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Safety tolerance zone calculation and interventions for driver-vehicle-environment interactions under challenging conditions

Periodic Reporting for period 3 - i-DREAMS (Safety tolerance zone calculation and interventions for driver-vehicle-environment interactions under challenging conditions)

Período documentado: 2022-05-01 hasta 2023-04-30

NEW OPPORTUNITIES TO TACKLE ROAD SAFETY
Several factors of driver state negatively impact road safety, such as distraction (in-vehicle or external), fatigue and drowsiness, health concerns (e.g. illness, frailty, cognitive state) and extreme emotions (e.g. anxiety, stress, anger). Moreover, differences in socio-cultural
factors are still among the main determinants of road risks. At the same time, technological developments make massive and detailed operator performance data easily available. For example via new in-vehicle sensors that capture detailed driving style and contextual data. This creates new opportunities for the detection and design of customised interventions to mitigate the risks, increase awareness and upgrade driver performance, constantly and dynamically. The optimal exploitation of these opportunities is the challenge that i-DREAMS faces.

HOW WILL I-DREAMS MAKE A DIFFERENCE?
The project focuses on the driver-vehicle environment interactions and on the human factors affecting the behaviour of drivers. Technology to monitor and analyse driving behaviour is used, to keep the driver in the ‘Safety Tolerance Zone’. This technology can intervene both during and after the ride. During experiments, for example, sensors in the steering wheel or a wristband will monitor the driver's heart rhythm, so that both the driving behaviour and the alertness of the driver are measured in real-time. The vehicle could give a warning if the sensor detects that the driver is no longer concentrated or engages in risky driving situations. Even after the ride, the driver can be briefed about dangerous traffic situations that occurred while driving. This can have a sensitizing effect and can be used for driver training purposes.
Initial testing will take place in a driving simulator environment after which promising interventions will be tested and validated under real-world conditions in a testbed consisting of 600 drivers in total across 5 EU countries. Market roadmaps will be developed to support smooth transition of the investigated technologies to the market and experience from use cases in different European countries will be used to disseminate best practices.
In reporting period 1, the following major activities took place:
1) the scientific underpinning of the i-DREAMS data collection system has been developed including methods, techniques, indicators and sensors to evaluate driver, environment and vehicle status (WP2)
2) the scientific underpinning of the i-DREAMS intervention framework has been developed including gamification techniques for nudging the driver in the vehicle and coaching the driver post-trip (WP3)
3) the scientific underpinning of the i-DREAMS Safety Tolerance Zone (STZ) has been developed, both in general and more specifically for risk-related events including: speeding, illegal overtaking, fatigue and tailgating (WP3)
4) the framework and experimental protocol for the operational design of the simulator and field trials have been prepared to inform all field trial partners of the practical arrangements to be prepared in advance (WP3)
5) a consultation with scientific experts (Expert Advisory Board) and stakeholders from different sectors (User Advisory Board) was organized to obtain feedback on the design of the i-DREAMS system (WP3+WP9)
6) the data architecture of the i-DREAMS system (i.e. in vehicle-logging and processing), and procedures for secure wireless transfer and safe storage of data by the i-DREAMS data Gateway to the cloud for post-trip processing, and the architecture for the back-office database for analysis have been designed (WP3)
7) the full functionality and screen designs were developed for the i-DREAMS driver app and i-DREAMS web portal (WP4)
8) the Safety Tolerance Zone in-vehicle intervention logic was implemented and a prototype of in-vehicle intervention device implemented (WP4)
9) a beta-release of the i-DREAMS driver app and web platform were implemented (WP4) and are now being tested
10) the integrated set of sensors for the i-DREAMS in-vehicle monitoring equipment were incrementally implemented, prototyped and tested in the simulator and pilot vehicles of CARDIOID and UH (WP4)
11) two driving simulators (car + heavy vehicle) equipped with the i-DREAMS technology were constructed and tested and are ready for use in the simulator trials (WP4)
12) a unified plan for the recruitment of drivers for the simulator and field trials was developed, social media content and recruitment questionnaires prepared (WP5)
13) detailed description of the driving simulator scenarios for the different transport modes were created and already partially implemented (WP5)
14) the data analysis protocol for the risk evaluation (WP6) and the effectiveness of interventions (WP7) were prepared
15) a first version of the exploitation strategies for the i-DREAMS system for different modes of transport were prepared (WP8)
16) Intermediate results of the i-DREAMS project were communicated through the project web portal, newsletters, conference publications, a policy brief and social media (WP9)
17) Ethics applications for the simulator and field trials were prepared by the different partners involved in the simulator and field trials (WP10)
Key expected project results include:
1. A methodology for the definition of the safety tolerance zone (STZ), taking into account the driving context and identification of situations approaching the boundaries of the safety zone
2. The i-DREAMS system for driver monitoring and interventions including: a) a big data platform for data fusion through different sensors and integration for monitoring of safety behaviour and early identification of safety-critical events, and b) applications and interfaces for driver alert, information, training and awareness raising (i.e. in-vehicle alerts, post-trip feedback and social gamification)
3. A human factors data resource, i.e. a dataset for analysis purposes including data from the simulator and field trials in 5 countries, 4 modes and 25 variables related to human factors, operator context and vehicle status.
4. Recommendations for key stakeholders, including EU, national and regional authorities, OEM, insurance, fleet management, road operators, with a focus on the implications for the development of highly automated vehicles.
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