2021
DOI: 10.31234/osf.io/f2wsa
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Variable-drift diffusion models of pedestrian road-crossing decisions

Abstract: Human behavior and interaction in road traffic is highly complex, with many open scientifi?c questions of high applied importance, not least in relation to recent development efforts toward automated vehicles. In parallel, recent decades have seen major advances in cognitive neuroscience models of human decision-making, but these models have mainly been applied to simplified laboratory tasks. Here, we demonstrate how variable-drift extensions of drift diffusion (or evidence accumulation) models of decision-mak… Show more

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Cited by 5 publications
(15 citation statements)
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“…Early yield acceptance We use the term early yield acceptance to refer to the tendency of pedestrians to sometimes accept the gap in front of a yielding vehicle before the vehicle has come to a full stop [51][52][53]. We defined a scenario where the modelled pedestrian was initially standing at the kerb (as defined earlier), while the car was initially driving at its free speed at a TTA of 2 s, and applied a constant deceleration to yield to the pedestrian.…”
Section: Yield Acceptance Hesitationmentioning
confidence: 99%
“…Early yield acceptance We use the term early yield acceptance to refer to the tendency of pedestrians to sometimes accept the gap in front of a yielding vehicle before the vehicle has come to a full stop [51][52][53]. We defined a scenario where the modelled pedestrian was initially standing at the kerb (as defined earlier), while the car was initially driving at its free speed at a TTA of 2 s, and applied a constant deceleration to yield to the pedestrian.…”
Section: Yield Acceptance Hesitationmentioning
confidence: 99%
“…Thus, future research should consider how eHMIs may enhance the impact of kinematic cues, such as edging or slow moving behaviour, in real world situations or around different types of junctions. The implementation of explicit AV communication is likely to reduce the frustration of both road user types, and enhance throughput and traffic flow (Pekkanen et al, 2021).…”
Section: Discussionmentioning
confidence: 99%
“…An important feature of the sensorimotor control framework on which we base our model [23] is that it assumes that sensorimotor decisions are made not deterministically as described above, but by accumulation of noisy sensory evidence to a decision threshold, in line with extensive research in decision theory [40]. This assumption has proven crucial for describing full probability distributions of driver behavior in both routine and near-crash situations [23]- [26], and has also been recently adopted in models of pedestrian and driver road-crossing decisions [27]- [30]. We incorporate evidence accumulation into our framework by generalizing the deterministic decision variable above to the stochastically accumulated decision variable.…”
Section: ) Stochastic Action Decisionsmentioning
confidence: 99%
“…We incorporate evidence accumulation into our framework by generalizing the deterministic decision variable above to the stochastically accumulated decision variable. This generalization thus enables the probabilistic human errors that might happen in nearcrash situations [30].…”
Section: ) Stochastic Action Decisionsmentioning
confidence: 99%
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