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Horizon Europe (2021 - 2027)

Human behavioural model to assess the performance of CCAM solutions compared to human driven vehicles (CCAM Partnership)

Last update: Sep 16, 2022 Last update: 16 Sep, 2022

Details

Location: EU 27 EU 27
Contracting Authority Type: Development Institution
Status: Awarded
Budget: Euro 8,000,000
Award ceiling: N/A
Award floor: N/A
Sector: Social Development, Vehicles, Research
Eligible applicants: Unrestricted / Unspecified, Individuals
Eligible nationalities: Afghanistan, Albania, Algeria, A ... See more Afghanistan, Albania, Algeria, American Samoa, Angola, Anguilla, Argentina, Armenia, Aruba, Austria, Azerbaijan, Azores, Bangladesh, Belarus, Belgium, Belize, Benin, Bermuda, Bhutan, Bolivia, Bosnia and Herzegovina, Botswana, British Virgin Islands, Bulgaria, Burkina Faso, Burundi, Cambodia, Cameroon, Canary Islands, Cape Verde, Caribbean Netherlands, Cayman Islands, Central African Republic, Chad, Chile, Colombia, Comoros, Congo, Costa Rica, Cote d'Ivoire, Croatia, Cuba, Cyprus, Czech Republic, Dem. Rep. Congo, Denmark, Djibouti, Dominica, Commonwealth of, Dominican Republic, Ecuador, Egypt, El Salvador, Eritrea, Estonia, Eswatini (Swaziland), Ethiopia, Falkland Islands, Faroe Islands, Fiji, Finland, France, French Polynesia, French Southern Territory, Gabon, Gambia, Georgia, Germany, Ghana, Greece, Greenland, Grenada, Guatemala, Guinea, Guinea-Bissau, Guyana, Haiti, Honduras, Hungary, Iceland, Indonesia, Iran, Iraq, Ireland, Israel, Italy, Jamaica, Jordan, Kazakhstan, Kenya, Kiribati, Kosovo, Kyrgyzstan, Laos, Latvia, Lebanon, Lesotho, Liberia, Libya, Lithuania, Luxembourg, Madagascar, Malawi, Malaysia, Maldives, Mali, Malta, Marshall Islands, Mauritania, Mauritius, Micronesia, Moldova, Mongolia, Montenegro, Montserrat, Morocco, Mozambique, Myanmar, Namibia, Nepal, Netherlands, New Caledonia, Nicaragua, Niger, Nigeria, North Korea, North Macedonia, Norway, Pakistan, Palau, Palestine / West Bank & Gaza, Panama, Papua New Guinea, Paraguay, Peru, Philippines, Pitcairn, Poland, Portugal, Romania, Rwanda, Saint Helena, Saint Kitts and Nevis, Saint Lucia, Saint Vincent and the Grenadines, Samoa, Sao Tome and Principe, Senegal, Serbia, Seychelles, Sierra Leone, Slovakia, Slovenia, Solomon Islands, Somalia, South Africa, South Sudan, Spain, Sri Lanka, St. Pierre and Miquelon, Sudan, Suriname, Sweden, Switzerland, Syria, Tajikistan, Tanzania, Thailand, Timor-Leste, Togo, Tonga, Tunisia, Turkey, Turkmenistan, Turks and Caicos, Tuvalu, Uganda, Ukraine, Uruguay, Uzbekistan, Vanuatu, Venezuela, Vietnam, Wallis and Futuna, Yemen, Zambia, Zimbabwe
Date posted: 21 Jun, 2021

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Description

Call updates

Jan 28, 2022 10:41:47 AM

The call HORIZON-CL5-2022-D6-01 closed on 12/01/2022. 66 proposals were submitted, with the following breakdown per topic:

HORIZON-CL5-2022-D6-01-03: (RIA) 4 proposals

Oct 26, 2021 10:29:47 AM

The submission session is now available for: HORIZON-CL5-2022-D6-01-03(HORIZON-RIA)


Human behavioural model to assess the performance of CCAM solutions compared to human driven vehicles (CCAM Partnership)

TOPIC ID: HORIZON-CL5-2022-D6-01-03

Programme: Horizon Europe Framework Programme (HORIZON)
Call: Safe, Resilient Transport and Smart Mobility services for passengers and goods (HORIZON-CL5-2022-D6-01)
Type of action: HORIZON-RIA HORIZON Research and Innovation Actions
Type of MGA: HORIZON Action Grant Budget-Based [HORIZON-AG]
Deadline model: single-stage
Planned opening date: 14 October 2021
Deadline date: 12 January 2022 17:00:00 Brussels time

Topic description

ExpectedOutcome:

Project results are expected to contribute to all of the following expected outcomes:

A robust and scalable reference model of human driving behaviour:

  • Replicating the full performance spectrum of human drivers, which allows comparing the performance of an automated driving system in a specific situation to the human driver population. This serves as a basis to define the required safety level of CCAM systems and to take decisions on validation requirements in type approval schemes. The model will also help to define fair assessment criteria in consumer testing campaigns relative to human-driven vehicles and for the safety verification of CCAM systems in industrial development processes.
  • Serving as a reference for the automotive industry and its R&I partners to design human-like and therefore easily predictable and acceptable behaviour of automated driving functions in mixed traffic.
  • Helping the automotive industry, its R&I partners, certification bodies and consumer testing organisations to realistically represent the behaviour of other human-driven vehicles in the (virtual) simulation of mixed traffic. Virtual testing shortens development cycles and accelerates the implementation of CCAM technologies.

Scope:

Statistical data available today gives a good idea of overall human driving, vehicle and infrastructure performance in terms of safety. However, evidence is missing on the precise performance of humans in the variety of specific situations that might be critical for automated driving systems. The variability of human behaviour and performance with factors like gender, cultural and ethnic background, ageing, diseases, driving experience, mental workload or fatigue makes the acquisition of such evidence a very challenging task. External factors such as diverse weather and lighting conditions play a role in this context, as well. Data on the dependence of human driving behaviour from such factors is partly available from previous research, but not sufficiently broken down to the level of specific driving situations.

Available software modules to simulate human driving behaviour only cover specific aspects of human driving performance so far and do not cover the full spectrum of drivers with statistical data on the probability of certain behavioural patterns.

Therefore, proposed actions have to develop a probabilistic human behavioural model with the potential to cover all relevant aspects of human driving performance as well as the broad spectrum of drivers and influencing factors. A methodology will be needed to extract consistent data on human driving performance from different data sources (e.g. real traffic, simulator tests) and collect such data with the long-term objective of fully depicting the large variance of human driving behaviour in different situations, while respecting gender, age and other factors like disabilities and diversity criteria. Proposals should calibrate the parameters of the model with the help of this data, and develop a corresponding validation concept based on real-world experiments. Potential ethical issues will have to be considered, as tests with humans need to be carried out and their personal data will have to be captured. The model should be transparent, independent from proprietary software tools and easy to use. It should be validated at least for selected fields of application with the perspective of extending these fields of application gradually and also simulating human behaviour in future scenarios of mixed traffic.

In order to achieve the expected outcomes, international cooperation is advised, in particular with projects or partners from the US, Japan, Canada, South Korea, Singapore, Australia.

This topic implements the co-programmed European Partnership on ‘Connected, Cooperative and Automated Mobility’ (CCAM).

Call updates

Jan 28, 2022 10:41:47 AM

The call HORIZON-CL5-2022-D6-01 closed on 12/01/2022. 66 proposals were submitted, with the following breakdown per topic:

HORIZON-CL5-2022-D6-01-03: (RIA) 4 proposals

Oct 26, 2021 10:29:47 AM

The submission session is now available for: HORIZON-CL5-2022-D6-01-03(HORIZON-RIA)


Human behaviour...

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