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Needs, wants and behaviour of 'Drivers' and automated vehicle users today and into the future

Periodic Reporting for period 2 - DriveToTheFuture (Needs, wants and behaviour of 'Drivers' and automated vehicle users today and into the future)

Reporting period: 2020-11-01 to 2022-10-31

Transport automation is a reality; it is now a matter of how to make the best of it. User awareness, acceptance & training formulate priority challenges. Questions on vehicle taking over control from humans, change of mobility habits & experience, cost of future commuting & travelling, ethical decisions of a machine vs. a human, the need of new driver training incentives for adapting to the technological evolution in future vehicles, require research-based answers. Drive2theFuture developed training, HMI concepts, incentives policies & other cost efficient measures by promoting & comparatively assessing alternative connected, shared & automated transport use cases for all modes & types of users (drivers, travelers, pilots, VRUs, fleet operators & other stakeholders), to understand, simulate, regulate & optimize their sustainable market introduction; including societal awareness creation, acceptance enhancement & training on use. Thus providing the means to prepare future “drivers”, travelers & vehicle operators to accept & use connected, cooperative & automated transport modes & the industry of these technologies to understand & meet their needs & wants.
Detailed user/stakeholder clustering was performed, the VRUs definition was updated for transport automation & common terminology for automated driving structured. The user opinion on AVs (for all modes) was analyzed through an extended customer survey with over 11500 questionnaires from over 30 countries. Transferability issues between modes & research hypotheses, along with a taxonomy of knowledge & skills required to operate AVs were specified per mode; resulting to 12 priority Use Cases. Based upon existing & project created data, the AV driver behaviour was modelled, using a data analytics framework for big data analysis & fusion. These led to a framework for assessing the acceptance & impact of AV & a micro-macro simulation tools suite, enabling such impact assessment. Relevant behavioral models were defined aiming on the development of a conceptual microscopic AV-DBM model. A sentiment analysis framework was applied to over 126000 responses on AVs from 3 social media platforms & analyzed by a connected NN model. Affective, persuasive & personalized HMIs for AVs were designed, developed & optimized through pilots; these were co-created for all modes, with emphasis on VRUs, conspicuity enhancement & interaction management with non-autonomous traffic participants. Also, a wearable-based emotion responses analysis multisensorial system was built & used. This work concluded to a number of innovative interfaces & an HMI co-creation toolkit for AVs for all modes. In parallel, training needs were researched & training content & programs developed for users & stakeholders, focusing on lifelong training, based on a multimedia training platform, including training content for all modes’ automation & for different clusters, including also a VR/AR training toolkit for AV “drivers”. Also, training certification requirements were issued along with “soft” acceptance creation measures & training incentives. The impact of automation to employment & relevant reskilling schemes were researched & analyzed. All project developments were piloted in 8 road, 2 rail, 1 maritime & 1 aviation– related pilots across Europe; in 3 pilot phases (benchmarking, iterative development, final tools assessment). Pilots included simulators, test track &real-world pilots, as well as demonstrations at key events. Pilot results consolidation & impact assessment resulted to significant user acceptance enhancement after the use of project tools; including user comfort, AV experience, perceived safety, trust & usability. The relation between transport automation & MaaS was investigated in pilots, while a comparison of the pilots’ results to a priori expectations per mode led to some key interesting findings. Finally, best practices were transformed into a “European Statement of Principles” (ESoP) on AV HMI. All above work was realised taking due care of ethical, sociocultural & gender, safety & security as well as legal & regulatory issues, which were researched in relation to transport automation for all modes. A wide & concise dissemination & communication plan was realized, with 28 scientific papers, dissemination material, attendance of over 30 relevant events, social media presence with over 1000 followers, 3 project workshops with great attendance & stakeholders’ balance. A business model suite was developed for all modes & levels AV, while 12 exploitable products stemmed out of project results. An inclusive set of guidelines & policy recommendations was developed & a thorough Research Roadmap on enhancing AV acceptance & deployment was defined for all transport modes & multimodal transport. Many concertation events took place with 3 parallel projects & several others in the area, leading to wide & structured knowledge exchange & transfer. An International Advisory Board of 4 world renowned experts in the field supervised & guided effectively project activities.
Drive2theFuture approaches AVs user awareness & acceptance issues in a holistic & user-oriented manner, addressing all user categories & modes of transport, their needs & different characteristics. Going beyond the state-of-the-art, it captured the feelings & attitudes of the different user groups (through the voice-of-customer survey, acceptance risk assessment & sentiment analysis) towards AVs, also considering the expected transformation of each group's role. The development of an AV driver behavioral model (for passenger cars -with transferability potential to other modes) aiming to ensure safety when the system takes control, & its integration in an AV developer’s simulation suite (incorporating big data management, modelling & prediction tools, wearables detecting user reaction to AV functions, simulation platform), bring a valuable tool for developers & evaluators of existing & new AV functions & HMI, to deliver safe, effective & acceptable products, through a user-centric approach. HMI is a crucial part for user acceptance, so focus was in the adaptation & further improvement of good practices through iterative testing with real users, using VR demonstrators as development & training tools, towards an educated expectation of automated transport to the public. Training needs were investigated & programs & curricula for all user clusters & modes with multiple means suggested. Special focus was on the future workforce, identifying the knowledge & skills required for increasing competences & competitiveness in the evolving transportation working environment. A maximizing factor for the benefits of AVs is their link to other transportation trends, such as MaaS; relevant best cases, business models, stakeholder rules & incentive strategies were investigated, for common deployment & convergence towards Connected Automated Vehicles Shared Mobility. Policy schemes, measures & incentives were proposed for AVs promotion, linked to appropriate business models. Ultimately, the progress of technological achievements paired with this of users’ & stakeholders’ awareness & the customization with the new era, led the creation of an Automation User Acceptance Creation Roadmap, determining the steps for automation deployment towards achieving maximum acceptance, for all transportation modes with common & differentiated milestones per mode.
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