Lane change manoeuvres and safety margins

The relation between perceptual information and the motor response during lane-change manoeuvres was studied in a fixed-based driving simulator. Eight subjects performed 48 lane changes with varying vehicle speed, lane width and direction of movement. Three sequential phases of the lane change manoeuvre are distinguished. During the first phase the steering wheel is turned to a maximum angle. After this the steering wheel is turned to the opposite direction. The second phase ends when the vehicle heading approaches a maximum that generally occurs at the moment the steering wheel angle passes through zero. During the third phase the steering wheel is turned to a second maximum steering wheel angle in opposite direction to stabilize the vehicle in the new lane. Duration of the separate phases were analysed together with steering amplitudes and Time-to-Line Crossing in order to test whether and how drivers use the outcome of each phase during the lane change manoeuvre to adjust the way the subsequent phase is executed. During the first phase the time margin to the outer lane boundary was controlled by the driver such that a higher speed was compensated for by a smaller steering wheel amplitude. Due to this mechanism the time margin to the lane boundary was not affected by vehicle speed. During the second phase the speed with which the steering wheel was turned to the opposite direction was affected by the time margins to the lane boundary at the start of the second phase. Thereafter, smaller minimum time margins were compensated for by a larger steering wheel amplitude to the opposite direction. The results suggest that steering actions are controlled by the outcome of previous actions in such a way that safety margins are maintained. The results also suggest that visual feedback is used by the driver during lane change manoeuvres to control steering actions, resulting in flexible and adaptive steering behaviour. Evidence is presented in support of the idea that temporal information on the relation between the vehicle and lane boundaries is used by the driver in order to control the motor response.     

A comparison of experienced and novice drivers’ rear-end collision avoidance maneuvers under urgent decelerating events

A leading vehicle’s sudden deceleration can lead to a rear-end collision. Due to a lack of driving experience, novice drivers have a greater tendency to be involved in these accidents. Most previous studies have examined driver response time and braking behaviors, but few researchers have focused on what experienced and novice drivers did after their feet touched the braking pedal and their hands turned the steering wheel. These braking and steering parameters are essential in understanding driver avoidance behavior during emergencies. We programmed rear-end crash risk scenarios to examine experienced and novice drivers’ behaviors thoroughly using a driving simulator. Twenty experienced and twenty five novice subjects participated in our experiments, and their braking and steering maneuvers were recorded when leading vehicles ran at 60 km/h, 80 km/h and 100 km/h. The results showed that the two groups of subjects tended to execute two kinds of maneuvers to avoid crashes: braking only (novice 33%, experienced 19%) and the combination of braking with steering (novice 22%, experienced 26%). When the novice drivers executed braking with steering, their response time and steering duration were significantly longer than those of the experienced drivers who executed braking with steering. As the speed increased, the novice drivers’ response time, maximum braking force and maximum steering angle were significantly affected. These results showed that novice drivers should brake only when the leading vehicle suddenly decelerates. The experienced drivers executed steadier maneuvers. Their risk perception time was shorter, and their maximum braking force and the maximum steering angles were smaller. The response time, braking intensity and steering wheel angle should be considered when developing rear-end collision warning systems.     

Measuring perceived risk: Self-reported and actual hand positions of SUV and car drivers

This research examines the observed steering wheel hand positions and the reported steering wheel hand placements of a sample of Sports Utility Vehicle (SUV) and car drivers. Following the method of Walton and Thomas (Walton, D. & Thomas, J. A. (2005). Naturalistic observations of driver hand positions. Transportation Research Part F. Traffic Psychology and Behaviour, 8, 229–238), variation in hand position is found to be an effective, indirect measure of drivers’ perceived risk. As perceived risk increases, it is expected that drivers will be more likely to adopt a ‘10–2 o’clock’ hand placement to increase their control over the vehicle. Because they are a larger vehicle, SUVs are typically perceived by drivers as being safe, so it is also expected that SUV drivers would have a lower level of perceived risk, as evidenced by their hand positions. A questionnaire examining drivers’ hand placements confirmed that drivers do perceive that two hands on the top half of the steering wheel will give the most control over the vehicle, and also revealed that drivers overestimate their use of this hand position, when compared with actual observation. Observed hand positions reveal that SUV drivers are more likely to drive with one hand instead of two hands on the top half of the steering wheel, indicating a lower level of perceived risk.     

Obstacle avoidance under automated steering: Impact on driving and gaze behaviours

Within the context of more and more autonomous vehicles, an automatic lateral control device (AS: Automatic Steering) was used to steer the vehicle along the road without drivers’ intervention. The device was not able to detect and avoid obstacles. The experiment aimed to analyse unexpected obstacle avoidance manoeuvres when lateral control was delegated to automation. It was hypothesized that drivers skirting behaviours and eye movement patterns would be modified with automated steering compared with a control situation without automation. Eighteen participants took part in a driving simulator study. Steering behaviours and eye movements were analysed during obstacle avoidance episodes. Compared with driving without automation, skirting around obstacles was found to be less effective when drivers had to return from automatic steering to manual control. Eye movements were modified in the presence of automatic steering, revealing further ahead visual scanning of the driving environment. Resuming manual control is not only a problem of action performance but is also related to the reorganisation of drivers’ visual strategies linked to drivers’ disengagement from the steering task. Assistance designers should pay particular attention to potential changes in drivers’ activity when carrying out development work on highly automated vehicles.     

Safety of bicyclists in roundabouts with mixed traffic: Video analyses of behavioural and surrogate safety indicators

Although converting an intersection into a roundabout has been shown to result in fewer injury accidents for both motor vehicle drivers and pedestrians, the effect on bicyclists’ safety is unclear or even negative. This study focuses on roundabouts without bicycle facilities (i.e., mixed traffic conditions) and makes use of semi-automated video observation software with the aim of analysing bicyclists’ behaviour and safety on roundabouts with different diameter. Four urban roundabouts in Belgium are observed. Interactions between bicyclists and other vehicles are analysed using speed, lateral position and five indicators to describe the closeness of interactions (TTC_min, PET, T_{2 min}, lateral overtaking proximity and minimum distance headway). Additionally, the lateral position and riding speed of bicyclists that are in interaction with other vehicles is compared with the behaviour of bicyclists that are not in interaction with other vehicles.The behavioural analysis revealed that regardless of the type of condition (free-flow bicyclists or different interactions bicyclist-car), bicyclists always ride faster on roundabouts with big diameter and slower on roundabouts with small diameter. Moreover, bicyclists ride closer to the central island on roundabouts with big diameter compared to roundabouts with small diameter for all the conditions analysed.The analysis of surrogate safety indicators (TTC_min, PET, T_{2 min}) revealed that close interactions between bicyclists and cars are relatively frequent at both small and big roundabouts. The percentages of close interactions are more or less equal for roundabouts with big diameter (7.86% of observed interactions) and roundabouts with small diameter (8.24%). The analysis of the indicators to describe the closeness of interactions also showed that the closest interactions at roundabouts are all situations where the bicyclist has a leading role. The analysis of the most common types of close interactions revealed indeed that the most common close interactions are interactions where the bicyclist is entering the roundabout. The analysis of lateral overtaking proximity showed that bicyclists who overtake a car take smaller lateral overtaking proximities compared to cars overtaking a bicyclist. The analysis of minimum distance headway finally revealed that bicyclists who ride behind a car take smaller distance headways compared to cars driving behind a bicyclist.     

Effect of time pressure on steering control of the drivers in a car-following situation

The current study focused on analyzing steering control of the drivers during a car-following situation under increasing time pressure conditions. A driving simulator experiment was conducted on ninety-two participants to assess steering performance measures. Five different steering control measures: Variability in Steering Angle (VSA), Steering Reversal Rate (SRR), Steering Speed (SS), Stability of Steering Control (SSC), and Maximum Steering Swerve (MSS) were examined under No Time Pressure (NTP), Low Time Pressure (LTP), and High Time Pressure (HTP) driving conditions. Repeated measures ANOVA (for continuous data) and Friedman’s test (count data) with post-hoc analysis and Generalized Estimating Equation (GEE) modeling technique were used to investigate the influence of time pressure and different predictor variables. The statistical analysis showed that time pressure driving conditions significantly affected steering control of the drivers. The pairwise comparison of time pressure conditions revealed that HTP significantly affected most of the steering control measures as compared to LTP. Further, a GEE model also exhibited similar results where steering control measures were substantially influenced by HTP as compared to LTP. Moreover, in addition to time pressure conditions, demographic characteristics showed significant influence on steering control measures. The GEE model results showed that female drivers performed 13% more steering corrections (5° SRR) which led to better SSC by 124.44% than male drivers. Additionally, it was discovered that young-aged and experienced drivers took extra steering efforts to control lateral position of the vehicle by increasing 53.50% SS and 1% SRR compared to middle-aged and inexperienced drivers. The findings from the current study revealed that drivers undergo fast and abrupt steering maneuvers under time pressure conditions. The research approach demonstrated in the current study can be beneficial to discriminate minimum requirement of steering efforts and set-up threshold values for various steering evasion techniques to control and maintain safe lateral position during car-following maneuvers.     

Driver hand position on the steering wheel while merging into motorway traffic

It has been suggested that a driver’s hand position on the steering wheel can reflect the perceived risk of the road context (Walton, D., & Thomas, J. A. (2005). Naturalistic observations of driver hand positions. Transportation Research Part F, 8, 229–238, Thomas, J. A., & Walton, D. (2007). Measuring perceived risk: Self-reported and actual hand positions of SUV and car drivers. Transportation Research Part F, 10, 201–207). These original studies were based on field observations where only a part of the steering wheel could be viewed. In the present study hand positions were observed in a driving simulator during the performance of a demanding task; merging into motorway traffic. In the current study the whole steering wheel could be observed and hand positions were classified in three categories: high control, medium control, and low control. Differences in hand position between different traffic conditions were limited, and hand position did not correlate with self-reported risk or self-reported mental effort, but changes in hand positions do seem to be associated with changes in workload demand. It is therefore concluded that hand position can give some information about mental workload.     

Driver performance effects of simultaneous visual and cognitive distraction and adaptation behavior

Driver distraction has become a major concern for transportation safety due to increasing use of infotainment systems in vehicles. To reduce safety risks, it is crucial to understand how fundamental aspects of distracting activities affect driver behavior at different levels of vehicle control. This study used a simulator-based experiment to assess the effects of visual, cognitive and simultaneous distraction on operational (braking, accelerating) and tactical (maneuvering) control of vehicles. Twenty drivers participated in the study and drove in lead-car following or passing scenarios under four distraction conditions: without distraction, with visual distraction, with cognitive distraction, and with simultaneous distraction. Results revealed higher perceived workload for passing than following. Simultaneous distraction was most demanding and also resulted in the greatest steering errors among distraction conditions during both driving tasks. During passing, drivers also appeared to slow down their responses to secondary distraction tasks as workload increased. Visual distraction was associated with more off-road glances (to an in-vehicle device) and resulted in high workload. Longer headway times were also observed under visual distraction, suggesting driver adaptation to the workload. Similarly, cognitive distraction also increased driver workload but this demand did not translate into steering errors as high as for visual distraction. In general, findings indicate that tactical control of a vehicle demands more workload than operational control. Visual and cognitive distractions both increase driver workload, but they influence vehicle control and gaze behavior in different ways.     

Naturalistic observation of drivers’ hands, speed and headway

Drivers’ hands position have been shown to vary with traffic speed and complexity of the driving environment, such that drivers are more likely to place two hands on the top half of the steering wheel as the supposed driving difficulty increases (Walton, D. & Thomas, J. A. [2005]. Naturalistic observations of driver hand positions. Transportation Research Part F, 8, 229–238). This research evaluates drivers’ hands positions, examining the reliability of the measure and the relationship between the positions of the driver’s hands, vehicle speed, vehicle headway and driver sex. The findings show that the observed positions of drivers’ hands have good inter-rater reliability and demonstrate both temporal and contextual reliability. The positions of drivers’ hands are related to other measures, such that drivers with lower-ranked positions of hands are more likely to travel at higher speeds and accept shorter headways. Female drivers are found to be 2.87 times more likely than males to place two hands rather than one hand on the top half of the steering wheel.     

Driver conflict response during supervised automation: Do hands on wheel matter?

Securing appropriate driver responses to conflicts is essential in automation that is not perfect (because the driver is needed as a fall-back for system limitations and failures). However, this is recognized as a major challenge in the human factors literature. Moreover, in-depth knowledge is lacking regarding mechanisms affecting the driver response process. The first aim of this study was to investigate how driver conflict response while using highly reliable (but not perfect) supervised automation differ for drivers that (a) crash or avoid a conflict object and (b) report high trust or low trust in automation to avoid the conflict object. The second aim was to understand the influence on the driver conflict response of two specific factors: a hands-on-wheel requirement (with vs. without), and the conflict object type (garbage bag vs. stationary vehicle). Seventy-six participants drove with highly reliable but supervised automation for 30 min on a test track. Thereafter they needed to avoid a static object that was revealed by a lead-vehicle cut-out. The driver conflict response was assessed through the response process: timepoints for driver surprise reaction, hands-on-wheel, driver steering, and driver braking. Crashers generally responded later in all actions of the response process compared to non-crashers. In fact, some crashers collided with the conflict object without even putting their hands on the wheel. Driver conflict response was independent of the hands-on-wheel requirement. High-trust drivers generally responded later than the low-trust drivers or not at all, and only high trust drivers crashed. The larger stationary vehicle triggered an earlier surprise reaction compared to the garbage bag, while hands-on-wheel and steering response were similar for the two conflict object types. To conclude, crashing is associated with a delay in all actions of the response process. In addition, driver conflict response does not change with a hands-on-wheel requirement but changes with trust-level and conflict object type. Simply holding the hands on the wheel is not sufficient to prevent collisions or elicit earlier responses. High trust in automation is associated with late response and crashing, whereas low trust is associated with appropriate driver response. A larger conflict object trigger earlier surprise reactions.     

Driver brake vs. steer response to sudden forward collision scenario in manual and automated driving modes

In autonomous vehicle operation, situations may arise when the driver is required to re-engage in manual control of the vehicle. Whether the control handoff from vehicle to human is done in a structured or unstructured manner, the process may be affected by the driver’s state, i.e. distracted or not. The study reported here was designed to measure a non-distracted driver’s response to a sudden forward collision (FC) event, in which the driver would assume manual control of the autonomous vehicle. Three driving scenarios were investigated: autonomous vehicle driven with full collision avoidance support, autonomous vehicle driven without collision avoidance support, and vehicle driven in manual mode.Forty-eight volunteers participated in a simulator study conducted in VIRTTEX. It was found that, at handoff, (1) drivers in manual mode tended to use evasive steering, rather than braking, compared to drivers in both the autonomous modes, (2) between subjects variations in speed were higher for the automation with collision support condition than for the other two scenarios, (3) for both autonomous driving scenarios, drivers reaction times were longer than for manual driving. In some cases the driver response was so late and the distance remaining so reduced that crash avoidance might be unfeasible. At a minimum, results of this study suggest that drivers may benefit from appropriate driver assistance technologies when a crash imminent situation is suddenly encountered.     

Measured increases in steering entropy may predict when performance will degrade: A driving simulator study

We investigated the effect of time-on-task on driver’s mental workload and driving performance during a simulated driving task. The extent of mental workload was estimated from steering entropy, while driver performance was measured from the Standard Deviation of Lateral Position (SDLP) and the Standard Deviation (SD) Sterring Angle. Seventeen participants underwent a simulated highway driving task for 60 min. The results show that mental workload increased significantly after 15 min, whereas driving performance did not degrade until 30 min. These results suggest that when drivers first affected by time-on-task, they can cope with the situation by increasing mental effort investment and can manage to perform normally for a while (15 min). Since changes in steering entropy precede changes in driving performance, this measure of mental workload may have utility as a predictor of increased accident risk.     

Analysis of vehicle-based lateral performance measures during distracted driving due to phone use

Distracted driving due to mobile phone use has been identified as a major contributor to accidents; therefore, it is required to develop ways for detecting driver distraction due to phone use. Though prior literature has documented various visual behavioural and physiological techniques to identify driver distraction, comparatively little is known about vehicle based performance features which can identify driver’s distracted state during phone conversation and texting while driving. Therefore, this study examined the effects of simple conversation, complex conversation, simple texting and complex texting tasks on vehicle based performance parameters such as standard deviation of lane positioning, number of lane excursions, mean and standard deviation of lateral acceleration, mean and standard deviation of steering wheel angle and steering reversal rates (for 1°, 5° and 10° angle differences). All these performance measures were collected for 100 licensed drivers, belonging to three age groups (young, mid-age and old age), with the help of a driving simulator. Effects of all the phone use conditions and driver demographics (age, gender and phone use habits) on the measures were analysed by repeated measures ANOVA tests. Results showed that 1°, 5° SRRs are able to identify all the distracted conditions except for simple conversation; while, 10° SSR can detect all the distracted conditions (including simple conversation). The results suggest that 10° SRR can be included in intelligent in-vehicle devices in order to detect distraction and alert drivers of their distracted state. This can prevent mobile phone use during driving and therefore can help in reducing the road accidents due to mobile phone distractions.     

Aggressive driving: Do driving overconfidence and aggressive thoughts behind the wheel,drive professionals off the road?

Aggressive driving has emerged as one of the most studied behaviors in the traffic psychology context due to its association with odds of motor vehicle crashes (MVCs) and especially fatal ones. Nevertheless, behavioral (aggression) and affective (anger) aspects of aggressive driving have been deeply studied; its cognitive part hasn’t gained much attention; However, its role in understanding the process of aggression and designing interventions couldn’t be neglected. This research investigated the contribution of overconfidence (as the driver’s cognitive bias), aggressive thoughts, driver’s aggression, and risk perception in driver’s performance and the number of self-reported active accidents. The unique contribution of this study is its sample of urban bus drivers that have less been studied to date. Structural equation modeling (SEM), and mediation analysis revealed that overconfidence contributes to aggressive driving through aggressive thoughts behind the wheel. Moreover, overconfidence decreased the risk perception and driving performance of individuals, which were associated with a higher number of driver’s accidents. Besides, aggressive thoughts behind the wheel predicted physically aggressive expression and using the vehicle to express anger, which were associated with a decreased level of driving performance and an increased number of accidents. This study brings further evidence, supporting the importance of cognition in understanding and preventing aggressive driving and its adverse outcomes.     

A diary study of distracted driving behaviours

The introduction and uptake of technology within road vehicles has readily advanced the capabilities and the functions that the driver of a road vehicle has available to them. While this has benefited the drivers’ productivity and entertainment behind the wheel, it has also heightened the possibility for distraction. Research into driver distraction to date has identified how technologies inside the vehicle may be used ineffectively and can compromise the safety of the road transport system. Yet, the factors that drivers state impact on their decision to engage with distracting technologies are less well known. This paper presents the first diary study into driver distraction. The study asked drivers to record all technological distractions that they engaged with across a 4-week period, as well as interactions that they ignored or choose not to engage with. The diary entries include the technologies drivers interacted with and the conditions surrounding this, as well as external factors that drivers cited to influence their decision to interact. Primarily, factors relating to the task itself were found to be of most importance to the drivers’ decision to engage. Differences were also found in how drivers stated they compensated for any engagement with distracting tasks. This has important consequences for the design and integration of technological devices into the vehicle. The novel application of the method offers insights into the naturalistic conditions surrounding drivers’ involvement with distracting technologies. The method is also reviewed on its applicability to the study of driver distraction.     

Supporting the changing driver’s task: Exploration of interface designs for supervision and intervention in automated driving

Driving automation leads to a changing role for drivers, that is from manual vehicle control to supervising automation. Supervision of partial automation requires now and then intervention. Since the automation causes low vigilance and out-of-the-loop performance problems, this changing role is not well suited for human operators. To explore how driver-vehicle interfaces can support drivers in their changed role, we tested three concepts. Concept A was a baseline reference, providing only acoustic warnings. Concept B presented status-information and warnings behind the steering wheel. Concept C used illumination and haptic feedback in the seat-pan to direct attention outside the vehicle and to stimulate response. Concept C only provided vibrotactile feedback when intervention was needed. Results of our study show improved support for supervision with the illumination-concept, i.e. better hazard-detection and raised levels of Situation Awareness in some scenarios relevant for supervisory control. Knowing that supervision will be the dominating driver’s responsibility during partially automated driving, the illumination-concept is a recommended solution for support of the driver’s changing role. Nonetheless, neither concept B, nor C, showed additional support for intervention compared to the baseline. It was hypothesised that the combination of concept C’s stimuli for intervention-support caused counter-productive levels of annoyance. Furthermore, we concluded that intervention and supervision benefit from different interface-features and discussed possible causes underlying ambiguity between support for supervision and support for intervention shown with concept C. Therewith, the considerations in this paper contribute to further development of – and knowledge about – appropriate driver-vehicle interaction while vehicle-operation advances into operating partially automated driving systems.     

Physiological indicators of driver workload during car-following scenarios and takeovers in highly automated driving

This driving simulator study, conducted as a part of Horizon2020-funded L3Pilot project, investigated how different car-following situations affected driver workload, within the context of vehicle automation. Electrocardiogram (ECG) and electrodermal activity (EDA)-based physiological metrics were used as objective indicators of workload, along with self-reported workload ratings. A total of 32 drivers were divided into two equal groups, based on whether they engaged in a non-driving related task (NDRT) during automation (SAE Level 3) or monitored the drive (SAE Level 2). Drivers in both groups were exposed to two counterbalanced experimental drives, lasting ∼ 18 min each, of Short (0.5 s) and Long (1.5 s) Time Headway conditions during automated car-following (ACF), which was followed by a takeover that happened with or without a lead vehicle. Results showed that driver workload due to the NDRT was significantly higher than both monitoring the drive during ACF and manual car-following (MCF). Furthermore, the results indicated that a lead vehicle maintain a shorter THW can significantly increase driver workload during takeover scenarios, potentially affecting driver safety. This warrants further research into understanding safe time headway thresholds to be maintained by automated vehicles, without placing additional cognitive or attentional demands on the driver. Our results indicated that ECG and EDA signals are sensitive to variations in workload, which warrants further investigation on the value of combining these two signals to assess driver workload in real-time, to help future driver monitoring systems respond appropriately to the limitations of the driver, and predict their performance in the driving task, if and when they have to resume manual control of the vehicle after a period of automated driving.     

Driver glance behavior towards displayed images on in-vehicle information systems under real driving conditions

Intelligent vehicle technologies like driver assistance systems and in-vehicle information systems, enhance convenience of the driving experience for drivers and passengers. At the same time, these systems may increase driver distraction and workload. Guidelines developed for this purpose include principles, methods, and assessments which are widely agreed upon, with some being singled out for a particular recommendation or requirement. Especially the display of graphical or photographic images are generally assumed to distract the driver from safely operating the vehicle and should be blocked during driving under all circumstances (so called per se lock outs). This study investigates the effect of displaying graphical and photographical images during driving on driveŕs glance behavior during real-world driving. Findings presented in this paper provide empirical evidence for the unobtrusiveness of these stimuli: Participants didn’t exhibit longer glance durations towards in-vehicle information systems, nor a deterioration of driver distraction parameters such as total eyes off road time and long glance proportion when being compared to driving without displaying any photographic images.     

Compensating for failed attention while driving

While operating a motor vehicle, drivers must pay attention to other moving vehicles and the roadside environment in order to detect and process critical information related to the driving task. Using a driving simulator, this study investigated the effects of an unexpected event on driver performance in environments of more or less clutter and under situations of high attentional load. Attentional load was manipulated by varying the number of neighboring vehicles participants tracked for lane changes. After baseline-driving behavior was established, the unexpected event occurred: a pedestrian ran into the driver’s path. Tracking-accuracy, brake initiation, swerving, and verbal report of the unexpected pedestrian were used to assess driver performance. All participants verbally reported noticing the pedestrian. However, analyses of driving behavior revealed differences in the reactions to the pedestrian: drivers braked faster and had significantly less deviation in their steering heading with a lower attentional load, and participants in low clutter environments had a larger overall change in velocity. This research advances the understanding of how drivers allocate attention between various stimuli and the trade-offs between a driver’s focus on an assigned task and external objects within the roadway environment. Moreover, the results of this research lend insight into how to construct roadway environments that encourage driver attention toward the most immediate and relevant information to reduce both vehicle-to-vehicle and vehicle-to-pedestrian interactions.     

Drivers’ and cyclists’ safety perceptions in overtaking maneuvers

Drivers overtaking cyclists on rural roads are a safety concern, as drivers need to handle the interaction with the cyclist and possibly an oncoming vehicle. Improving the maneuver’s outcome requires an understanding of not only the objective, measurable safety metrics, but also the subjective, perceived safety of each road user. Previous research has shown that the perceived safety of the cyclist is most at risk at the passing moment, when driver and cyclist are closest to each other. However, to develop safety measures, it is necessary to know how both road users perceive safety, by understanding the factors that influence their perceptions during the overtaking maneuver. This study measured the perceived safety of drivers in a test-track experiment in Sweden and the perceived safety of cyclists in a field test in Spain. For both drivers and cyclists, we developed Bayesian ordinal logistic regression models of perceived safety scores that take as input objective safety metrics representing the different crash risks at the passing moment. Our results show that while drivers’ perceived safety decreases when there is an oncoming vehicle with a low time-to-collision, cyclists’ perceived safety is reduced by a small lateral clearance and a high overtaking speed. Although our datasets are heterogeneous and limited, our results are in line with previous research. In addition, the Bayesian models presented in this paper are novel and may be improved in future studies once more naturalistic data become available. We discuss how our models may support infrastructure development and regulation, policymaking, driver coaching, the development of active safety systems, and automated driving by providing a possible method for predicting perceived safety.