Integrated 4D driver modelling under uncertainty

Informations projet

i4Driving

N° de convention de subvention: 101076165

DOI

10.3030/101076165

Date de signature de la CE 24 Août 2022

Date de début 1 Octobre 2022

Date de fin 31 Mars 2026

Financé au titre de

• Climate, Energy and Mobility

Coût total

€ 6 766 958,75

Contribution de l’UE

€ 6 766 958,75

Coordonné par

PANTEIA BV
Netherlands

CORDIS fournit des liens vers les livrables publics et les publications des projets HORIZON.

Les liens vers les livrables et les publications des projets du 7e PC, ainsi que les liens vers certains types de résultats spécifiques tels que les jeux de données et les logiciels, sont récupérés dynamiquement sur OpenAIRE .

Livrables

Data sets, microdata, etc (2)

Experimental data relevant to model development

Open-access GitHub repository containing data that have been measured in field experiments and have informed the development of the model. With the data, various hypotheses and assumptions are tested before they are integrated into the model. Linked to task 5.2

Harmonized, annotated, and processed data in usable format

Open-access GitHub repository containing converted data from various sources, available in the OpenSCENARIO and the CommonRoad format. Linked to task 1.1.

Documents, reports (18)

Integrated LC with social interactions and HF models – theory and principles

Paper / report, published on an open access GitHub repository, on new simulation models for integrated lane changing (LC) and car following (CF) that include additional Human Factors which are expected to increase the predictive power of human driver models. These HFs include social interactions (tailgating, getting/staying out-of-the-way) and effects of perception errors (e.g. underestimating gaps) and response adaptation (e.g. reducing desired speed). Linked to task 2.3

Dissemination and exploitation plan update

Update/revised dissemination and exploitation plan, including communication activities). Linked to task 7.1

Critical review of state-of-the-art techniques to model drivers’ heterogeneity

A report published on an open access GitHub repository will detail the state-of-the-art techniques applied in Traffic Flow Theory and Human Factors literatures to model inter- and intra-driver heterogeneity. Linked to task 4.1

Research Data Management Plan 2

Second update of the research data management plan. Linked to task 8.4

Experimental setup for the driving simulator experiments

A report published on open access GitHub repository, describing the experimental design of the driving simulator experiments. This includes description of which use cases will be studied, in which driving simulator, and descriptions of the driving simulator scenarios. Linked to task 3.1

Methods to harmonize data on human driving performance from different datasets

A report uploaded on an open access GitHub repository detailing developed methods to translate data into different formats (for instance, map information of traffic scenes is stored in different formats, such as OpenDRIVE or lanelets). Converters will be able to convert all data into a single format for a streamlines evaluation. This is linked to task 1.1.

Project Quality Handbook

Develop a Project Quality Handbook (including risk assessment plan, ethics and GDPR) and annual quality reviews. This will be developed in M1, revised and updated in M36. Linked to task 8.3

Research Data Management Plan 1

Develop the Data Management Plan by M6 and revise in M18 and M36, which follows the FAIR data principles making project data/research outputs findable, accessible, interoperable and reusable. Linked to task 8.4

Causal relationships between human/external factors and human driving behaviors: modelling requirements & framework of testable hypotheses

A report published on an open-source GitHub repository detailing key requirements and testable hypotheses for the modelling framework developed in WP2 geared towards credible and plausible modelling outcomes from an HF perspective. Major categories of testable hypotheses examined are awareness, cognitive workload and tactical driving strategies. Linked to task 1.3

Project glossary

Develop a project glossary which contains a summary of all main acronyms, terms and definitions relevant for the project. This will be developed in M1, reviewed and updated in M24. Linked to task 8.2

i4Driving Framework design & modeling and coding design principles

A document and/or reference published on an open access GitHub repository that describes the conceptual and mathematical principles of the microsimulation software (OTS/Aimsun) used in the project in terms of scope and behavioral principles (key assumptions, abstractions and simplifications); numerical solutions (approximation/solution methods, vehicle & infra/graph representation, time/event-queue handling, etc.) and software design principles (naming and coding conventions, data/project management, version management, etc.). Linked to task 2.1

Methods to extract statistically significant relationships between human/external factors and driver behavioral mechanisms, in uncritical and critical situations

A report uploaded on an open access GitHub repository detailing the selection and use of specific machine learning techniques for identifying the statistically significant relationships between factors and behaviours. Linked to task 1.2.

Implementation framework of the scenario-based evaluation workflow

This deliverable is the documentation of the development of the scenario based evaluation framework, including all the sub-elements of the framework, and how the framework can be implemented and executed in simulation environment. This is linked to task 6.1.

Project Management Handbook

Develop an internal handbook to establish and define clear rules/ procedures for communication, contractual, financial and administrative management aspects. Linked to taska 8.1 and 8.2

Methodology and results: relevant use cases and safety-critical scenarios

This deliverable is to identify the relevant use cases and safety critical scenarios for evaluating the human driver model and the target applications. Using an hazard based testing approach, this deliverable will generate scenarios and identify scenario parameter ranges. They will be in the form of documentation of the scenario generation methodology, and the actual generated scenarios uploaded to the Safety PoolTM scenario database. Linked to task 1.4

Evaluation criteria and detailed description of field experiments

A document published in an open access GitHub repository describing field experiments, including the definition of key driving performance indicators and how they are measured in the field experiments, the characterization of scenarios, necessary equipment, how many participants are needed to realistically replicate the scenarios, and how many experiments are needed to generate statistically valid results. Linked to task 5.1

Project glossary update

Updated project glossary. Linked to task 8.2

Dissemination and exploitation plan (including communication activities)

This deliverable contains a detailed plan stating the dissemination and exploitation roadmap for the i4Driving project. It includes the responsibilities of each partner, the dissemination channels intend to use, together with a dissemination monitor/tracker. Dissemination and exploitation roadmap will include publications, presentations, inputs to standards and regulations. This will be done by M6 and revised in M18 and M36. Linked to task 7.1

Other (5)

Validated ethics assessment plans and approval from Ethics committee

A document published in an open access GitHub repository describing the ethics considerations for the driving simulator and real worlds test from the different test facilities. It also includes the approvals from the different national ethic committees. Linked to task 3.1

Website and social networks profiles

Project website and social networks profiles designed and published online. Linked to task 7.2

Software for automatically increasing the criticality of scenarios

Open-source GitHub repository containing a software that will alter the states of vehicles (by using optimization techniques), such that the solution space of the ego vehicle is reduced, thus creating a more critical scenario for that vehicle. The input to the software will be a traffic scene in the CommonRoad format. Linked to task 3.1

Open-source library of data mining techniques

The software employed and adapted for the data mining research will be published on an open-source GitHub repository. Linked to task 1.2

Validated ethics assessment plan and approval from Ethics committee

A document published in an open access GitHub repository describing the process of unification and validation of the ethics assessment plans from each partner executing experimental work in closed field tests. The document will also describe the comprehensive programme on Research Ethics at TUM (LfE), and the training possibly provided to the partners to support and ensure the familiarization process with conducting the type of experimental work required for this project. Linked to task 5.1

Publications

Peer reviewed articles (7)

An annotated timeline of sensitivity analysis

Auteurs: arantola S., F. Ferretti, S. Lo Piano, M. Kozlova, A. Lachi, R. Rosati, A. Puy, P. Roy, G. Vannucci, M. Kuc-Czarnecka and Saltelli, A.
Publié dans: Elsevier, in Environmental Modelling & Software 174, Numéro Elsevier, in Environmental Modelling & Software 174, 2024, ISSN 1873-6726
Éditeur: Elsevier
DOI: 10.1016/j.envsoft.2024.105977

What is Post-normal Science? A post-normal encounter

Auteurs: Saltelli, A.
Publié dans: Springer, in Foundations of Science Journal, 2024, ISSN 1572-8471
Éditeur: Springer
DOI: 10.1007/s10699-023-09932-x

Unpacking uncertainty in the modelling process for energy policy making

Auteurs: Lo Piano, S., Lőrincz, M. J., Puy, A., Pye, S., Saltelli, A., Smith, S. T., & van der Sluijs, J. P.
Publié dans: Wiley Periodicals LLC on behalf of Society for Risk Analysis, 2023, ISSN 1539-6924
Éditeur: Wiley Periodicals LLC on behalf of Society for Risk Analysis
DOI: 10.1111/risa.14248

The challenge of quantification: an interdisciplinary reading

Auteurs: Di Fiore, M., Kuc-Czarnecka, M., Lo Piano, S., Puy, A. and Saltelli, A.
Publié dans: Minerva, 2023, ISSN 1573-1871
Éditeur: Minerva
DOI: 10.1007/s11024-022-09481-w

Impact assessment culture in the European Union. Time for something new?

Auteurs: Saltelli, A., Kuc-Czarnecka, M., Piano, S.L., Lőrincz, M.J., Olczyk, M., Puy, A., Reinert, E., Smith, S.T. and van Der Sluijs, J.P.
Publié dans: Elsevier - environmental science & policy, Numéro Elsevier, in journal of Environmental Science & Policy, 142, pp.99-111, 2023, ISSN 1873-6416
Éditeur: Elsevier
DOI: 10.1016/j.envsci.2023.02.005

Discrepancy Measures for Global Sensitivity Analysis

Auteurs: Puy, Arnald; Roy, Pamphile T.; Saltelli, Andrea
Publié dans: Technometrics, 2024, ISSN 0040-1706
Éditeur: American Statistical Association
DOI: 10.48550/arxiv.2206.13470

Predicting Autonomous Driving Behavior through Human Factor Considerations in Safety-Critical Events

Auteurs: Jamal Raiyn; Galia Weidl
Publié dans: MDPI - Smart Cities journal, Numéro MDPI, in Smart Cities journal, 7(1), 460-474, 2024, ISSN 2624-6511
Éditeur: MDPI
DOI: 10.3390/SMARTCITIES7010018