Planet Braitenberg: Experiments in virtual psychology

Braitenberg vehicles are simple robotic platforms, equipped with rudimentary sensor and motor components. Such vehicles have typically featured as part of thought experiments that are intended to show how complex behaviours are apt to emerge from the interaction of inner control mechanisms with aspects of bodily structure and features of the wider (extra-agential) environment. The present paper describes a framework for creating Braitenberg-like vehicles, which is built on top of a widely used and freely available game engine, namely, the Unity game engine. The framework can be used to study the behaviour of virtual vehicles within a multiplicity of virtual environments. All aspects of the vehicle’s design, as well as the wider virtual environment in which the vehicle is situated, can be modified during the design phase, as well as at runtime. The result is a general-purpose simulation capability that is intended to provide the foundation for studies in so-called computational situated cognition—a field of study whose primary objective is to support the computational modelling of cognitive processes associated with the physically-embodied, environmentally-embedded, and materially-extended mind.     

Analysis of overtaking patterns of Indian drivers with data collected using a LiDAR

Vehicle overtaking is a complex maneuver on highways and high-speed arterials. When overtaking occurs in heterogeneous traffic conditions, it becomes even more challenging due to the variety of different vehicle sizes and operating characteristics. This study analyzes overtaking behavior on Indian highways under high vehicle heterogeneity. Data were collected using LiDAR and video cameras from an instrumented vehicle. Overtaking times for both sides of overtaking and for different types of vehicles were analyzed. This study introduces a new variable, “excess distance,” to understand overtaking. The results show that on divided four-lane roads, the side of overtaking plays an important role in determining overtaking behavior. On undivided two-lane roads, the type of overtaken vehicle is found to be significant. It is observed, as expected, that while overtaking at higher speeds, overtaking vehicles maintained greater excess distances with the overtaken vehicle. However, data shows that the rate of change of excess distance depends upon the type of road and the type of overtaking vehicle. The analysis also shows that overtaking behavior on undivided roads is affected by the presence of oncoming vehicles and the type of overtaken vehicle.     

Impressions after an automated mobility experience: An acceptance study

This paper presents people’s impressions after a demonstration of a fully robotized electric vehicle in Rambouillet, a peri-urban area connected with rural sections in France. 155 participants experienced a 6.5 km ride that included driving in a narrow two-way road, negotiating roundabouts, traversing a tunnel and interacting with other users of the road such as vehicles, pedestrians and cyclists. 298 impressions from 114 respondents were collected from a written questionnaire and open interviews. Users’ comments were classified in categories as follows: system capabilities, purpose and benefits, travel destination and encouraging remarks. Major results show that participants felt safe, where only 1.01% of comments denoted apprehension despite the increase of speed (up to 50 km/h) with respect to other studies. Users’ were satisfied with the automated vehicle (AV) performance, where only 3.5% criticized the system, denoting they expected a higher level of autonomy. 22% of users mentioned train stations as useful application (i.e. potential destination) for an automated on-demand mobility service. More than 200 comments were related to travel destinations, pointing towards various scenarios where an AV service could be useful for them. Conclusions show that realistic vehicle speed increases passenger acceptance of automated vehicles, increasing system confidence with respect to previous studies in the field.     

Effects of mode distinction,user visibility,and vehicle appearance on mode confusion when interacting with highly automated vehicles

Automated vehicles are expected to communicate with pedestrians at least during the introductory phase, for example, via LED strips, displays, or loudspeakers. While these are added to minimize confusion and increase trust, the human passenger within the vehicle could perform motions that a pedestrian could misinterpret as opposing the vehicle’s communication. To evaluate potential solutions to this problem, we conducted an online video-based within-subjects experiment (N = 59). The solutions under evaluation were mode distinction, vehicle appearance, and the visibility of the passenger via a tintable windshield. Our results show that especially the mode distinction and the conspicuous sensor attached to the automated vehicle showed positive effects. A tintable windshield, however, was negatively assessed. Thus, our work helps to design eHMI concepts to introduce automated vehicles safely by informing about feasible methods to avoid mode confusion.     

CONCEPT MAPPING AS A FEMINIST RESEARCH METHOD

A method used in program evaluation and public health research called concept mapping is examined in this article for its usefulness in feminist research. This method embodies several defining characteristics of feminist social science. Concept mapping is a single method that integrates qualitative and quantitative approaches, provides an opportunity for participants to work together as a group to develop an understanding of a concept, and places the participants in control of interpretation. Over the course of a six-step process, a group of people are assembled to discuss an issue or concept, moving toward a group understanding of that concept, which is then represented in a visual picture, or map. Concept mapping was used in the current study to examine how community resources for sexual-assault victims could be improved. A national random sample of 168 rape-victim advocates provided ideas as to how the legal, medical, and mental health systems could better serve victims. A subgroup of advocates then constructed and interpreted a concept map. The map suggested that rape victims still face many problems in seeking community help. Twelve clusters of broad-based and specific system changes were identified (e.g., fighting victim blaming, community education, sensitizing medical staff, legal reform). Implications for research on sexual assault and feminist research methodology are discussed.     

Audiovisual time-to-collision estimation for accelerating vehicles: The acoustic signature of electric vehicles impairs pedestrians' judgments

To avoid collisions, pedestrians intending to cross a road need to accurately estimate the time-to-collision (TTC) of an approaching vehicle. For TTC estimation, auditory information can be considered particularly relevant when the approaching vehicle accelerates. The sound of vehicles with internal combustion engine (ICEVs) provides characteristic auditory information about the acceleration state (increasing rotational speed and engine load). However, for electric vehicles (EVs), the acoustic signature during acceleration is less salient. Although the auditory detection of EVs has been studied extensively, there is no research on potential effects of the altered acoustic signature of EVs on TTC estimation. To close this gap, we compared TTC estimates for ICEVs and for EVs with and without activated acoustic vehicle alerting system (AVAS). We implemented a novel interactive audiovisual virtual-reality system for studying the human perception of approaching vehicles. Using acoustic recordings of real vehicles as source signals, the dynamic spatial sound field corresponding to a vehicle approaching in an urban setting is generated based on physical modeling of the sound propagation between vehicle and pedestrian (listener) and is presented via sound field synthesis (higher-order Ambisonics). In addition to the auditory simulations, the scene was visually presented on a head-mounted display with head tracking. Participants estimated the TTC of vehicles that either approached at a constant speed or accelerated positively. In conditions with constant speed, TTC estimates for EVs with and without AVAS were similar to those for ICEVs. In contrast, for accelerating vehicles, there was a substantial effect of the vehicle type on the TTC estimates. For the EVs, the mean TTC estimates showed a significant overestimation. Thus, subjects on average perceived the time of arrival of the EV at their position as longer than it actually was. The extent of overestimation increased with acceleration and presented TTC. This pattern is similar to a first-order TTC estimation representing a failure to consider the acceleration, which is consistently reported in the literature for visual-only presentations of accelerating objects. In comparison, the overestimation of TTC was largely reduced for the accelerating ICEVs. The AVAS somewhat improved the TTC estimates for the accelerating EVs, but without reaching the same level of accuracy as for the ICEVs. In real traffic scenarios, overestimations of the TTC of approaching vehicles might lead to risky road-crossing decisions. Therefore, our finding that pedestrians are significantly less able to use the acoustic information emitted by accelerating EVs for their TTC judgments, compared to accelerating ICEVs, has important implications for road safety and for the design of AVAS technologies.     

Evaluating the influence of approaching vehicles on pedestrian’s visual patterns and crossing behaviors at an uncontrolled crosswalk

The visual behaviors and movement characteristics of pedestrians are related to their surrounding potential safety hazards, such as approaching vehicles. This study primarily aimed to investigate the visual patterns and walking behaviors of pedestrians interacting with approaching vehicles. Field experiments were conducted at two uncontrolled crosswalks located at the Cuihua and Yanta roads in Xi’an, China. The visual performance of pedestrians was assessed using the eye tracking system from SensoMotoric Instruments (SMI). Moreover, motion trajectories of the pedestrians and approaching vehicles were obtained using an unmanned aerial vehicle. Subsequently, the visual attributes and movement trajectories of pedestrians and motion trajectories of approaching vehicles were statistically analyzed. The results showed that approaching vehicles distracted the fixation of crossing pedestrians significantly, and occupied 29.5% of the total duration of fixation; that is, pedestrians always directed more fixation points to the approaching vehicles compared to other stimuli. As a vehicle approached, pedestrians’ fixation shifted from other areas of interest to the vehicle. Moreover, an increase in the velocity of the vehicle and a closer distance between pedestrian and the vehicle resulted in an increase in the pedestrians’ duration of fixation on the approaching vehicle, and they implemented more saccades. Furthermore, approaching vehicle’s velocity and distance between pedestrian and approaching vehicle are not significantly associated with pedestrian’s movement attributes. These findings provide insights into the crossing behavior of pedestrians during pedestrian-vehicle interactions, which could assist future researchers and policy makers.     

Control of a virtual vehicle influences postural activity and motion sickness

Everyday experience suggests that drivers are less susceptible to motion sickness than passengers. In the context of inertial motion (i.e., physical displacement), this effect has been confirmed in laboratory research using whole body motion devices. We asked whether a similar effect would occur in the context of simulated vehicles in a visual virtual environment. We used a yoked control design in which one member of each pair of participants played a driving video game (i.e., drove a virtual automobile). A recording of that performance was viewed (in a separate session) by the other member of the pair. Thus, the two members of each pair were exposed to identical visual motion stimuli, but the risk of behavioral contagion was minimized. Participants who drove the virtual vehicle (drivers) were less likely to report motion sickness than participants who viewed game recordings (passengers). Data on head and torso movement revealed that drivers tended to move more than passengers, and that the movements of drivers were more predictable than the movements of passengers. Before the onset of subjective symptoms of motion sickness movement differed between participants who (later) reported motion sickness and those who did not, consistent with a prediction of the postural instability theory of motion sickness. The results confirm that control is an important factor in the etiology of motion sickness and extend this finding to the control of noninertial virtual vehicles.     

Can driving condition prompt systems improve passenger comfort of intelligent vehicles? A driving simulator study

The main trend in the development of intelligent vehicles has been on ensuring comfort, safety, efficiency, and environmental sustainability. However, current research focuses primarily on the safety and energy saving of intelligent vehicles, and a comfortable driving experience through a human–machine interaction system has not been sufficiently investigated. This study used a high-fidelity 6-degree-of-freedom driving simulator to evaluate the impact of an independently-designed vehicle driving condition prompt (DCP) systems on subjective passenger comfort and motion sickness. The experiment showed that when future driving information is obtained through the vehicle DCP systems, the passengers' subjective comfort is improved, motion sickness is alleviated, and the degree of passenger posture instability is reduced. These conclusions contribute toward improving the comfort of autonomous vehicles and providing a reference for the future design of human–machine interaction systems for intelligent vehicles.     

Modeling and prediction of driver preparations for making a right turn based on vehicle velocity and traffic conditions while approaching an intersection

This paper focuses on modeling and predicting the influence of a vehicle’s velocity and the relative position between a driver’s vehicle and a vehicle to the front or rear on the onset of driver preparations for making a right turn at an intersection. Repeated experiments were carried out on a public road to measure driver preparations, including releasing the accelerator pedal, moving the right foot to cover the brake pedal, and activating the turn signal, as well as to record vehicle velocity and the relative distances to the leading and following vehicles. Structural equation modeling was applied to estimate these relationships quantitatively. Two separate latent variables accounting for the interaction between the driver’s vehicle and leading or following vehicles, and the onset point where driving behavior changes from straight mode to preparation mode before a right turn, were introduced in the specification of the structural equation model. The model estimates and testing indicate that the proposed structural equation model represents well the relationship hypothesized by observational analysis: that the vehicle velocity and the traffic conditions surrounding the driver’s vehicle strongly influence the driver’s deceleration and more weakly influenced turn signal activation. The proposed structural equation model contributes to the prediction of the onset locations of covering the brake pedal and activating the turn signal based on the vehicle velocity and the relative distances to the front and rear vehicles when the accelerator pedal is released. The prediction accuracy is high compared with predictions in which the vehicle velocity and the headway or rear distances are not taken into account or predictions using a single regression model with one independent variable, namely driving speed. Finally, a possible new addition to in-vehicle navigation systems that detects unusual driver behavior by predicting the driver’s preparatory maneuvers is discussed.     

Pedestrians’ road crossing behaviour in front of automated vehicles: Results from a pedestrian simulation experiment using agent-based modelling

The objective of this research is to explore the relation between personal characteristics of pedestrians and their crossing behaviour in front of an automated vehicle (AV). For this purpose, a simulation experiment was developed using Agent-Based Modelling (ABM) techniques. Sixty participants were asked to cross the road in a virtual environment displayed on a computer screen, allowing to record their crossing behaviour when in the presence of AVs and conventional vehicles (CVs). In some experimental configurations, the AVs communicated their intention to continue or not to continue their trajectories through the use of lights. The ABM allowed controlling the behaviour of the vehicles when interacting with the simulated avatar of the respondents. The subjects of the experiment were also asked to fill in a questionnaire about usual behaviour in traffic, as well as attitudes and risk perceptions toward crossing roads. The questionnaire data were used to estimate individual specific behavioural latent variables by means of principal component analysis which resulted in three main factors named: violations, lapses, and trust in AVs. The results of generalized linear mixed models applied to the data showed that besides the distance from the approaching vehicle and existence of a zebra crossing, pedestrians’ crossing decisions are significantly affected by the participants’ age, familiarity with AVs, the communication between the AV and the pedestrian, and whether the approaching vehicle is an AV. Moreover, the introduction of the latent factors as explanatory variables into the regression models indicated that individual specific characteristics like willingness to take risks and violate traffic rules, and trust in AVs can have additional explanatory power in the crossing decisions.     

Fimbria/fornix lesions facilitate the learning of a nonspatial response task

The spatial cognitive map theory of O’Keefe and Nadel (1978) predicts that lesions of the hippocampal system should impair learning on spatial tasks but not learning on nonspatial tasks. However, there is evidence that such lesions can facilitate learning on certain nonspatial tasks. Their theory does not predict such facilitation. Nevertheless, it is reasonable to expect that animals possessing a spatial cognitive map would have an inherent bias to engage a mapping strategy and thus be at a disadvantage on certain nonspatial tasks in comparison with animals without the mapping capacity and bias. In the present study, fimbria/fornix lesions impaired learning on a spatial task, but actually facilitated learning on a nonspatial task of equal difficulty. Thus, brain lesions that interfere with map functioning can facilitate learning on tasks for which a mapping strategy interferes with task solution. The results require a modification of the spatial cognitive map theory.     

Driving manoeuvre during lane maintenance in older adults: Associations with neuropsychological scores

Older drivers experience difficulties in lane maintenance under challenging driving sections due to age-related cognitive declines, yet there is little comprehensive evidence on associations between cognitive functions and the lane maintenance in this population. In this study, fifty older drivers completed an on-road driving assessment and a battery of standard neuropsychological tests. Mean Lane Position (MLP), Standard Deviation of Lane Position (SDLP) and manoeuvre time calculated from precise vehicle movement trajectories were used as the lane maintenance parameters. The GNSS tracking vehicle movement presents comprehensive and reliable vehicle position data, which is more sensitive for detecting subtle variations of lane maintenance in older drivers. Statistical analysis results showed that lower visual attention (selective and divided attention) was associated with higher MLP and SDLP; MLP was also correlated to spatial abilities, executive function, and motor speed; manoeuvre time was negatively correlated with drivers’ risk-taking personality (all p < .01). Selective attention was found to be the best predictor of MLP in lane maintenance. A combined eight variables from three neuropsychological tests, UFOV 2 and 3, BD and BJLO, D-KEFS TMT 1, 2, 3, and 4, correctly classified 80.4% of participants with good versus low-performing lane maintenance.     

External communication of automated vehicles in mixed traffic: Addressing the right human interaction partner in multi-agent simulation

The urban traffic system is most likely to change in the next years to a mixed traffic with human drivers, vulnerable road users, and automated vehicles. In the past, the development of external communication approaches for automated vehicles focused on scenarios where an automated vehicle communicates with either a pedestrian or a human driver. However, interactions with more than one traffic partner are more realistic. Therefore, a study with 42 participants was conducted with a multi-agent simulation in which an automated vehicle interacted simultaneously with two participants, a pedestrian and a driver of a manual vehicle. In this study, two main scenarios were investigated in order to evaluate the safety and efficiency of the interactions and to determine whether the human road users feel correctly addressed. In one scenario, the pedestrian had to cross the road in front of the automated and the manual vehicle, which were approaching from different sides. In the other, the manual vehicle had to drive through a bottleneck in front of the oncoming automated vehicle, while the pedestrian had to cross the road after both vehicles passed. The communication approach of the automated vehicle consisted of implicit signals using a speed profile and lateral offset within its lane, and explicit signals using an external human–machine interface. The results of the study show that no collisions were observed in terms of safety and no significant negative effects on efficiency were measured. However, in contrast to single agent interactions, a majority of participants felt wrongly addressed in situations where the automated vehicle signals the right-of-way to the other human road user. It can be concluded that the communication approach of the automated vehicle needs to be modified in order to address certain road users more clearly.     

Investigating the impact of a novel active gap metering signalization strategy on driver behavior at highway merging sections

A safe headway to the lead vehicle is important to reduce conflicts with merging vehicles from highway on-ramps. Previous research has outlined the advantage of gap metering strategies to yield sufficient space to merging vehicles and improve highway capacity during peak hours. However, prevailing gap metering systems fail to indicate the minimum required gap and leave it to the drivers’ judgment to adjust their headway. This paper proposes a new Active Gap Metering (AGM) signalization that helps outer lane drivers to adjust their headway to the lead vehicle when approaching highway ramps with incoming vehicles. This AGM signalization represents a combination of pavement markings and an innovative Variable Message Sign (VMS). The AGM system was tested alone and in combination with additional variable speed limits (VSL) in distinct environments of the Doha Expressway in the State of Qatar using a driving simulator. The driving behavior of 64 drivers was analyzed using repeated-measures ANOVA. The results showed that the AGM effectively influenced the drivers’ behavior on the right stream lane. Drivers did gradually increase the distance to the lead vehicle, which resulted in optimal headways to merging on-ramp vehicles. Most importantly, the minimum time-to-collision (TTC_min) to the merging vehicle was increased by an additional 1–1.5 s as compared to no treatment. The proposed AGM signalization can, therefore, be considered by policymakers to influence drivers’ headways at critical merging sections.     

A driving simulator study to assess driver performance during a car-following maneuver after switching from automated control to manual control

A review of the literature on autonomous vehicles has shown that they offer several benefits, such as reducing traffic congestion and emissions, and improving transport accessibility. Until the highest level of automation is achieved, humans will remain an important integral of the driving cycle, which necessitates to fully understand their role in automated driving. A difficult research topic involves an understanding of whether a period of automated driving is likely to reduce driver fatigue rather than increase the risk of distraction, particularly when drivers are involved in a secondary task while driving. The main aim of this research comprises assessing the effects of an automation period on drivers, in terms of driving performance and safety implications. A specific focus is set on the car-following maneuver. A driving simulator experiment has been designed for this purpose. In particular, each participant was requested to submit to a virtual scenario twice, with level-three driving automation: one drive consisting of Full Manual Control Mode (FM); the other comprising an Automated Control Mode (AM) activated in the midst of the scenario. During the automation mode, the drivers were asked to watch a movie on a tablet inside the vehicle. When the drivers had to take control of the vehicle, two car-following maneuvers were planned, by simulating a slow-moving vehicle in the right lane in the meanwhile a platoon of vehicles in the overtaking lane discouraged the passing maneuver. Various driving performances (speeds, accelerations, etc.) and surrogate safety measures (PET and TTC) were collected and analysed, focusing on car-following maneuvers. The overall results indicated a more dangerous behavior of drivers who were previously subjected to driving automation; the percentage of drivers who did not apply the brakes and headed into the overtaking lane despite the presence of a platoon of fast-moving vehicles with unsafe gaps between them was higher in AM drive than in FM drive. Conversely, for drivers who preferred to brake, it was noted that those who had already experienced automated driving, adopted a more careful behavior during the braking maneuver to avoid a collision. Finally, with regard to drivers who had decided to overtake the braking vehicle, it should be noted that drivers who had already experienced automated driving did not change their behavior whilst overtaking the stopped lead vehicle.     

Influence of traffic conditions on driver behavior before making a right turn at an intersection: Analysis of driver behavior based on measured data on an actual road

This paper describes an investigation of the influence of the position of a forward vehicle and following vehicle on the onset of driver preparatory behavior before making a right turn at an intersection. Four experimental vehicles with various sensors and a driving recorder system were developed to measure driver behavior before making a right turn at a specific intersection on a public road. The experimental term was eight weeks to collect data on natural driving maneuvers. The relationships between the remaining distances to the center of the intersection when releasing the accelerator pedal, moving the right foot to cover the brake pedal, and activating the turn signal and the relative distances from the forward and following vehicles were analyzed based on the measured data. The time it took to reach the center of the turn and the driving speed when each behavioral event occurred were also evaluated from the viewpoint of the relative position between the driver’s vehicle and the leading or following vehicles. The results suggest that the drivers approached the target intersection in a car-following condition, and that the positions of the front and rear vehicles and the vehicle velocity influence the onset location and timing of releasing the accelerator pedal and covering the brake pedal. Drivers began to decelerate closer to the center of the intersection when they approached the intersection close to a leading or following vehicle at a reduced driving speed. However, these influences were not reflected in the turn signal operation, indicating that drivers intend to make a right turn at a constant location while approaching a target intersection and that intention appears in the turn signal activation. The findings of this observational study imply that the method of providing route guidance instruction, in which the traffic conditions surrounding the driver’s vehicle are taken into consideration, is effective in reducing driver errors in receiving instruction and following the correct route. The results also indicate that measuring and accumulating different behavioral indices based on traffic conditions contribute to determining the criteria for the presentation timing just before reaching the intersection, which can assist drivers in preparing to make a right turn at a usual location. Driver decelerating maneuvers are used while driving without leading or following vehicles and while driving with a lead and/or following vehicle at long range, and driver turn signal operations are used when approaching an intersection under close car-following conditions.     

Use of a driving simulator to assess performance under adverse weather conditions in adults with albinism

Participants with albinism have reduced vision and nystagmus with reduced foveation times. This prospective study evaluated driving in 12 participants with albinism and 12 matched controls. Participants drove a vehicle simulator through a virtual rural course in sunny and foggy conditions. Under sunny conditions, participants with albinism showed a narrower preferred minimum safety boundary during car-following tasks than did controls, but there was no difference under foggy conditions. Their driving did not differ significantly from that of controls when approaching a stop sign or when choosing gap size between oncoming vehicles when crossing an intersection. However, when compared to control drivers, participants with albinism had a decreased minimum safety boundary for car-following that should be included in counseling regarding driving safety.     

Children’s mapping between symbolic and nonsymbolic representations of number

When children learn to count and acquire a symbolic system for representing numbers, they map these symbols onto a preexisting system involving approximate nonsymbolic representations of quantity. Little is known about this mapping process, how it develops, and its role in the performance of formal mathematics. Using a novel task to assess children’s mapping ability, we show that children can map in both directions between symbolic and nonsymbolic numerical representations and that this ability develops between 6 and 8 years of age. Moreover, we reveal that children’s mapping ability is related to their achievement on tests of school mathematics over and above the variance accounted for by standard symbolic and nonsymbolic numerical tasks. These findings support the proposal that underlying nonsymbolic representations play a role in children’s mathematical development.     

Cyclist strategies and behaviour at intersections. Conscious and un-conscious strategies regarding positioning

Severe and even fatal accidents between cyclists and motor vehicles commonly occur at intersections. Many of these accidents occur with right-turning vehicles, with drivers not observing an adjacent cyclist. Few structured investigations exist regarding the interaction between cyclist and motor vehicle, and factors in need of study are how infrastructure and vehicle properties affect human decision-making and cycling behaviour. Therefore, a bicycle simulator study was performed, where vehicle type, presence of lane markings and lane width were systematically varied in a scenario with a cyclist approaching a vehicle from behind, at a signalized city intersection. 33 participants cycled through 8 intersection variants each. Data on cycling trajectories, stopping points and speed was coupled with survey data from the participants, and semantically categorized verbal responses to questions regarding strategy for choice of stopping point. Results show that all three factors (vehicle type, lane markings and available vehicle-adjacent space) significantly affects cyclists’ behaviour and conscious strategies. Participants were more cautious in the presence of a truck than a car, reflected in choice of position when cycling and stopping, and in explicit verbalisations regarding perilous aspects of the situation and their conscious and strategic choice of positioning. Available lateral space also affected stop positions and feeling of safety (expressed verbally). Presence of bicycle lane markings made the cyclists inclined to continue into the space to the right of the vehicle. This was revealed by their positioning and speed, and also apparent in the verbal expressions, especially the positive remarks on the situation and conditions. However, the perceived comfort with lane markings present was actually lower than when they were missing. Cyclist type (slow, moderate, or fast) matters with the self-reported faster cyclists being more prone to stop to the right than the slower one.