Jonny Kuo

• PhD
• Researcher at Seeing Machines

Introduction Internal driver events such as emotional arousal do not consistently elicit observable behaviors. However, heart rate (HR) offers promise as a surrogate measure for predicting these states in drivers. Imaging photoplethysmography (IPPG) can measure HR from face video recorded in static, indoor settings, but has yet to be examined in an...

Objective: We aimed to (a) describe the development and application of an automated approach for processing in-vehicle speech data from a naturalistic driving study (NDS), (b) examine the influence of child passenger presence on driving performance, and (c) model this relationship using in-vehicle speech data. Background: Parent drivers frequent...

Naturalistic driving studies (NDS) allow researchers to discreetly observe everyday, real-world driving to better understand the risk factors that contribute to hazardous situations. In particular, NDS designs provide high ecological validity in the study of driver distraction. With increasing dataset sizes, current best practice of manually review...

Driver Readiness (DR) refers to the likelihood of drivers successfully recovering control from automated driving and is correlated with collision avoidance. When designing Driver Monitoring Systems (DMS) it is useful to understand how driver states and DR interact, through predictive modelling of collision probability. However, collisions are rare...

Objective: The paper aims to integrate interior and exterior sensing signals to explore gaze-context connections for more context-aware driver attention management. Background: Driving context is important for crash risk assessment, but little is known about how it modulates attention requirements for developing driver monitoring systems. Method: T...

This paper provides a theoretical overview of how the concept of driver readiness can be objectively measured, using controlled experimental data. First, a literature review regarding the concept of driver readiness is provided. Then, it highlights challenges for a standardized readiness estimation model. A conceptual readiness estimation model is...

This paper reports results from a high-fidelity driving simulator study (N=215) about a head-up display (HUD) that conveys a conditional automated vehicle’s dynamic “uncertainty” about the current situation while fallback drivers watch entertaining videos.We compared (between-group) three design interventions: display (a bar visualisation of uncert...

This paper provides a theoretical overview of how the concept of driver readiness can be objectively measured, using controlled experimental data. First, a literature review regarding the concept of driver readiness is provided. Then, it highlights challenges for a standardized readiness estimation model. A conceptual readiness estimation model is...

Objective: examine the prevalence of driver distraction in naturalistic driving when implementing European New Car Assessment Program (Euro NCAP)-defined distraction behaviours. Background: The 2023 introduction of Occupant Status monitoring (OSM) into Euro NCAP will accelerate uptake of Driver State Monitoring (DSM). Euro NCAP outlines distract...

Understanding whether drivers can accurately assess sleepiness is essential for educational campaigns advising drivers to stop driving when feeling sleepy. However, few studies have examined this in real-world driving environments, particularly among older drivers who comprise a large proportion of all road users. To examine the accuracy of subject...

The aim of this study was to compare the success of two different Human Machine Interfaces (HMIs) in attracting drivers’ attention when they were engaged in a Non-Driving-Related Task (NDRT) during SAE Level 3 driving. We also assessed the value of each on drivers’ perceived safety and trust. A driving simulator experiment was used to investigate d...

Objective The study aims to model driver perception across the visual field in dynamic, real-world highway driving. Background Peripheral vision acquires information across the visual field and guides a driver’s information search. Studies in naturalistic settings are lacking however, with most research having been conducted in controlled simulati...

Objective The study aims to investigate the potential of using HUD (head-up display) as an approach for drivers to engage in non–driving-related tasks (NDRTs) during automated driving, and examine the impacts on driver state and take-over performance in comparison to the traditional mobile phone. Background Advances in automated vehicle technology...

Impaired driving performance due to sleep loss is a major contributor to motor-vehicle crashes, fatalities, and serious injuries. As on-road, fully-instrumented studies of drowsy driving have largely focused on young drivers, we examined the impact of sleep loss on driving performance and physiological drowsiness in both younger and older drivers o...

Recent advances in vehicle technology permit the real-time monitoring of driver state to reduce distraction-related crashes, particularly within the heavy vehicle industry. Relatively little published research has evaluated the human machine interface (HMI) design for these systems. However, the efficacy of in-vehicle technology depends in large pa...

Head pose has been proposed as a surrogate for eye movement to predict areas of interest (AOIs) where drivers allocate their attention. However, head pose may disassociate with AOIs in glance behavior involving zero or subtle head movements, commonly known as “lizard” glance pattern. In contrast, “owl” glance pattern is used to describe glance beha...

Background: An inadequate rest break between shifts may contribute to driver sleepiness. This study assessed whether extending the major rest break between shifts from 7-hours (Australian industry standard) to 11-hours, improved drivers' sleep, alertness and naturalistic driving performance. Methods: 17 heavy vehicle drivers (16 male) were recru...

Objective: This paper aimed to investigate the robustness of driver cognitive workload detection based on electrocardiogram (ECG) when considering temporal variation and individual differences in cognitive workload. Background: Cognitive workload is a critical component to be monitored for error prevention in human-machine systems. It may fluctu...

This paper investigated individual differences in attentional strategies during the non-driving-related tasks in Level 2 automated driving. Ward’s method was used to cluster participants into different groups according to the characteristics of their sequential off-road glances in the email-sorting task: duration, frequency, variance, and intensity...

Objective Research shows frequent mobile phone use in vehicles but says little regarding how drivers hold their phone. This knowledge would inform countermeasures and benefit law enforcement in detecting phone use. Methods 934 participants were surveyed over phone-use prevalence, handedness, traffic-direction, and where they held their device. Re...

Objective This study aimed to investigate the impacts of feature selection on driver cognitive distraction (CD) detection and validation in real-world nonautomated and Level 2 automated driving scenarios. Background Real-time driver state monitoring is critical to promote road user safety. Method Twenty-four participants were recruited to drive a...

Contextual investigations of automated vehicle technology have so far been rare, however they are crucial to uncover the challenges that exist around its acceptance and safe use. Twenty-one drivers used a partially automated vehicle on a public highway in unaltered traffic conditions, while their behaviour was observed. Subjective measures of techn...

Objective The paper aimed to investigate glance behaviors under different levels of distraction in automated driving (AD) and understand the impact of distraction levels on driver takeover performance. Background Driver distraction detrimentally affects takeover performance. Glance-based distraction measurement could be a promising method to remin...

Vehicle automation will fundamentally change what it means to safely operate a vehicle. Future vehicles will afford the driver opportunities to decrease their active control of the vehicle through taking their hands off the wheel and taking their eyes and mind off the road. The components of the driving task, and thus driver behavior and expectatio...

Highly automated vehicles relieve drivers from driving tasks, allowing them to engage in non-driving-related-tasks (NDRTs). However, drivers are required to take over control in certain circumstances due to the limitations of highly automated vehicles. This study focused on drivers’ eye-movement patterns during take-overs when an NDRT (watching vid...

Sleepiness is a major contributor to motor vehicle crashes and shift workers are particularly vulnerable. There is currently no validated objective field-based measure of sleep-related impairment prior to driving. Ocular parameters are promising markers of continuous driver alertness in laboratory and track studies, however their ability to determi...

The safety concerns linked to semi-automated driving – more automation, less driver engagement – could be resolved by real-time driver monitoring with mitigation strategies. To achieve this, this paper analyzed an on-road dataset of sequential off-road glance behaviors under different levels of distraction in an autonomous vehicle trial named CANdr...

To examine the relationship between heavy vehicle driver fatigue, time of day and shift-start times, data from an automatic driver monitoring system (Guardian, Seeing Machines) was assessed for over 140,000 shifts across four different operator companies. Results revealed that of the 2290 fatigue events detected, 63% occurred during the night time...

Drowsiness detection has a significant importance in aviation industry. Electroencephalogram (EEG) has been extensively studied to characterize drowsiness, nevertheless, its behavior with respect to accurately annotated drowsy periods remains to be investigated. At present, Karolinska Sleepiness Scale (KSS) and Psychomotor Vigilance Task (PVT) are...

The aim of this study was to understand driver responses to ''silent" failures in automated driving, where automation failed during a simulator drive, without a takeover warning. The effect of a visual non-driving related task (NDRT) and a road-based vigilance task presented drivers' takeover response and visual attention was also investigated. Cur...

The aim of this study was to understand driver responses to “silent” failures in automated driving, where automation failed during a simulator drive, without a take-over warning. The effect of a visual non-driving related task (NDRT) and a road-based vigilance task presented drivers’ take-over response and visual attention was also investigated. Cu...

Driver drowsiness is a significant public health problem and has previously been linked to an increase in drivers’ propensity to engage in visual distraction. This relationship however has yet to be examined under naturalistic driving conditions, where task demands may differ from lab-based experimental studies. This study aimed to examine the beha...

Cognitive distraction can impair drivers’ situation awareness and control performance in driving. An on-road study was conducted to examine the efficacy in the detection of driver cognitive distraction based on the driver monitoring system developed by Seeing Machines. Participants completed a 25-km test drive on the local public roads whilst engag...

Introduction Child occupant safety in motor-vehicle crashes is evaluated using Anthropomorphic Test Devices (ATD) seated in optimal positions. However, child occupants often assume suboptimal positions during real-world driving trips. Head impact to the seat back has been identified as one important injury causation scenario for seat belt restraine...

This study examined the utility of continuous operator state monitoring in predicting air traffic control officer (ATCO) workload and fatigue. Participants (N=8) were observed in live operational air traffic control environments for 60-minute periods. ATCO state was assessed using a real-time, computer vision-based system which tracked operator gaz...

Objective: Restraint performance is evaluated using anthropomorphic test devices (ATDs) positioned in prescribed, optimal seating positions. Anecdotally, humans-children in particular-assume a variety of positions that may affect restraint performance. Naturalistic driving studies (NDSs), where cameras and other data acquisition systems are placed...

Objective: This pilot study aimed to investigate physiological responses during an on-road driving task for older and younger drivers. Methods: Five older drivers (mean age = 74.60 years [2.97]) and 5 younger drivers (mean age = 30.00 years [3.08]) completed a series of cognitive assessments (Montreal Cognitive Assessment [MoCA], Mini Mental Sta...