LEVITATE in TRB annual meeting 2020

Perhaps the biggest transportation research conference in the world – TRB – took place this year from the 11th to 16th of January 2020. LEVITATE could not be missing from this prestigious event, and this year, the project was represented by several members: Dr Alkis Papadoulis, Prof Pete Thomas and Prof Mohammed Quddus from Loughborough University, Dr Jordi Casas from Aimsun and Prof Eleni Vlahogianni from National Technical University of Athens. As expected, Connected and Automated Transport Systems were one of the themes that dominated the agenda of the conference as they have been the research focus of industry and academia for the last few years.

TRB is always an excellent opportunity for European and International projects to interact with each other and attempt to learn from each other’s research. The members of LEVITATE, attended lectern sessions where several CATS-related projects were presented (Co-Exist, HumanDrive among others), and the following conclusions were drawn.

  1. Connected and Automated Driving data are starting to emerge. Microsimulation software companies are starting to develop their “autonomous” vehicle algorithms based on this data and several studies are starting to employ these models in order to evaluate the impact of Connected and Automated Vehicles in simple road network layouts. These studies could potentially be very useful for Levitate, as they can provide a basis of comparison for the results of Levitate and they can provide useful guidelines regarding the configuration of driving models in order to simulate connectivity and automation.
  2. The definition of Connected and Automated Vehicles in simulation terms hasCa not advanced significantly during the last few years. This is where Levitate will aim to contribute by defining new CAV behaviours that will emerge due to the sub-use cases so cities can evaluate them in the Policy support tool.
  3. The transferability of results is still an on-going and sensitive topic for simulation-related projects as simulation models are location specific and models must be individually tailored for each different city of interest.

Additionally, LEVITATE’s most recent piece of simulation work on parking pricing policies in the Connected and Automated Vehicle era was presented in the Freeway and CAV Simulation subcommittee. The session was well attended from experts of the field and the members of the project received very useful feedback that will help strengthen the sub-use case work in the future.

The project is looking forward to attending more meetings in Europe and worldwide in order to exchange opinions and thoughts about its methods and assumptions.

Advances in Connected and Autonomous Mobility – IEEE ITSC 2020

The 2020 annual flagship conference of the IEEE Intelligent Transportation Systems Society will be held in Rhodes, Greece in September. LEVITATE will contribute to this conference with a special session: Advances in Connected and Autonomous Mobility: From Data to Models, Impacts and Enablers for Adoption.

Recent breakthroughs in technology, digital infrastructure, dynamic mapping and big data computing will transform the way we will plan, undertake, interact, make decisions and use our built environment and transportation infrastructure for the movement of people and goods. Connected and Autonomous Mobility (CAM), enabled by vehicle connectivity and automation, cloud computing, artificial intelligence and Internet of Things (IoT), allows unprecedented capability to collect, exchange and analyze large volumes of data to formulate models and tools for optimal decision making at individual, local and city levels and will, therefore, increasingly be revolutionized our economy and society over the next decade. However, to what extent they will disrupt mobility and transport operations is still a subject of research. CAM services are expected to emerge in various forms affecting different user groups and imposing network-level changes on various urban scales. To this end, understanding public acceptance and the levels of adoption (and respective timing) of emerging technologies, devising novel approaches and modeling tools to replicate mixed and CAV (Connected and Autonomous Vehicles) traffic in large-scale urban networks for impact assessment and identifying large-scale procedures and policies for CAV traffic management are the key factors for successful deployment of CAM services.

This special session aims at:

  1. providing the audience with information about the deployment of state-of-the-art vehicular and transportation technologies to CAM in a smart city context;
  2. discussing the latest advancements, existing data, conceptual and modeling hurdles and challenges in both research and practice (particularly on the selected topics below)
  3. identifying potential research gaps and collaboration opportunities between industry and academia.