Accurate understanding of driver behaviour is crucial for future Advanced Driver Assistance Systems (ADAS) and autonomous driving. For user acceptance it is important that ADAS respect individual driving styles and adapt accordingly. Using data collected during a naturalistic driving study carried out at the University of Southampton, we assess existing models of driver acceleration and speed choice during car following and when cornering. We observe that existing models of driver behaviour that specify a preferred inter-vehicle spacing in car-following situations appear to be too prescriptive, with a wide range of acceptable spacings visible in the naturalistic data. Bounds on lateral acceleration during cornering from the literature are visible in the data, but appear to be influenced by the minimum cornering radii specified in design codes for UK roadway geometry. This analysis of existing driver models is used to suggest a small set of parameters that are sufficient to characterise driver behaviour in car-following and curve driving, which may be estimated in real-time by an ADAS to adapt to changing driver behaviour. Finally, we discuss applications to adaptive ADAS with the objectives of improving road safety and promoting eco-driving, and suggest directions for future research
Adaptive driver modelling in ADAS to improve user acceptance: A study using naturalistic data
Lot, Roberto
2018
Abstract
Accurate understanding of driver behaviour is crucial for future Advanced Driver Assistance Systems (ADAS) and autonomous driving. For user acceptance it is important that ADAS respect individual driving styles and adapt accordingly. Using data collected during a naturalistic driving study carried out at the University of Southampton, we assess existing models of driver acceleration and speed choice during car following and when cornering. We observe that existing models of driver behaviour that specify a preferred inter-vehicle spacing in car-following situations appear to be too prescriptive, with a wide range of acceptable spacings visible in the naturalistic data. Bounds on lateral acceleration during cornering from the literature are visible in the data, but appear to be influenced by the minimum cornering radii specified in design codes for UK roadway geometry. This analysis of existing driver models is used to suggest a small set of parameters that are sufficient to characterise driver behaviour in car-following and curve driving, which may be estimated in real-time by an ADAS to adapt to changing driver behaviour. Finally, we discuss applications to adaptive ADAS with the objectives of improving road safety and promoting eco-driving, and suggest directions for future researchFile | Dimensione | Formato | |
---|---|---|---|
2018 Adaptive driver modelling in ADAS to improve user acceptance.pdf
accesso aperto
Tipologia:
Preprint (submitted version)
Licenza:
Accesso gratuito
Dimensione
1.86 MB
Formato
Adobe PDF
|
1.86 MB | Adobe PDF | Visualizza/Apri |
Pubblicazioni consigliate
I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.