Newsletter #3 November 2021

EDITORIAL

In this 3rd Drive2theFuture Newsletter we are pleased to present you with news of the project within 2021 so far. Important results have occurred in this period and already presented various in papers and conferences. The 2nd Project Workshop took place in March 2021, with great participation and very interesting keynote speeches and panel discussion, along with the presentation of recent project achievements. Moreover, Drive2theFuture preliminary results on user acceptance were presented during a very successful lunchtime session, organised by CINEA in September 2021, together with the other cluster projects. As we are approaching to the final stages of the project work, interesting results are coming up and all tasks are in full activity, aiming to the smooth and successful achievement of the project scope and, thus contributing to the future of CCAM deployment. Stay tuned through our social media to keep up to date with our progress!

Drive2theFuture in the CINEA lunchtime session “Do we trust self-driving cars? - Social acceptance of autonomous mobility”

CINEA organised on the 9th September 2021 a lunchtime session, entitled “Do we trust self-driving cars? - Social acceptance of autonomous mobility”. The aim of the session was to give an overview about Connected, Cooperative and Automated Mobility (CCAM), its objectives and overall landscape, learn about driver behaviour and social acceptance of CCAM in Europe and get insights from the Horizon 2020 cluster of ongoing research projects focused on driver behaviour and social acceptance towards deployment of CCAM infrastructure and seamless services.
Drive2theFuture was one of the invited projects, represented by its Coordinator Ms E. Gaitanidou and its Technical and Innovation Manager Dr. E. Bekiaris (CERTH/HIT). The event received great attention and congratulations from the CINEA and DGs (MOVE, RTD and CONNECT) high level participants.

The 2nd Drive2theFuture Workshop 12th of March

The 2nd Drive2theFuture Workshop was held online on the 12th March 2021, with over 70 participants, representing related stakeholders in the area as well as the three sister projects (PAsCAL, SUaaVE and Trustonomy).
Four invited presentations were given by Gina Baas (Associate Director, Engagement & Education, Center for Transportation Studies, University of Minnesota) on the “Connected and Automated -Vehicle Workforce and Engagement Initiatives”, Zachary Doerzaph (Director, Division of Driver, Vehicle, & System Safety, VTTI) on the ”Overview of VTTI activities related to Drive2theFuture topics”, Ingrid Skogsmo (BRAVE project Coordinator, VTI) on “BRAVE – BRidging gaps in Adoption of automated Vehicles” and Henriette Cornet (SHOW project Coordinator, UITP) on “SHOW Large-scale demonstration of AV fleets – First insights of user expectations”.
Moreover, project results were outlined, regarding the Drive2theFuture surveys (Voice of Customers, Drones acceptance and Drivers’ trainers), the identification of skills and relevant training, as well as demos and testing in Drive2theFuture.
A panel discussion session was also held on “Ethical, security, safety and legal dilemmas: Are they impacting the acceptance of autonomous vehicles?”, with the participation of outstanding panelists (namely, Rune Elvik – TØI, Annie Pauzié - University Gustave Eiffel, Niels Kristensen – TØI, Simon Parkinson – University of Huddersfield, Erich Stadler - Wiener Linien, Jo-Ann Pattinson – PAsCAL project, Ebru Dogan – SUaaVE project, David Rios – Trustonomy project).

Finally, the Drive2theFuture Technical and Innovation Manager, Dr. E. Bekiaris, summarizing the findings of the 2nd project Workshop, underlined that we are at the break of a new era of automation in all transportation modes; at the beginning of an evolution that is, actually, a revolution!

Drive2theFuture in the EUCAD 2021 “Connected and Automated driving” (20-22 April 2021, Online)

Drive2theFuture was invited to participate in the EUCAD 2021 Virtual Conference on “Connected and Automated Driving” which was held on the 20-22 April 2021. The project had its own virtual stand in the online exhibition of the Conference, presenting demos and videos of the project activities, such as Real road testing of automated cars in Poland; Safety around self-driving buses in Linköping, Sweden; Interaction between passengers and automated buses at bus transit points, Interaction between bus drivers and automated buses at bus transit points and Interaction with a highly automated car on the highway in Virtual Reality along with downloadable content (leaflet, poster, newsletters).

All videos are available on the Drive2theFuture YouTube channel

Drive2the Future in the “Challenges & Lessons Learned in CCAM” Workshop in 10th ICTR Conference (1-3 September 2021, Rhodes, Greece)

Within the framework of the 10th ICTR International Congress on Transportation Research that took place on 1-3 September in Rhodes, Greece, a Workshop with title “Challenges & Lessons Learned in CCAM” took place, organized by SHOW Innovation Action and in specific by the Technical Management team of HIT/CERTH. 12 presentations were made during the workshop, originated from SPACE, SHOW, AVENUE, WISE-ACT, Drive2theFuture, Trustonomy, SUaaVE, ICT4CART, EIMANTRA, LEVITATE, SPROUT and ARCADE initiatives as well as from CCAM Platform WG3.

Drive2theFuture was represented by its coordinator Ms Evangelia Gaitanidou, presenting an overview of the project activities and first results, entitled “Towards an automated mobility future: the Drive2theFuture user-centered approach”.

Societal impact assessment of autonomous vehicle scenarios using multi-actor multi-criteria analysis – paper presented at the ICTR conference (1-3 September 2021, Rhodes, Greece)

During the International Congress on Transportation Research (ICTR2021) the Vrije Universiteit Brussel (VUB-MOBI) presented the results from 4 European interactive online stakeholder workshops. The stakeholders were represented by a total of 63 experts from the mobility and logistics sector. During the workshops the stakeholders were asked to reflect on the potential societal impacts of autonomous vehicles and services. Multi-Actor Multi-Criteria Analysis (MAMCA) was used to capture the stakeholders’ evaluation in terms of different criteria for each stakeholder group. From the workshops that looked at relevant scenarios for the mobility sector, we learned that ‘first/last mile feeders’ and ‘automated mass rapid transit’ are consistently among the highest performing scenarios across all stakeholders. These scenarios are closely followed by the ‘automated ride sharing’ scenario. However, Local Authorities and Manufacturers are more prudent when it comes to this service’s expected positive impact. Lastly, Public Transport Operators and Mobility Service Providers expect that the two private car scenarios, automated vehicles and connected and cooperative vehicles, will bring higher positive impacts than ‘business as usual’. This is, however, not the case according to Users, Local Authorities and Manufacturers

Development of affective, trusted, personalized and persuasive HMIs for Automated Vehicles

A crucial role for user acceptance is played by the Human-Machine-Interface (HMI), which gives the user the possibility to interact with an automated system or receive information about its current state. In Drive2theFuture, we investigate the optimal HMI for the different modes and user clusters, such as operators, drivers, riders, passengers, vulnerable road users (VRU) and traffic managers. Based on an extensive literature review and expert evaluation, different cross-modal recommendations for an affective, persuasive and trusted HMI were identified and applied to HMI concepts developed in Drive2theFuture. These are demonstrated and iteratively tested with users within the pilot sites in different European countries. For example, Fraunhofer IAO uses Virtual Reality to develop and investigate an in-vehicle HMI for highly automated road vehicles with intuitive steering.

A video of the HMI concept can be found here: VIDEO

National Technical University of Athens analyzed real time human driving data collected via drones

Within the framework Drive2theFuture, National Technical University of Athens analyzed real time human driving data collected via drones for extracting driving behavior profiles that automated vehicles should adopt for ensuring safety and increased user acceptance. More specifically, a reinforcement learning algorithm was developed that can be used inside cars as a drivers’ assistance system that based on the traffic conditions around the ego vehicle, will be able to identify the best action in each timestep. Based on the distance between the examined vehicle and the vehicles around it (front, back, left, right), as well as their speeds, the algorithm categorizes the state of the driving environment and proposes the optimal action accordingly.

Additionally, the same dataset was used for determining the critical area of influence of a vehicle by implementing the principles on mutual information theory considering the speeds of the vehicles as the random variable. Different vehicle types were investigated and mutual information was computed for 20 different radiuses. The estimation of the area of influence has applications in cooperative environments where vehicles are exchanging messages with its surrounding ones within the transmission range of the wireless network.

The results of the above research works have been presented in the 24th IEEE International Conference on Intelligent Transportation Systems - ITSC2021 and in the 10th International Congress on Transportation Research, respectively.

Finally, a first version of the Driver Behavioral Model (DBM) was derived from virtual experiment data, collected within the framework of the RO2 pilot, led by FZI in Karlsruhe, using the principles of inverse reinforcement learning. This model is a preliminary effort to describe the reaction of a Level 3 automated vehicle when a pedestrian appears aiming to cross the road. Based on the collected vehicle trajectories, the speed of the two agents and the spatial gap between them, the algorithm tries to find the optimum behavior for a safe interaction between the vehicle and this type of vulnerable road user.

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This project has received funding from the European Union’s Horizon 2020 Research and Innovation Programme under grant agreement no 815001.

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