, Jukka Pekka Riekki, Fei-Yue Wang, Fenghua Zhu
An Erlang-Based Simulation Approach of Artificial Transportation Systems
Songhang Chen, Fenghua Zhu, Fei-Yue Wang
Agent-Based Model of Highway Traffic: Reduction in Driving Efficiency with Density
Prafull Kasture, Hidekazu Nishimura
10:30-11:00 Coffee Break
11:00 -12:30 Session II
Framework for vehicles to join or leave the vehicle formation
Fanshou Zhang, Shuming Tang
Distributed Simulation Platform for C-ADAS Testing and Validation
Ines Ben Jemaa, Dominique Gruyer, Sébastien Glaser
Multivariate Modelling for Autonomous Vehicles
Lígia Conceição, Rosaldo Rossetti
12:30-14:00 Lunch
14:00-15:30 Session III
Autonomous Vehicle Testing Methods Review
Huang, Kunfeng Wang, Yisheng Lv, Fenghua Zhu
Mining Social Media for Open Innovation in Transportation Systems
Daniela Ulloa, Pedro Saleiro, Rosaldo Rossetti, Elis Silva
Simulative Scenario Analysis with respect to Urban Speed-Volume Relationship Implementing Data from Automatic Number Plate Recognition
Gundolf Jakob, Fritz Busch
15:30-15:40 Workshop Closing

WS03: “2nd International Workshop on Intelligent Public Transports – Toward the Next Generation of Urban Mobility” (Website, PDF)

Workshop Code: n31c3

Organizers: Luís Moreira-Matias (NEC Laboratories Europe, Germany), Oded Cats (TU Delft, The Netherlands), Daqing Zhang (Institut TELECOM & Maga, France)


Scope and Goals:

Nowadays, everything is being built up taking advantage in sensor’s data (e.g.: bridges, computers, houses, vehicles). The Public Transport is not an exception. By being highly dependent on the dynamics of the human behavior (both drivers and passengers), it is intrinsically connected to the data derived from them as well. In the past, this was completely unrealistic. The Data Miners worked closed on their labs with their impractical Machine Learning algorithms – as there was no large-scale data to apply them. On the other hand, the Civil Engineers aimed to model such dynamics assuming theoretical levels of stochasticity and/or optimistic scenarios. Such models comprise a fair but still inaccurate approach to such dynamic behavior. Today’s reality increased dramatically the availability of the mobility-based data by the multiple social infrastructures that already use intelligent sensors and real-time communicational frameworks (e.g. 3G).
The availability of these types of data (e.g. smartphones, traffic light sensors, APC/AVL, fare-based, etc.) on a largescale changed the way both Civil and Computer Scientists faced the problematics around Public Transportation. It enables a whole new bunch of possibilities which are still far by being fully explored. On the other hand, it also brings novel issues regarding each individual’s and/or company’s privacy that are worthy to be discussed and analyzed. Where are we going? Where do we want to go? Which are the current trends? How can we explore these data to improve Public Transportation? What can be done to improve bus transfers coordination? How about the taxi dispatching, preventive maintenance, planning and control of public transportation in general?
These problematics are addressed by this workshop’s scope (introduced below). The researchers/engineers are encouraged to participate and take advantage of this opportunity to exchange ideas and to share their R&D findings/experiences.

Topics of Interest:

  • Intelligent and real-time public transport control and operational management (bus bunching, transfer coordination, corrective actions);
  • Public transportation planning and management (route definition, schedule planning, duties definition and/or assignment) using Big Data;
  • Mobility-based data analytics and machine learning applications;
  • Different modes of public transport and their interactions (road, rail, air and water-based);
  • 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 and policies for urban environments;
  • Complex network theory applications in public transport;
  • Automatic assessment and/or evaluation on the public transport reliability (planning, control and other related policies).

Program (November 1, 2016)

9:00-9:05 Opening Session
09:05-10:40 Session I – Behavior Modelling

Keynote: Use of smartcard data to improve our knowledge of travel behavior: applications to the case of Santiago, Chile

Abstract: The introduction of a new public transport system in Santiago, Chile, in 2007 brought to us an unexpected gift: the availability of what we now call BIG DATA; massive amounts of passive data obtained from the technological devices installed to control the operation of buses and to administer the fare collection process. Like Santiago and London, many other cities in the world have been experiencing the same, and sooner or later, this is likely to happen everywhere. Many researchers have seen this as an opportunity, and have developed tools to obtain valuable information from the available data. However, the case of Transantiago is particularly advantageous, because the penetration rate of the smartcard (bip!) is 97% (it is the only payment option available at buses, and by far the most popular in Metro). Also, all buses are equipped with GPS devices that sends a position signal every 30s. This presentation will include a brief description of the Transantiago public transport system, a description of the methods we have developed to obtain valuable information from the data available: public transport trips origin-destination matrices, speed profiles of buses, service quality indicators, time use patterns. The presentation will conclude with the presentation of some travel behaviour models, and a discussion of the implications of the availability of massive data on travel behaviour modelling and planning.

Biography: Associate Professor at Universidad de Chile. Specialist on transport demand modeling, predictive models and microeconomic analysis applied to private and public transport. In the last few years has leaded research on smartcard data and developed applications to obtain valuable information from automatically generated databases, which have been transferred to practice and used for planning purposes. Associate Researcher of the Complex Engineering Systems Institute ISCI, in charge of the Smartcities research group. Adjoint researcher at the Center for Climate and Resilience Research (CR)2. Co-Chair of the International Steering Committee for Transport Survey Conferences ISCTSC.

Marcela Munizaga

Normative optimal strategies: a new approach in advanced transit trip planning
Agostino Nuzzolo, Antonio Comi, Luca Rosati

Mobility characterization for user recognition in public transportation

Abstract: Characterization of users mobility has become an accessible challenge due to new data collecting systems, such as smart cards and mobile devices. In transportation systems, having long periods of users mobility recorded can be very useful as it provides a wider and less biased sample for Time series analysis. However, due to high renovation rates of smart cards, it is not always possible to collect users mobility for long periods of time. To mitigate this problem, we study the possibility of matching smart cards that belong to the same user by measuring the similarity of the movement recorded. We implement three methods for recognizing users by comparing their mobility in two different time periods. We evaluated the performance of these methods using two weeks of smart cards transactions from a public transportation system. Our preliminary results showed that, by different approaches, a significant amount of users can be recognized. The method with the best performance recognizes around 70% of users.

Biography: Student in a dual degree program of Computer Engineering and Master in Computer Science at Universidad de Chile. Her interests include data mining and massive data processing combined with software development in different applications. Currently she is working on mobility characterization as her research thesis and developing an application for public transport users.

Catalina Espinoza

10:40-11:00 Coffee Break
11:00 -12:15 Session II – New Technologies in Transport
Towards Integrating Electric Buses in Conventional Bus Fleets
Diogo Santos, Zafeiris Kokkinogenis, Jorge Freire de Sousa, Deborah Perrotta, Rosaldo Rossetti
Partial Speed Trajectory Optimization for Urban Rail Vehicles with Considerations on Motor Efficiency
Shaofeng Lu, Jie Yang, Fei Xue, Tiew On Ting
Real-Time Bus Holding Control on a Transit Corridor Based on Multi-Agent Reinforcement Learning 
Weiya Chen, Chunxiao Chen
12:15-14:00 Lunch
14:00-15:30 Session III – Transit Planning

Keynote: Route choice in public transport networks: choice set generation and route choice models

Abstract: Public transport assignment or simulation procedures for transit network require some behavioral assumptions regarding the passenger’s route selection. An inter-related problem is the generation of alternative routes, which takes into account the complexity of the different trip legs. These trip legs generally comprise walking to or from the station, waiting, riding transit lines and transferring between them. People have different time perceptions of these components, which may be captured by different model structures.

This lecture will present an overview of different choice set generation approaches, focusing on methods that can be applied for real-size networks. The second part of the lecture will discuss transit route choice models in the assignment and simulation contexts. In particular, the lecture will address models that can accommodate the possibility of new information and communication technologies available both to the users and to the operators.

Biography: Shlomo Bekhor holds a B.Sc. in Aeronautical Engineering from the Aeronautical Institute of Engineering, Sao Jose dos Campos, Brazil, and M.Sc. and Ph.D in Transportation Engineering at the Technion. He was a Research Affiliate (Post-Doc) in the Intelligent Transport Systems Laboratory at the MIT in 2000-2001. After the Post-Doc he joined the Department of Transportation and Geo-Information Engineering at the Faculty of Civil and Environmental Engineering at the Technion and is Associate Professor since 2008. He was the Head of the Transportation Research Institute between 2010 and 2015.

He teaches and conducts research in transportation planning, discrete choice and network equilibrium models. He has published more than 70 papers in peer-reviewed journals and has presented more than 80 papers at international conferences. He is currently the Chairman of the Israeli Association of Transportation Research and was a member of the Transportation Demand Forecasting Committee at the Transportation Research Board (USA) between 2006 and 2014.

Shlomo is specialized in transportation planning and network optimization in general and in demand modelling and behavioural models in particular. Academic achievements are the development of new behavioural route choice models and traffic assignment models. He was Principal Investigator of several large-scale research projects funded by the Israel Ministry of Transport and the Israel Science Foundation, and has actively participated in the European Commission funded projects CyberCars, CyberMove, CitiMobil, and 2MOVE2 within the Civitas framework.

Shlomo Bekhor

Challenging user interaction in public transportation Spider Maps: a Cobweb solution for the city of Porto
Francisco Maciel, Teresa Galvao
A Frequency Based Transit Assignment Model That Considers Online Information at the Boarding Stop
Nurit Oliker, Shlomo Bekhor
15:30-16:00 Coffee Break
16:00-17:40 Session IV – Predictive Analytics and Optimization
Mining Taxi Data for Describing City in the Context of Mobility, Sociality, and Environment: Lessons Learned
Marco Veloso, Santi Phithakkitnukoon, Carlos Bento
A Multi-Level Clustering Approach for Forecasting Taxi Travel Demand
Neema Davi, Gaurav Raina, Krishna Jagannathan
Exploring Pedestrian Bluetooth and WiFi Detection at Public Transportation Terminals
Neveen Shlayan, Abdullah Kurkcu, Kaan Ozbay
A solution to the road network design problem for multimodal flow
Bagloee Saeed, Majid Sarvi, Rajabifard Abbas, Thompson Russell
17:40-17:45 Closing Session

WS05: “International Workshop on Advanced perception, Machine learning and Data sets” (Website)

Workshop Code: yd86m

Organizers: Patrick Shinzato (University of Sao Paulo, Brazil), Cristiano Premebida (Institute for Systems and Robotics, Portugal), Jose Eugenio Naranjo (Universidad Politecnica de Madrid, Spain), Brendan Morris (University of Nevada, USA)


Scope and Goals:

The aim of this workshop is to bring together researchers to discuss current and future challenges of advanced/intelligent sensor-based perception systems for intelligent vehicles and ADAS applications, so as to share their experience in current and new challenges in the various topics of advanced perception.
The AMD’16 Workshop welcomes contributions reporting on original research, work under development and experiments of different fields related to perception systems for intelligent vehicles and ADAS applications. We strongly encourage authors to make their datasets available to the community. In order to stimulate and facilitate the comparison of different algorithms, evaluation scripts and ground truth are also welcome.

Topics of Interest:

  • Machine Learning and intelligent algorithms applied to perception system
  • Multimodal sensor datasets (Mono and Stereo Vision, LIDAR, Radar, GPS, IMU) and evaluation metrics
  • VRU and vehicle detection
  • Environment modeling
  • Road and signal detection
  • Sensor fusion and cooperative perception

Program (November 1, 2016)

09:00-10:30 Session I

Keynote: Autonomous Driving with the Drive Me Project

Abstract: Autonomous driving (AD) is about providing a part of the answer to the needs and challenges that we are facing on, e.g., reducing the number of casualties and improving the traffic flow. Moreover, AD can play an important role for a sustainable mobility and can save lots of time that is lost in queues every day. Automakers realize that this type of technology will be highly in demand in the future and are therefore spending a lot of research on its development. Volvo Cars Drive Me Project is a research platform in which we investigate how autonomous cars can contribute to a sustainable development, where we look into different aspects from technology and infrastructure to legal and customer expectations. Machine learning plays an important role not only in the development of solutions for AD but also in designing efficient verification processes. After introducing the Drive Me project, we will discuss some AD related challenges, for which machine learning could provide a good solution.

Biography: Nasser Mohammadiha is a senior analysis engineer at the Volvo Car Corporation, Sweden, where he is working on machine learning for active safety and autonomous driving and verification of such systems. He is also leading an advanced engineering project on big data analysis. He received the M.Sc. degree in Electrical Engineering from the Sharif University of Technology, Iran, in 2006, and the Ph.D. degree in Electrical Engineering from the KTH Royal Institute of Technology, Sweden, in 2013. He was a Postdoctoral Fellow at the University of Oldenburg, Germany from 2013 until 2015, after which he joined Volvo. He is the author of more than 45 patents and peer-reviewed papers, and he received the Best Student Paper Award at the European Signal Processing Conference in 2013. His research interests include big data analysis, machine learning, and audio and image processing. He has been a reviewer of numerous international conferences and journals, such as IEEE Trans. on Signal Processing, IEEE Trans. on Audio, Speech and Language Processing, and IEEE Trans. on Neural Networks and Learning Systems.

Dr. Nasser Mohammadiha, Volvo Cars, Sweden

CaRINA Dataset: An Emerging-Country Urban Scenario Benchmark for Road Detection Systems
P. Shinzato, T. C. Santos, L. A. Rosero, T. Watanabe, D. A. Ridel, C. A. Massera Filho, F. R. de Alencar, A. Hata, M. Batista, F. Osorio, D. Wolf
An Approach to Traffic Analysis over Intersections
Gustavo Lira, Daniel Moura, Rosaldo Rossetti
10:30-11:00 Coffee Break
11:00-12:30 Session II
Offline Object Matching and Evaluation Process for Autonomous Driving Verification
Johan Florbäck, Lars Tornberg, Nasser Mohammadiha
Multi-Drive Road Map Generation on Standardized High-Velocity Roads Using Low-Cost Sensor Data
Maximilian Naumann, André-Marcel Hellmund
Automatic Calibration of Low Cost Inertial Gyroscopes with a PTU
Jaime Delgado, Pedro R. de Mello Silva, César H. C. Quiroz, Paulo Kurka
Towards Intra-Vehicular Sensor Data Fusion
Paulo Henrique L. Rettore, Bruno P. Santos, André B. Campolina, Leandro A. Villas, Antonio A. F. Loureiro
12:30-12:35 Workshop Closing

WS06: “International Workshop on Simulation of Intelligent Industrial Transportation and Logistics Systems” (Website, PDF)

Workshop Code: 4ei61

Organizers: Luís Dias, Guilherme Pereira, António Vieira (U. Minho, Portugal), António Brito, C. Bragança de Oliveira (FEUP, Portugal), Ana Luísa Ramos (U. Aveiro, Portugal)

E-mails: {lsd, gui, antonio.vieira}, {acbrito, braganca},

Scope and Goals:

Organizations are continuously trying to improve their competitiveness in several fields, which can be seen in the current context of the industry 4.0. The goods transportation inside and outside companies represents a significant fraction of the total costs. It is a transversal problem to most business organizations.
One of such problems is related to internal logistics, which is crucial for the performance of companies. In fact, an accurate and efficient internal logistics system is vital to ensure that the right materials are receipt on the right time and place and in the right quantities. This is a problem that comprises several thematic, such as intelligent transportations. Its advancements can result from electro-mechanical physical devices (e.g. AGV – Automated Guided Vehicles), or conceptual logistics systems, such as milk runs (mizusumashi) and Kanban systems. Intermediate warehouses often support supply chains.
Simulation is one of the techniques that are being applied in many situations in this fourth industrial revolution, addressing problems related to transportation of goods (or even people). It can also be complemented with optimization techniques. Therefore, this workshop will cover transportation issues related to logistics and will foster active discussion on topics related to the field.

Topics of Interest:

  • Industrial Transportation
  • Logistics
  • Internal Logistics (e.g. AGVs, Milk Runs, Conveyors, Kanban)
  • Supply Chain
  • Optimization
  • Intelligent Warehouses – storing and picking
  • Internet of things, on the move (industry 4.0)
  • Modelling and Simulation

Program (November 1, 2016)

9:00-09:30 Opening Session
9:30-10:30 Session I (Chair: Carlos Bragança)
A Review of Intelligent Transportation Systems from a Communications Technology Perspective
Athanasios Maimaris, George Papageorgiou
Dynamic Inductive Power Transfer Lane Design for e-Bikes
L. A. Lisboa Cardoso, M. Comesaña Martinez, A. A. Nogueiras Meléndez João L. Afonso
10:30-11:00 Coffee Break
11:00 -12:30 Session II (Chair: António Brito)
Long Short-Term Memory Model for Traffic Congestion Prediction with Online Open Data
Yuan-yuan Chen, Yisheng Lv, Zhenjiang Li, Fei-Yue Wang
Application of Monte Carlo Simulation As a Tool for Capacity Planning Strategy in a Multi-Level Global Supply Chain Focused to Reduce the Bullwhip Effect
Rodrigo Koch, Ricardo Cassel, Michel Anzanello
Incorporating Economic Issues in the Design of Sustainable DRT Systems: Insights from the Case of a Portuguese Municipality
Paulo Afonso, Jose Telhada, Maria Carvalho
12:30-14:00 Lunch
14:00-15:30 Session III (Chair: Luís Dias)
Round Table: Designing Futures with APBS (The Portuguese and Brasilian Association of Simulation)
António Brito

Invited Talk: Wireless Technologies and Augmented Reality in Tracking Logistics Processes, Inspection, Maintenance and Real-time Control

Abstract: The presentation will address the aspects of infrastructure and functionality of IoT, convergence with the Industry 4.0, mobile computing, applications and their impact on logistics processes, inspection and maintenance. Cases applications will be presented in 3 major companies in the oil sector, rail and hydroelectric generation. Finally, it presents a vision backed by the technological evolution projections currently accepted in academia and research.

Biography: Civil engineer with a doctorate in High Performance Computing language for Virtual Systems. Coordinator / Founder Virtual Reality Group and Augmented from COPPE / UFRJ since 1997, technical coordinator of the Brazilian Network View UFRJ, technical coordinator of the Computer Network and Visualisation Petrobras UFRJ develops discilpinas research and teaches master’s and doctorate in COPPE / UFRJ in the areas of Tracking and Location Real Time, Computer Vision, Image Processing, Virtual and Augmented reality and Simulation Systems. It operates more than 25 years developing and transferring technology to the industry in the exploration and production of oil, mining, hydroelectric and nuclear generation, construction, health and cultural projects.

Gerson Cunha, Federal University of Rio de Janeiro, Brazil

PID Control Applied on a Line-Follower AGV Using a RGB Camera
Malcoln V. Gomes, Kelen C. T. Vivaldini, Luis A. Bássora, Antônio, Orides Morandin Jr
15:30-16:00 Coffee Break
16:00-18:00 Session IV (Chair: Guilherme Pereira)
Simulation and Economic Analysis of an AGV System As a Mean of Transport of Warehouse Waste in an Automotive OEM
Tomé Silva, Luís Dias, Manuel L Nunes, Guilherme Pereira, Paulo Sampaio, José Oliveira
An Exploratory Study of Taxi Sharing Schemas
Elis Silva, Zafeiris Kokkinogenis, Álvaro Câmara, João Ulisses, Joana Urbano, Daniel C. Silva, Eugénio Oliveira, Rosaldo Rossetti
An Automated Warehouse Design Validation Using Discrete Simulation
Robson T. Peixoto, Luís Dias, Maria S. Carvalho, Guilherme Pereira, Carla A. S. Geraldes
A Micro-Simulation Model for Assessing the Performance of Airport Check-In Area
Manuel Félix, Vasco Reis
18:00 Closing Session

WS08: “Workshop on Intelligent Transportation Systems in Operation in Rio de Janeiro”

Organizers: Paulo Cezar Ribeiro (PET-COPPE, UFRJ, Brazil)


Scope and Goals:

This workshop is dedicated to present some ITS solutions currently in use in Rio de Janeiro, and discuss trends and opportunities for the ITS Industry, Practitioners, and Stakeholders. Delegates from the industry and practitioners will be invited to present the systems in use that have been successfully deployed to increase efficiency of transportation in the city of Rio de Janeiro, in the first part of the workshop, whereas other solutions will be discussed by other invited guests during the second part of the workshop. In the end, organizers will reserve some time for a roundtable and open discussion.

Program (November 1, 2016)

14:00-15:30 Session I: Invited panellists
Serio Viana, Operations Manager, Engebras (30 min.)
Augusto Schein, Operations and Maintenance Director, VLT Rio (30 min.)
Paulo Cezar Ribeiro, General Director, Forum Brasileiro de ITS – FORBITS (30 min.)
15:30-16:00 Coffee Break
16:00-18:00 Session II: Invited panellists
Chequer Jabour Chequer, Director, ITS Brasil (25 min.)
Carlos Costa, CEO, Armis-ITS, Portugal (25 min.)
Roberto Esquinazi, CEO, Trafeg Ltda (25 min.)
Cezar Vasconcelos, CEO, NewsGPS (25 min.)
Alessandro Santiago dos Santos, Research Manager, IPT (20 min.)
Round Table