When taking a curve, drivers follow their own unique trajectory. Most driver style classifiers in literature are based on inertial inputs, denoting whether a given driver is aggressive or calm. However, this does not give any indication of a drivers trajectory style, i.e. whether a driver is curve cutting. To fill this void, this paper introduces a novel rule based classifier that categorises seven different trajectory styles. The classifier is applied to data from a fixed-base driving simulator study in which 45 subjects drove on three roads, comprising three different velocities: 25, 50 and 80 km/h, with three corresponding radii: 20, 80 and 204 m. The results show that some classes are more prevalent than others, with biased outer curve negotiation performed by a majority of the subjects and with no drivers classified as centerline drivers. The proposed trajectory classifier is shown to exhibit high levels of consistency, with 93% of drivers exhibiting consistent trajectory classes for at least 66% of the right curves driven and 84% exhibits consistent trajectory classes for atleast 66% of the left curves driven. Where this consistency indicates a potential for generalising the classification results to other curves. Additionally, this classifier can be used to adapt trajectory-driven advanced driver assistance systems, thereby serving as an alternative to driver modelling.
|Title of host publication||Proceedings of the IEEE International Conference on Systems, Man and Cybernetics (SMC 2019)|
|Place of Publication||Piscataway, NJ, USA|
|Publication status||Published - 2019|
|Event||2019 IEEE International Conference on Systems, Man and Cybernetics, SMC 2019 - Bari, Italy|
Duration: 6 Oct 2019 → 9 Oct 2019
|Conference||2019 IEEE International Conference on Systems, Man and Cybernetics, SMC 2019|
|Period||6/10/19 → 9/10/19|