A comparison of computational driver models using naturalistic and test-track data from cyclist-overtaking manoeuvres
Artikel i vetenskaplig tidskrift, 2020

The improvement of advanced driver assistance systems (ADAS) and their safety assessment rely on the understanding of scenario-dependent driving behaviours, such as steering to avoid collisions. This study compares driver models that predict when a driver starts steering away to overtake a cyclist on rural roads. The comparison is among four models: a threshold model, an accumulator model, and two models inspired by a proportional-integral and proportional-integral-derivative controller. These models were tested and cross-applied using two different datasets: one from a naturalistic driving (ND) study and one from a test-track (TT) experiment. Two perceptual variables, expansion rate (the horizontal angular expansion rate of the image of the lead road user on the driver’s retina) and inverse tau (the ratio between the image’s expansion rate and its horizontal optical size), were tested as input to the models. A linear cost function is proposed that can obtain the optimal parameters of the models by computationally efficient linear programming. The results show that the models based on inverse tau fitted the data better than the models that included expansion rate. In general, the models fitted the ND data reasonably well, but not as well the TT data. For the ND data, the models including an accumulative component outperformed the threshold model. For the TT data, due to the poorer fit of the models, more analysis is required to determine the merit of the models. The models fitted to TT data captured the overall pattern of steering onsets in the ND data rather well, but with a persistent bias, probably due to the drivers employing a more cautious strategy in TT. The models compared in this paper may support the virtual safety assessment of ADAS so that driver behaviour may be considered in the design and evaluation of new safety systems.

Driver behaviour

Linear program

Cyclist

Overtaking

Driver modelling

Författare

Jordanka Kovaceva

Chalmers, Mekanik och maritima vetenskaper, Fordonssäkerhet

Jonas Bärgman

Chalmers, Mekanik och maritima vetenskaper, Fordonssäkerhet, Olycksanalys och prevention

Marco Dozza

Chalmers, Mekanik och maritima vetenskaper, Fordonssäkerhet, Olycksanalys och prevention

Transportation Research Part F: Traffic Psychology and Behaviour

1369-8478 (ISSN)

Vol. 75 87-105

MICA - Modellering av Interaktion mellan Cyklister och Fordon

VINNOVA, 2018-03-09 -- 2019-12-31.

Styrkeområden

Transport

Ämneskategorier

Tillämpad psykologi

Farkostteknik

Reglerteknik

DOI

10.1016/j.trf.2020.09.020

Mer information

Senast uppdaterat

2020-11-20