Auditory Information Improves Time-to-collision Estimation for Accelerating Vehicles

A binary acceleration signal reduces overestimation in pedestrians' visual time-to-collision estimation for accelerating vehicles

When a pedestrian intends to cross the street, it is essential for safe mobility to correctly estimate the arrival time (time-to-collision, TTC) of an approaching vehicle. However, visual perception of acceleration is rather imprecise. Previous studies consistently showed that humans (mostly) disregard acceleration, but judge the TTC for an object as if it were traveling at constant speed (first-order estimation), which is associated with overestimated TTCs for positively accelerating objects. In a traffic context, such TTC overestimation could motivate pedestrians to cross in front of an approaching vehicle, although the time remaining is not sufficiently long. Can a simple acceleration signal help improve visual TTC estimation for accelerating objects? The present study investigated whether a signal that only indicates whether a vehicle is accelerating or not can remove the first-order pattern of overestimated TTCs. In a virtual reality simulation, 26 participants estimated the TTC of vehicles that approached with constant velocity or accelerated, from the perspective of a pedestrian at the curb. In half of the experimental blocks, a light band on the windshield illuminated whenever the vehicle accelerated but remained deactivated when the vehicle travelled at a constant speed. In the other blocks, the light band never illuminated, regardless of whether or not the vehicle accelerated. Participants were informed about the light band function in each block. Without acceleration signal, the estimated TTCs for the accelerating vehicles were consistent with an erroneous first-order approximation. In blocks with acceleration signal, participants substantially changed their estimation strategy, so that TTC overestimations for accelerating vehicles were reduced. Our data suggest that a binary acceleration signal helps pedestrians to effectively reduce the TTC overestimation for accelerating vehicles and could therefore increase pedestrian safety.

Perceptual-Cognitive Integration for Goal-Directed Action in Naturalistic Environments

Real-world actions require one to simultaneously perceive, think, and act on the surrounding world, requiring the integration of (bottom-up) sensory information and (top-down) cognitive and motor signals. Studying these processes involves the intellectual challenge of cutting across traditional neuroscience silos, and the technical challenge of recording data in uncontrolled natural environments. However, recent advances in techniques, such as neuroimaging, virtual reality, and motion tracking, allow one to address these issues in naturalistic environments for both healthy participants and clinical populations. In this review, we survey six topics in which naturalistic approaches have advanced both our fundamental understanding of brain function and how neurologic deficits influence goal-directed, coordinated action in naturalistic environments. The first part conveys fundamental neuroscience mechanisms related to visuospatial coding for action, adaptive eye-hand coordination, and visuomotor integration for manual interception. The second part discusses applications of such knowledge to neurologic deficits, specifically, steering in the presence of cortical blindness, impact of stroke on visual-proprioceptive integration, and impact of visual search and working memory deficits. This translational approach-extending knowledge from lab to rehab-provides new insights into the complex interplay between perceptual, motor, and cognitive control in naturalistic tasks that are relevant for both basic and clinical research.

Camera-Monitor Systems as An Opportunity to Compensate for Perceptual Errors in Time-to-Contact Estimations

For the safety of road traffic, it is crucial to accurately estimate the time it will take for a moving object to reach a specific location (time-to-contact estimation, TTC). Observers make more or less accurate TTC estimates of objects of average size that are moving at constant speeds. However, they make perceptual errors when judging objects which accelerate or which are unusually large or small. In the former case, for instance, when asked to extrapolate the motion of an accelerating object, observers tend to assume that the object continues to move with the speed it had before it went out of sight. In the latter case, the TTC of large objects is underestimated, whereas the TTC of small objects is overestimated, as if physical size is confounded with retinal size (the size-arrival effect). In normal viewing, these perceptual errors cannot be helped, but camera-monitor systems offer the unique opportunity to exploit the size-arrival effect to cancel out errors induced by the failure to respond to acceleration. To explore whether such error cancellation can work in principle, we conducted two experiments using a prediction-motion paradigm in which the size of the approaching vehicle was manipulated. The results demonstrate that altering the vehicle's size had the expected influence on the TTC estimation. This finding has practical implications for the implementation of camera-monitor systems.

Rapid Audiovisual Integration Guides Predictive Actions

Natural movements, such as catching a ball or capturing prey, typically involve multiple senses. Yet, laboratory studies on human movements commonly focus solely on vision and ignore sound. Here, we ask how visual and auditory signals are integrated to guide interceptive movements. Human observers tracked the brief launch of a simulated baseball, randomly paired with batting sounds of varying intensities, and made a quick pointing movement at the ball. Movement end points revealed systematic overestimation of target speed when the ball launch was paired with a loud versus a quiet sound, although sound was never informative. This effect was modulated by the availability of visual information; sounds biased interception when the visual presentation duration of the ball was short. Amplitude of the first catch-up saccade, occurring ∼125 ms after target launch, revealed early integration of audiovisual information for trajectory estimation. This sound-induced bias was reversed during later predictive saccades when more visual information was available. Our findings suggest that auditory and visual signals are integrated to guide interception and that this integration process must occur early at a neural site that receives auditory and visual signals within an ultrashort time span.

Overestimated time-to-collision for quiet vehicles: Evidence from a study using a novel audiovisual virtual-reality system for traffic scenarios

To avoid collision, pedestrians intending to cross a road need to estimate the time-to-collision (TTC) of an approaching vehicle. Here, we present a novel interactive audiovisual virtual-reality system for investigating how the acoustic characteristics (loudness and engine type) of vehicles influence the TTC estimation. Using acoustic recordings of real vehicles as source signals, the dynamic spatial sound fields corresponding to a vehicle approaching in an urban setting are generated based on physical modeling of the sound propagation between vehicle and pedestrian and are presented via sound field synthesis. We studied TTC estimation for vehicles with internal combustion engine and for loudness-matched electric vehicles. The vehicle sound levels were varied by 10 dB, independently of the speed, presented TTC, and vehicle type. In an auditory-only condition, the cars were not visible, and lower loudness of the cars resulted in considerably longer TTC estimates. Importantly, the loudness of the cars also had a significant effect in the same direction on the TTC estimates in an audiovisual condition, where the cars were additionally visually presented via interactive virtual-reality simulations. Thus, pedestrians use auditory information when estimating TTC, even when full visual information is available. At equal loudness, the TTC judgments for electric and conventional vehicles were virtually identical, indicating that loudness has a stronger effect than spectral differences. Because TTC overestimations can result in risky road crossing decisions, the results imply that vehicle loudness should be considered as an important factor in pedestrian safety.

Implicit intention communication as a design opportunity for automated vehicles: Understanding drivers' interpretation of vehicle trajectory at narrow passages

To ensure road safety in mixed traffic, automated vehicles (AVs) must be equipped with distinct and easy-to-understand communication strategies. For this, the communication design of AVs might be oriented toward implicit communication between manually driven vehicles. This research focused on how drivers interpret observable vehicle behavior (vehicle trajectory) to predict vehicle intentions and planned maneuvers. In addition, the processing and interpretation of contradictory cues were examined as a possible cause for misunderstandings and failed coordination. Two video-based experiments investigated the presumed intention (yielding or insisting on priority), intention recognition time, distinctiveness, and cooperativeness of a vehicle's implicit communication at narrow road passages. For this, two vehicles approached a bottleneck from opposite sides, and only one vehicle could pass at a time. The driving behavior of the oncoming vehicle consisted of longitudinal (decelerating, stopping, accelerating, maintaining speed) and lateral movements (driving to the center, driving to the edge of the road, no lateral deviation) at different timings (early, late). The results indicated advantages of lateral vehicle movements for distinct intention communication. Lateral movements were interpreted the fastest, perceived more distinct, and were more decisive for the presumed intention than longitudinal movements. Early communication was preferred by drivers but increased the intention recognition time, especially for longitudinal movements. However, early lateral communication was interpreted as fast as late longitudinal communication. Furthermore, lateral and longitudinal vehicle movements within a driving pattern that contradicted each other led to ambiguous perceptions. For AVs, early distinct communication via lateral vehicle movement is recommended. Minimizing ambiguity in the interpretation of communication cues might maximize the probability of the safest response from human drivers and contribute to accident prevention in mixed traffic.