SUrrogate measures for SAFE autonomous and connected mobility

ERC (European Research Council)HORIZON-ERCID: 101039222
EC Contribution
€15,000
Consortium Size
1 orgs
Start Year
2023
Summary

SUperSAFE ""SUrrogate measures for SAFE autonomous and connected mobility"" will address the problem of the safety evaluation of the interaction between conventional vehicles and connected and automated vehicles (CAVs). The project builds on the notion that vehicle automation is posing new risks that the traditional accident-based and proactive safety analysis methods are unable to investigate. In SUperSAFE, I will select the relevant variables drew on the newly identified risks posed by CAVs, and with these I will develop a new proactive method based on surrogate measures of safety for studying the effects of the physical and digital infrastructure on the interaction between road users in a mixed-mobility environment. Also considering the benchmarks for cities liveability and transport sustainability that include road casualties as a primary factor, the European White Paper on Transport calls to reach zero fatalities by 2050 following Vision Zeros policy (zero serious casualties). Recent statistics indicate a reduction of traffic accidents but also that this development has slowed and additional efforts are required. At the same time, CAVs are already a reality. Tendency towards vehicle automation is even more evident in the European policies which encourage member states to push with the introduction of vehicles with advanced driver assistance systems. However, the road towards full automation is still not open because there is a fear of crashes/injuries and low acceptance of potential CAV accidents. This is mainly because the CAVs behaviour vis-a-vis the conventional vehicles on the road and the digital and physical infrastructure is still unknown. To meet these rapidly approaching needs, I propose SUperSAFE, which will contribute to attaining the aforementioned European goals by developing a scientifically rigorous method of estimating risk based on the road users real needs to improve traffic safety in the transition period to fully automated driving.""

Consortium (1)

Project Results (5)

Source: CORDIS, the EU research results database.

Publications (4)
A Simulator Study on the Driver Failure and Traffic Conflict in Lane Change Situation on 2+1 Road
Adjunct Proceedings of the 16th International Conference on Automotive User Interfaces and Interactive Vehicular Applications· 2024DOI
Sara Hong, Carl Johnsson, Carmelo D'Agostino, Ji Hyun Yang
Comparison of E-Scooter and Bike Users Behavior in Mixed Traffic
Transportation Research Record: Journal of the Transportation Research Board· 2024DOI
Natalia Distefano, Salvatore Leonardi, Mariusz Kie, Carmelo DAgostino
Distributions conditioned on extrapolated events via copula and extreme value theory
MethodsX· 2024DOI
Zhankun Chen, Carl Johnsson, Carmelo D'Agostino
Stochastic method based on copulas for predicting severe road traffic interactions
Analytic Methods in Accident Research· 2024DOI
Zhankun Chen, Oksana Yastremska-Kravchenko, Aliaksei Laureshyn, Carl Johnsson, Carmelo D’Agostino
Deliverables (1)
Documents, reports