CORDIS provides links to public deliverables and publications of HORIZON projects.
Links to deliverables and publications from FP7 projects, as well as links to some specific result types such as dataset and software, are dynamically retrieved from OpenAIRE .
Deliverables
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
Experimental data relevant to model validation (opens in new window)After the model development, field experiments are performed to test the models in specific situations and compare i4Driving model predictions with measured driving behaviours. An Open-access GitHub repository will include data that are measured in field experiments and passed to the validation framework. Linked to task 5.3
Harmonized, annotated, and processed data in usable format (opens in new window)Open-access GitHub repository containing converted data from various sources, available in the OpenSCENARIO and the CommonRoad format. Linked to task 1.1.
The document published in an open access GitHub repository includes two aspects: (i) the quality of the 4D human driver model is evaluated and compared to current models available to simulate human driver behaviors, (ii) the newly developed 4D human driver model is applied for safety and efficiency evaluation (in a mixed traffic environment). In this respect, travel time and energy consumption are comparison criteria, among other things. Linked to task 6.6
Specification of the scenario description language, and conversion tool (opens in new window)This deliverable contains: 1) a documentation of a scenario description language specification, specifying the language concept, the language grammar, and the conversion approach to the ASAM OpenX format, 2) a documentation detailing the conversion toolchain development for converting the scenarios described in the scenario description language in point 1 to the ASAM OpenX standards. Linked to task 6.2
Human driver models as baseline for consumer testing campaigns of ADS (opens in new window)A document published in an open access GitHub repository will describe:a) the execution of concrete scenarios using, as ego vehicle, either the ADS and the human driver models in order to compare their behaviours. b) the execution of a set of scenarios using an integrated human driver model + ADS/ADAS unit as ego vehicle to demonstrate that the human driver models can be used for ADS/ADAS testing (not fully automated functions). Linked to task 6.4
Integrated LC with social interactions and HF models – theory and principles (opens in new window)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 (opens in new window)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 (opens in new window)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 (opens in new window)Second update of the research data management plan. Linked to task 8.4
Integrated LC with social interactions and HF models – verification and calibration (opens in new window)A report uploaded on an open access GitHub repository detailing the scrutinized competing approaches, assumptions, model formulations and parameter structures, and the results of model verification and calibration. Linked to task 2.4
Experimental setup for the driving simulator experiments (opens in new window)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 (opens in new window)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 (opens in new window)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 (opens in new window)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
Report on dissemination activities, including cooperation with other projects (opens in new window)This report summarises the dissemination activities, stating the details of individual items, partners’ contribution, impact, and how they compare with the original plan. Linked to task 7.2, 7.3, and 7.4
Map of the heterogeneity of human/external factors into driving behaviour perform. (opens in new window)A report published on an open access GitHub repository describing the analysis of the results from the driving simulator experiments. This includes mapping the results and findings with respect to the heterogeneity of human/external factors. Linked to task 3.2
Research Data Management Plan 3 (opens in new window)Final update of the research data management plan. Linked to task 8.4
Project Quality Handbook update (opens in new window)Updated project quality handbook. Linked to task 8.3
White paper (opens in new window)A documentation describes the project development process within the project, and provides guidelines on how the work can be used in ADS development and policy making. Linked to task 7.5
Final booklet (opens in new window)Develop the final booklet summarising the main project results, outputs and tools in an easy-to-read and concise format. Linked to task 7.5
Causal relationships between human/external factors and human driving behaviors: modelling requirements & framework of testable hypotheses (opens in new window)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
Dissemination and exploitation plan update final (opens in new window)Final update of the dissemination and exploitation plan. Linked to task 7.1
Project glossary (opens in new window)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 (opens in new window)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 (opens in new window)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.
Exploitation plans for each partner (opens in new window)An exploitation plan details of the i4Driving outcome for CCAM stakeholders (ADS developers, regulators, certification bodies, consumers etc). It will liaise with various international standardisation and regulatory bodies. This is linked to task 7.6
Implementation framework of the scenario-based evaluation workflow (opens in new window)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 (opens in new window)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 (opens in new window)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
Sensitivity Auditing (opens in new window)A technical self-sustaining report uploaded in an open access GitHub repository will describe the principles of sensitivity auditing, how these have been applied to the modelling activities of i4Driving, and relevant findings. Linked to task 2.5
Evaluation criteria and detailed description of field experiments (opens in new window)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
Human driver models as baseline for PEARS (opens in new window)Documentation on how the evaluation framework is used for the human driver model (from integrating with the model, to obtaining the scenarios, to establishing the evaluation criteria and executing the scenarios), it also contains the details of the evaluation results. This is linked to task 6.3
Project glossary update (opens in new window)Updated project glossary. Linked to task 8.2
Dissemination and exploitation plan (including communication activities) (opens in new window)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
The library of validated probabilistic human driver behavioural models will be published open source on a GitHub repository. Linked to tasks 4.3 and 4.4.
Open-source library of techniques to encode drivers’ heterogeneity into models (opens in new window)The software employed to estimate distributions and correlation structures of i4Driving model parameters will be published open-source on a GitHub repository. Linked to task 4.2
Validated ethics assessment plans and approval from Ethics committee (opens in new window)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 (opens in new window)Project website and social networks profiles designed and published online. Linked to task 7.2
Software for automatically increasing the criticality of scenarios (opens in new window)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 (opens in new window)The software employed and adapted for the data mining research will be published on an open-source GitHub repository. Linked to task 1.2
Incremental versions of i4Driving / software library (opens in new window)Open-source GitHub repository containing software versions. A version represents a major new release of the simulation software (e.g. version 1.0 or 2.1) including release notes, and e.g. updated examples, demo’s, documentation and unit tests. Linked to task 2.2
Open-source GitHub evaluation software toolchain (opens in new window)OOpen source the language and conversion toolchain (including identifying the correct license) on Github, the deliverable will be a repository with required documentation. This is linked to task 6.1
Suite of unit tests for model development (opens in new window)A (growing!) catalog / library of annotated testcases (code snippets) designed to identify, locate, and reproduce semantic errors, published in an open-source GitHub repository. This library is a safeguard in preventing re-occuring (resolved) bugs and errors and in making sure new releases/versions are backward compatible. Linked to task 2.1
Validated ethics assessment plan and approval from Ethics committee (opens in new window)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
Documentation on how the evaluation framework is used for different target applications (from integrating with the models, to obtaining the scenarios, to establishing the evaluation criteria and executing the scenarios), it also contains the details of the evaluation results and the thresholds/metrics used for each of the five target applications. This is linked to task 6.2
Publications
Author(s):
Florian Finkeldei, Christoph Thees, Jan-Niklas Weghorn, Matthias Althoff
Published in:
Automotive Innovation, Issue 8, 2025, ISSN 2096-4250
Publisher:
Springer Science and Business Media LLC
DOI:
10.1007/S42154-025-00360-0
Author(s):
Andrea Saltelli, Marta Kuc-Czarnecka, Samuele Lo Piano, Máté János Lőrincz, Magdalena Olczyk, Arnald Puy, Erik Reinert, Stefán Thor Smith, Jeroen P. van der Sluijs
Published in:
Environmental Science & Policy, Issue 142, 2025, ISSN 1462-9011
Publisher:
Elsevier BV
DOI:
10.1016/J.ENVSCI.2023.02.005
Author(s):
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.
Published in:
Elsevier, in Environmental Modelling & Software 174, Issue Elsevier, in Environmental Modelling & Software 174, 2024, ISSN 1873-6726
Publisher:
Elsevier
DOI:
10.1016/j.envsoft.2024.105977
Author(s):
Ahlström, C., Kircher, K., Johansson, F., Andersson, A. Olstam, J.
Published in:
Elsevier (Accident Analysis & Prevention), 2025, ISSN 0001-4575
Publisher:
Pergamon Press Ltd.
DOI:
10.1016/J.AAP.2025.108276
Author(s):
Andrea Saltelli
Published in:
Environmental Modelling & Software, Issue 188, 2025, ISSN 1364-8152
Publisher:
Elsevier BV
DOI:
10.1016/J.ENVSOFT.2025.106430
Author(s):
Andrea Saltelli, Gerd Gigerenzer, Mike Hulme, Konstantinos V. Katsikopoulos, Lieke A. Melsen, Glen P. Peters, Roger Pielke, Simon Robertson, Andy Stirling, Massimo Tavoni, Arnald Puy
Published in:
WIREs Climate Change, Issue 15, 2024, ISSN 1757-7780
Publisher:
Wiley
DOI:
10.1002/WCC.915
Author(s):
Saltelli, A.
Published in:
Springer, in Foundations of Science Journal, 2024, ISSN 1572-8471
Publisher:
Springer
DOI:
10.1007/s10699-023-09932-x
Author(s):
Lo Piano, S., Lőrincz, M. J., Puy, A., Pye, S., Saltelli, A., Smith, S. T., & van der Sluijs, J. P.
Published in:
Wiley Periodicals LLC on behalf of Society for Risk Analysis, 2023, ISSN 1539-6924
Publisher:
Wiley Periodicals LLC on behalf of Society for Risk Analysis
DOI:
10.1111/risa.14248
Author(s):
Maya Sekeran, Tanja Niels, Johannes Lindner, Klaus Bogenberger
Published in:
Transportation Research Procedia, Issue 95, 2026, ISSN 2352-1465
Publisher:
Elsevier BV
DOI:
10.1016/J.TRPRO.2026.02.107
Author(s):
Andrea Saltelli
Published in:
Foundations of Science, Issue 29, 2024, ISSN 1233-1821
Publisher:
Springer Science and Business Media LLC
DOI:
10.1007/S10699-023-09932-X
Author(s):
Di Fiore, M., Kuc-Czarnecka, M., Lo Piano, S., Puy, A. and Saltelli, A.
Published in:
Minerva, 2023, ISSN 1573-1871
Publisher:
Minerva
DOI:
10.1007/s11024-022-09481-w
Author(s):
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.
Published in:
Elsevier - environmental science & policy, Issue Elsevier, in journal of Environmental Science & Policy, 142, pp.99-111, 2023, ISSN 1873-6416
Publisher:
Elsevier
DOI:
10.1016/j.envsci.2023.02.005
Author(s):
Stefano Tarantola, Federico Ferretti, Samuele Lo Piano, Mariia Kozlova, Alessio Lachi, Rossana Rosati, Arnald Puy, Pamphile Roy, Giulia Vannucci, Marta Kuc-Czarnecka, Andrea Saltelli
Published in:
Environmental Modelling & Software, Issue 174, 2024, ISSN 1364-8152
Publisher:
Elsevier BV
DOI:
10.1016/J.ENVSOFT.2024.105977
Author(s):
Andrea Saltelli, Arnald Puy, Monica Di Fiore
Published in:
International Review of Applied Economics, Issue 39, 2025, ISSN 0269-2171
Publisher:
Informa UK Limited
DOI:
10.1080/02692171.2024.2365727
Author(s):
Puy, Arnald; Roy, Pamphile T.; Saltelli, Andrea
Published in:
Technometrics, 2024, ISSN 0040-1706
Publisher:
American Statistical Association
DOI:
10.48550/arxiv.2206.13470
Author(s):
Jamal Raiyn; Galia Weidl
Published in:
MDPI - Smart Cities journal, Issue MDPI, in Smart Cities journal, 7(1), 460-474, 2024, ISSN 2624-6511
Publisher:
MDPI
DOI:
10.3390/SMARTCITIES7010018
Author(s):
Samuele Lo Piano, Andrea Saltelli
Published in:
Energy Research & Social Science, Issue 127, 2026, ISSN 2214-6296
Publisher:
Elsevier BV
DOI:
10.1016/J.ERSS.2025.104296
Author(s):
Monica Di Fiore, Marta Kuc-Czarnecka, Samuele Lo Piano, Arnald Puy, Andrea Saltelli
Published in:
Minerva, Issue 61, 2023, ISSN 0026-4695
Publisher:
Springer Science and Business Media LLC
DOI:
10.1007/S11024-022-09481-W
Author(s):
Samuele Lo Piano, Máté János Lőrincz, Arnald Puy, Steve Pye, Andrea Saltelli, Stefán Thor Smith, Jeroen van der Sluijs
Published in:
Risk Analysis, Issue 44, 2024, ISSN 0272-4332
Publisher:
Wiley
DOI:
10.1111/RISA.14248
Author(s):
Andrea Saltelli, Lieke A. Melsen, Arnald Puy
Published in:
Minerva, 2025, ISSN 0026-4695
Publisher:
Springer Science and Business Media LLC
DOI:
10.1007/S11024-025-09581-3
Author(s):
Jamal Raiyn, Galia Weidl
Published in:
Smart Cities, Issue 7, 2025, ISSN 2624-6511
Publisher:
MDPI AG
DOI:
10.3390/SMARTCITIES7010018
Author(s):
Andrea Saltelli, Arnald Puy
Published in:
SSRN Electronic Journal, 2022, ISSN 1556-5068
Publisher:
Elsevier BV
DOI:
10.2139/SSRN.4212453
Author(s):
Arnald Puy, Pamphile T. Roy, Andrea Saltelli
Published in:
Technometrics, Issue 66, 2024, ISSN 0040-1706
Publisher:
Informa UK Limited
DOI:
10.1080/00401706.2024.2304341
Author(s):
Ahlström, C., Kircher, K., Olstam, J., Johansson, F., & Andersson, A.
Published in:
Transportforum, 2025
Publisher:
VTI
Author(s):
Gerald Würsching, Tobias Mascetta, Sammy Breen, Matthias Althoff
Published in:
2025 IEEE 28th International Conference on Intelligent Transportation Systems (ITSC), 2026
Publisher:
IEEE
DOI:
10.1109/ITSC60802.2025.11423226
Author(s):
Tianyu Tang, Tobias Zillmann, Johan Olstam, Christer Ahlström, Fredrik Johansson, Wouter Schakel, Klaus Bengler
Published in:
AHFE International, Intelligent Human Systems Integration (IHSI 2026): Disruptive and Innovative Technologies, Issue 200, 2026
Publisher:
AHFE International
DOI:
10.54941/AHFE1007130
Author(s):
Kranthi Kumar Talluri, Anders L. Madsen, Galia Weidl
Published in:
2025 IEEE Intelligent Vehicles Symposium (IV), 2025
Publisher:
IEEE
DOI:
10.1109/IV64158.2025.11097350
Author(s):
Jamal Raiyn, Galia Weidl
Published in:
Proceedings of the 9th International Conference on Vehicle Technology and Intelligent Transport Systems, 2023
Publisher:
SCITEPRESS - Science and Technology Publications
DOI:
10.5220/0011839600003479
Author(s):
Tobias Mascetta, Edmond Irani Liu, Matthias Althoff
Published in:
2024 IEEE Intelligent Vehicles Symposium (IV), 2024
Publisher:
IEEE
DOI:
10.1109/IV55156.2024.10588548
Author(s):
Chaar, Mohamad Mofeed, Galia Weidl, and Jamal Raiyn
Published in:
9th International Symposium on Transportation Data & Modelling (ISTDM2023), 2023
Publisher:
ResearchGate
Author(s):
Gerald Würsching, Tobias Mascetta, Yuanfei Lin, Matthias Althoff
Published in:
2024 IEEE Intelligent Vehicles Symposium (IV), 2024
Publisher:
IEEE
DOI:
10.1109/IV55156.2024.10588748
Author(s):
Florian Finkeldei, Michael Wolf, Jan-Niklas Weghorn, Alexander Pretschner, Matthias Althoff
Published in:
2025 IEEE 28th International Conference on Intelligent Transportation Systems (ITSC), 2026
Publisher:
IEEE
DOI:
10.1109/ITSC60802.2025.11423597
Author(s):
Jamal Raiyn, Galia Weidl
Published in:
2023 IEEE International Smart Cities Conference (ISC2), 2023
Publisher:
IEEE
DOI:
10.1109/ISC257844.2023.10293463
Author(s):
Tobias Mascetta, Kilian Northoff, Matthias Althoff
Published in:
2025 IEEE Intelligent Vehicles Symposium (IV), 2025
Publisher:
IEEE
DOI:
10.1109/IV64158.2025.11097682
Author(s):
Müller, M. and Finkeldei, F. and Krasowski, H. and Althoff, M.
Publisher:
arXive
Author(s):
Christopher Stang, Julian Hay, Klaus Bogenberger, Galia Weidl
Published in:
2025 IEEE Intelligent Vehicles Symposium (IV), 2025
Publisher:
IEEE
DOI:
10.1109/IV64158.2025.11097453
Author(s):
Weidl, G., Berres, S. and Raiyn, J.,
Published in:
International Symposium on Transportation Data & Modelling (ISTDM2023), 2023
Publisher:
ResearchGate
Author(s):
Ahlström, C., Kircher, K., Johansson, F., Andersson, A., & Olstam, J
Published in:
Road Safety on Five Continents – RS5C , 2025
Publisher:
VTI
Author(s):
Kircher, K., Ahlström, C., Andersson, A., Johansson, F., & Olstam, J. (2025
Published in:
Road Safety on Five Continents – RS5C , 2025
Publisher:
VTI
Author(s):
Florian Finkeldei, Matthias Althoff
Published in:
2023 IEEE 26th International Conference on Intelligent Transportation Systems (ITSC), 2024
Publisher:
IEEE
DOI:
10.1109/ITSC57777.2023.10422092
Author(s):
Wouter Schakel, Victor Knoop, Mehdi Keyvan-Ekbatani, Hans van Lint
Published in:
2023, ISSN 2662-9992
Publisher:
MDPI AG
DOI:
10.20944/PREPRINTS202305.0193.V1
Author(s):
Papadoulis, A.
Published in:
2023
Publisher:
Aimsum
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