The study, published in Frontiers in Built Environment, examined how seven different landscape buffer typologies shaped pedestrians’ perceived walkability across four distinct street contexts. The seven scenarios ranged from a bare concrete strip, the control condition, to lawn, manicured shrubs, and mixed herbaceous plantings described by the authors as biodiverse planting, each of which was also combined with street trees in three further scenarios. Participants rated each scene on five dimensions of perceived walkability: overall satisfaction, safety from crime, aesthetic pleasure, safety from cars, and comfort. These five dimensions are widely used in perception research because they capture the subjective quality of a street environment that objective measurements such as street connectivity or land-use density cannot.

Perceived walkability has become an increasingly important concept in planning and public health research. Compared with purely objective assessments of the built environment, subjective measurements show stronger positive correlations with physical activity levels, the choice to walk rather than drive, and quality of life measures including happiness, social cohesion, and life satisfaction. Perception also leaves room for personal history, travel preferences, values, and culture, all of which objective indices ignore. Yet decades of walkability research have concentrated overwhelmingly on neighborhood-scale attributes such as street network connectivity, land-use density, and land-use diversity, leaving street-level microscale features like planting buffers comparatively understudied despite growing evidence that they can shape walking behavior.

The research team, led by Coryn Brinks with Xiaowei Li, Jun-Hyun Kim, and Zeenat Kotval-Karamchandani, used digitally manipulated photographs of four real sidewalk locations in mid-Michigan, two classified as urban because a building facade sat directly beside the pedestrian path, and two classified as suburban because no adjacent facade existed and the streetscape was more open. Within each of the four settings, the sidewalk alignment and viewpoint were held constant while only the buffer treatment changed. This meant participants compared identical streets where the only difference was the ground cover and planting between the curb and the walkway, producing twenty-eight simulated images in total for the main phase.

Phase I was conducted online between October and November 2024, reaching an estimated 5,353 people through university email lists. The final dataset contained 95 survey records, and the main statistical model analyzed 8,768 ratings from 74 respondents using linear mixed-effects models, Type II Wald chi-square tests, and estimated marginal means. The results were striking in their consistency. The model identified significant main effects of landscape buffer scenario, setting, and perception dimension on walkability ratings, as well as significant two-way and three-way interaction effects among these factors, all at p less than 0.001. In practical terms, the effect of a buffer design depended on both the street context and the perceptual dimension being judged, which the researchers say justifies treating streetscape design as context-sensitive rather than universal.

The ratings climbed steadily from the concrete condition to the vegetated ones, with scenarios containing street trees generally receiving the highest scores. In the suburban setting, the bare concrete buffer received the lowest model-adjusted mean across the five perception dimensions at 1.90, rising to 2.59 for lawn, 3.13 for shrubs, and 3.46 for biodiverse planting, and reaching 4.24 for biodiverse planting combined with street trees, the highest suburban score. The urban scenes followed the same trajectory, from 2.73 for concrete to 4.43 for biodiverse planting with street trees. Notably, urban scenes were rated more positively than suburban scenes for the same buffer design, but the gap between the two settings was largest for the concrete and lawn conditions and smallest once street trees were added, suggesting that trees may help suburban streets close the perceptual distance to their urban counterparts.

The five perception dimensions did not respond identically. Safety from crime tended to receive lower ratings than other dimensions in the more vegetated scenarios, though it was not the lowest dimension in every condition. Safety from cars, by contrast, was generally higher in scenarios with street trees, consistent with the idea that vertical vegetation creates a perceived separation between pedestrians and traffic. The authors caution that this pattern aligns with defensible space theory, which holds that crime-related judgments depend more on visibility, passive surveillance, transparency, maintenance, and activity levels than on planting treatments alone. In other words, greenery can make a street feel pleasant and shielded from cars, but it cannot substitute for the sightlines and openness that make people feel secure from crime.

The theoretical explanation the researchers propose draws on several strands of environmental psychology. Tree canopy and vertical planting define spatial edges, creating a room-like feeling of enclosure that can offer comfort and a better microclimate. The concept of thigmotaxis, the tendency to seek proximity to vertical boundaries, suggests that edges contribute to perceived protection and orientation, while prospect-refuge theory holds that comfortable environments combine protective edges with expansive outward views. At the same time, excessive enclosure can increase vulnerability by limiting surveillance, a warning reflected in the open-ended comments of participants who noted that overly dense planting could feel confining.

Phase II added an exploratory twist: seven returning participants rated the same twenty-eight scenes again, this time in Michigan State University’s Digital Scholarship Lab 360 Room, an immersive visualization space with a wrap-around projection screen. The overall media comparison was not statistically significant, and the authors are careful to stress that a nonsignificant result does not establish that two-dimensional images and immersive projection are interchangeable. Some context-specific differences appeared, with certain suburban scenarios rated higher in the immersive condition and certain urban scenarios rated lower, and safety from crime rising slightly while aesthetic pleasure fell. Because all participants saw the 2D images first and the media order was never randomized, media effects cannot be separated from familiarity, elapsed time, or repeated exposure. Qualitatively, all seven participants found the immersive condition more realistic and easier to interpret at human scale, and most pointed to trees, canopy cover, separation from cars, and open sightlines as the factors that determined their comfort.

The study has clear limitations that the authors lay out candidly. Scenario and setting order were fixed rather than randomized, so the observed gradient from concrete to lushly planted buffers could partly reflect contrast, habituation, expectation, or fatigue rather than design alone. The immersive phase involved only seven self-selected participants, the imagery came from just four mid-Michigan sites, and the respondent pool skewed young, university-based, and design-literate. The biodiverse planting treatment was a visual description rather than a measured biodiversity index, and the study assessed perceptions without observing actual walking behavior, mode choice, or health outcomes. Even so, the findings point toward a practical opportunity, especially for suburbs. Where density, block length, or destination access cannot easily change, planted buffers and street trees may offer a feasible, context-sensitive way to improve how streets feel to pedestrians, and the largest perceptual gains appeared precisely in the suburban scenes that started from the lowest baseline. The authors call for future studies with randomized sequences, counterbalanced media, larger and more diverse samples, and real-world behavioral benchmarks before translating these perceptual patterns into general design prescriptions, but their message to planners is already hard to ignore: the strip of land between curb and sidewalk is not leftover space, and what you plant there may shape whether anyone walks at all.

Subject of Research: Effects of landscape buffer typologies and street trees on perceived walkability in urban and suburban streetscapes

Article Title: Landscape buffers as microscale streetscape design factors for enhancing perceived walkability

Article References: Brinks, C., Li, X., Kim, J.-H., & Kotval-Karamchandani, Z. (2026). Landscape buffers as microscale streetscape design factors for enhancing perceived walkability. Frontiers in Built Environment, 12, Article 1976360. https://doi.org/10.3389/fbuil.2026.1976360

Image Credits: AI Generated

DOI: 10.3389/fbuil.2026.1976360

Keywords: walkability, landscape buffers, street trees, streetscape design, urban planning, perceived safety, suburban design, immersive visualization, environmental perception, pedestrian comfort, microscale design, green infrastructure

The findings come from an unusually direct test of a widely discussed personality trait. Environmental sensitivity, often marketed in popular psychology as the hallmark of the highly sensitive person, is defined as a tendency to feel the effects of both positive and negative experiences more deeply than others do. Highly sensitive individuals are thought to react more strongly to stress and adversity while also drawing greater benefit from supportive relationships and uplifting experiences. Previous work has even linked the trait to genetics: a study of nearly 2,900 teenage twins found that heredity may account for almost half of the variation in how sensitive people are to their surroundings.

But most of that earlier research concentrated on dramatic life events: childhood experiences, trauma, major transitions. Lead author Kim Meidenbauer, an assistant professor of psychology at Washington State University, and her colleagues wanted to know whether heightened sensitivity also extends to the ordinary physical settings people move through every day. To find out, they analyzed more than 3,800 surveys completed by Chicago residents who used a smartphone app to record their emotions in real time and rate the conditions of the outdoor neighborhoods and parks they were visiting.

The results were striking in what they did not show. There was no evidence that the personality trait amplified emotional responses to physical conditions such as air quality, temperature, or noise. A highly sensitive person sweltering on a hot sidewalk or walking past a smelly alley reported essentially the same emotional reaction as anyone else facing the same conditions. The trait simply did not act as an amplifier for the physical world.

What the researchers did find was a powerful social signature. Perceived safety, orderliness, and friendly interactions among nearby people were far more strongly associated with positive emotions in highly sensitive participants than in their less sensitive counterparts. A street littered with trash or covered in graffiti triggered a greater sense of unease in these individuals, while a neighborhood where people greeted each other warmly provided a stronger emotional boost. The sensitivity, in other words, was tuned to human signals rather than to thermal or acoustic ones.

That distinction raises uncomfortable questions about what the standard questionnaire used to identify the trait is actually measuring. If highly sensitive people are not more reactive to physical environments, the instrument may be capturing something closer to social and emotional attunement than to a general responsiveness to surroundings. Scientists, Meidenbauer suggests, may have been measuring a different kind of sensitivity than the name implies, and the popular label of environmental sensitivity could be actively misleading.

For the many people who identify as highly sensitive, the findings carry a reassuring message. Having the trait does not necessarily mean bracing for a stronger emotional response to every aspect of one’s surroundings. As Meidenbauer put it, it seems to be more about social environments than the physical environment. Someone with the trait can walk down a loud, uncomfortable street without expecting to be overwhelmed, provided the social atmosphere feels safe and welcoming.

The researchers are careful to note the limits of their conclusions. The study examined everyday conditions, not extremes. Meidenbauer cautioned that the results do not rule out stronger reactions to dangerous heat, severe air pollution, or other genuinely hazardous conditions, where heightened sensitivity might still play a role. Her laboratory is now investigating whether other personality traits and individual preferences for hot or cold weather can better explain why people respond differently to the same environmental conditions, a line of inquiry that could untangle the confounds the current study exposed.

The broader implication is a reframing of what it means to be highly sensitive at all. Rather than experiencing everything around them more intensely, highly sensitive people may simply be more affected by the human experiences that make a place feel welcoming or threatening: the warmth of strangers, the order of a public space, the visible signs of care or neglect in a neighborhood. If future research confirms this pattern, the trait may need a new name, and the growing community of people who identify as highly sensitive may gain a more accurate understanding of the gift and the burden they actually carry.

Subject of Research: Environmental sensitivity and emotional responses to social versus physical surroundings

Article Title: ‘Highly sensitive’ people may not experience everything more intensely, study suggests

Article References: ‘Highly sensitive’ people may not experience everything more intensely, study suggests. (n.d.). Original publication

Image Credits: AI Generated

DOI: Not provided

Keywords: environmental sensitivity, highly sensitive people, personality psychology, social cues, perceived safety, Journal of Environmental Psychology, Washington State University, emotional reactivity, urban environments, experience sampling, psychology, neighborhoods

The study arrives at a moment of tension in the deployment of self-driving technology. On the technical side, the numbers are impressive. Drawing on prior real-world evidence, the authors note that across 56.7 million rider-only miles, autonomous systems showed crash-rate reductions of roughly 79 percent for injury-reported crashes, 81 percent for airbag-deployment crashes, and 85 percent for suspected serious-injury crashes compared with human benchmarks. Bodily-injury insurance claims in fully driverless operations fell by as much as 92 to 93 percent, and police-reported injury crashes dropped by about 55 percent in some analyses. Since human error contributes to roughly 94 to 95 percent of road collisions, these gains represent a genuine transformation in road safety.

Yet the study argues that functional safety and perceived safety are fundamentally distinct constructs, and that conflating them is a mistake with real consequences for public acceptance. The researchers, led by Anu Masso of Tallinn University of Technology together with colleagues in Hong Kong and Denmark, designed a semi-experimental online study in which participants viewed paired traffic scenarios presented under both autonomous and non-autonomous conditions. The scenarios deliberately featured a wide range of social diversity cues, including gender, age, race operationalized through skin-tone variation, income, disability, and micromobility, grounded in theories of super-diversity and intersectionality. Areas of interest were matched in size and position across paired images to rule out low-level visual saliency as a confound.

Eye tracking was conducted through the RealEye platform, which uses webcam-based AI gaze prediction with an accuracy of roughly 110 pixels. Each trial began with a 40-point calibration and a 9-point validation check, and participants whose calibration errors exceeded 2.5 degrees of visual angle or who failed attention checks were excluded. The primary measure was fixation total time, the cumulative dwell time spent on each social diversity area of interest, chosen for its robustness in webcam-based settings and its interpretability as sustained attentional engagement. Revisit counts served as secondary validation. The team then used Bayesian multilevel regression models, estimated with four Markov Chain Monte Carlo chains in the brms package, to link attention patterns with self-reported safety and security evaluations while accounting for individual and city-level variation.

The first major finding concerns the structure of visual attention itself. Gaze patterns toward social groups proved to be highly organized and remarkably stable across both autonomous and non-autonomous scenarios. Categories such as age, race, and income consistently attracted higher levels of attention in both contexts, while disability-related and COVID-related cues remained comparatively backgrounded. Automation modestly increased overall attention to social cues without fundamentally reshaping these hierarchies. The estimated association between attention indices in the two contexts was moderate, with a beta of approximately 0.66 and a 95 percent confidence interval spanning 0.44 to 0.88, indicating that attentional structure is partially stable but also partially reconfigured by mobility context. In other words, autonomous mobility amplifies existing perceptual salience hierarchies rather than creating new ones.

The surprise came when the researchers connected those gaze patterns to feelings of safety. At the individual level, correlations between visual attention indices and perceived safety or security were weak, with absolute correlation values below 0.2, and scatter plots revealed no clear linear associations. In the final Bayesian models, the key predictor was the difference in attention between autonomous and non-autonomous contexts, and its posterior estimates were centered near zero with credible intervals overlapping zero for both outcomes. Once trust, social positioning, and regional context were accounted for, shifts in visual attention simply did not translate into changes in experienced safety or normative security. Being perceptually alert to social difference, it turns out, is not the same as feeling protected by it.

What did predict perceived safety? Trust emerged as the dominant force. Both general trust in automation, measured across SAE automation Levels 0 through 5, and situational trust in autonomous transport applications showed consistently positive posterior estimates for experienced safety. Notably, trust remained relatively stable across automation levels 0 to 4, with mean scores between 3.40 and 3.49, but dropped to 3.10 for Level 5 full automation, signaling persistent hesitation toward fully driverless systems even among people otherwise comfortable with semi-automated technology. Trust also varied by who was being transported: respondents expressed the highest trust in autonomous vehicles carrying people from rural to urban areas and the lowest in vehicles carrying elderly people to parks, suggesting that acceptance depends on the perceived vulnerability and social status of passengers.

Security values followed a different explanatory logic altogether. Unlike perceived safety, security as a normative principle was less strongly associated with trust and more strongly shaped by social position and cultural context. Minority status, measured through self-identification as belonging to a national minority group, was the most robust individual-level predictor, with minority respondents systematically assigning lower importance to security values and reporting lower perceived safety even after controlling for trust and attention. Regional effects were substantial in both models, with patterns more pronounced for security values than for perceived safety, reinforcing the interpretation that security evaluations are deeply anchored in cultural and institutional environments. Higher perceived safety was generally reported by respondents with higher education and by those living in European and East and Southeast Asian regions, while younger respondents aged 18 to 29 and those in the Americas or Sub-Saharan Africa reported lower levels.

The broader survey results add texture to this picture. Nearly 30 percent of respondents felt that transport safety in their city had remained unchanged over the previous five years, while roughly 55 percent perceived an increase and about 16 percent a decrease, indicating that even perceptions of objective safety trends are filtered through local experience. Meanwhile, security as a public value was overwhelmingly salient: 54.7 percent rated it as very important in the development of AI-based urban technologies, and only 13 percent considered it insignificant. These patterns suggest that while people care intensely about security in the abstract, their concrete feelings of safety in automated mobility are constructed through trust, social identity, and institutional context rather than through what their eyes happen to land on.

The implications for the autonomous vehicle industry and for AI ethics are significant. A widespread assumption holds that making diverse social groups visible and recognizable within mobility environments is sufficient to foster inclusion, trust, and safety. This study challenges that assumption directly. Visual representation may be necessary for functional safety, ensuring that systems reliably detect vulnerable road users, but it does not guarantee psychological reassurance or normative legitimacy. The authors call for complementing safety-by-design with socio-psychological safety-by-design, in which trust calibration, cultural legibility, and social recognition extend beyond what systems detect or display. The study also acknowledges limitations, including the lower spatial precision of webcam-based eye tracking compared with laboratory systems, the possibility that visual stimuli unintentionally encoded stereotypes, and small sample sizes in some cities, which the authors address through partial pooling in their Bayesian models. Future research, they suggest, should combine laboratory-grade eye tracking, in situ mobility experiences, and qualitative approaches to uncover the mediating mechanisms, such as institutional trust and prior experience with automation, that connect perception to judgment. For now, the message is clear: legitimate autonomous mobility will not be won by crash statistics or visible diversity alone, but by the social and institutional conditions under which people come to feel genuinely safe.

Subject of Research: Cross-cultural eye-tracking research on perceived safety and trust in autonomous vehicle environments

Article Title: What shapes perceived safety in autonomous mobility? Cross-cultural evidence from large-scale online eye tracking

Article References: Masso, A., Pietarinen, A.-V., Ibrahimi, M., & Ben Yahia, S. (2026). What shapes perceived safety in autonomous mobility? Cross-cultural evidence from large-scale online eye tracking. AI & SOCIETY. https://doi.org/10.1007/s00146-026-03278-1

Image Credits: AI Generated

DOI: 10.1007/s00146-026-03278-1

Keywords: autonomous vehicles, eye tracking, perceived safety, trust in automation, AI ethics, cross-cultural study, social diversity, Bayesian multilevel models, data justice, minority status, human-machine interaction, urban mobility

The study, led by Lina Schreiber, Henrik Teuber, Hans-Christoph Pape, and Christiane Barthel from the Department of Traumatology at Universitätsspital Zürich, with Barthel also affiliated with Schulthess Klinik in Zurich, set out to answer two deceptively simple questions: how available and structured is trauma bay training for residents, and how do these junior physicians perceive the two dominant educational tools in the field, Advanced Trauma Life Support courses and simulation-based training? ATLS, a standardized, internationally recognized framework developed to systematize the early care of injured patients, has long been considered the backbone of trauma education, while simulation training places teams in realistic, often high-fidelity mock resuscitations where errors can be made and corrected without any risk to a living patient.

To capture the reality on the ground, the researchers designed a cross-sectional, web-based survey that was voluntary and anonymous. Participants were resident physicians involved in trauma bay care across three countries, and the self-developed questionnaire probed their training exposure, their perceived preparedness, and selected organizational aspects of trauma bay management, comparing responses across specialties and training levels. A total of 124 residents completed the survey, a sample that, while modest, spans a meaningful range of hospital environments, from large university centers to smaller regional institutions, and therefore offers a rare window into how educational opportunity is distributed in real-world health systems.

The statistical findings are telling. Participation in ATLS courses or trauma bay simulation training was significantly associated with the type of hospital where a resident worked, with a p-value of 0.033, and with the resident’s training level, at p = 0.002. In practical terms, this means that whether a young doctor has access to formalized trauma education is not simply a matter of personal initiative but is strongly shaped by institutional context and seniority. Residents at certain hospitals and at certain stages of training are systematically more likely to receive structured preparation, while others may face their first real polytrauma resuscitation with little more than observation and on-the-job learning.

Perhaps the most striking number in the study concerns perceived safety. Residents who had attended ATLS courses reported significantly higher self-assessed safety in trauma bay management than those without such training, with mean scores of 3.67 versus 2.91 on the survey scale, a difference the authors report as statistically significant at p = 0.0024. While self-reported confidence is not the same as measured competence, the gap is substantial and aligns with a broader body of literature suggesting that standardized trauma courses translate into providers who feel, and often perform, more securely in the resuscitation room. Earlier work cited by the authors, including long-term follow-up of ATLS programs and systematic reviews of high-fidelity team-based simulation in acute care settings, supports the idea that structured training builds both technical skill and the non-technical abilities, such as communication and leadership, that trauma care demands.

Yet access to that training remains the exception rather than the rule for many residents. Fewer than half of the survey respondents reported having access to regular trauma bay simulation training, a finding that will surprise few who have worked in resource-constrained hospitals but that carries real weight for educators and policymakers. Simulation is expensive and logistically complex: it requires mannequins or in-situ setups, protected time for multidisciplinary teams that include surgeons, anesthesiologists, and emergency physicians, and trained instructors who can debrief effectively. The survey’s data suggest that these resources are concentrated unevenly, leaving the quality of a resident’s trauma education partly dependent on the postal code of their hospital.

The study also examined the quieter, organizational details of trauma bay culture that rarely make headlines but shape daily practice. Functional identification badges, which clarify each team member’s role during a resuscitation, were most commonly used in university hospitals and were viewed positively by 63.0 percent of participants. Supervisory support was generally rated as good or very good, an encouraging signal that senior staff are present and engaged when juniors take on trauma responsibilities. On the more troubling side, unprofessional communication within trauma teams was reported by a minority of respondents, though most described it as occurring rarely. Even infrequent unprofessional behavior in a high-stakes environment is not trivial; crisis resource management research has long emphasized that clear, respectful communication is a safety-critical component of team performance under pressure.

The authors are careful about what their data can and cannot show. As a descriptive, cross-sectional survey, the study captures perceptions and self-reported exposure at a single point in time rather than measuring objective performance or patient outcomes. The association between ATLS participation and perceived safety, for example, could reflect the genuine benefit of the courses, but could also reflect selection effects, since residents at better-resourced institutions may both receive more training and feel more confident for related reasons. Still, the authors argue that these descriptive data provide a foundation for future discussions on how postgraduate trauma education should be organized and delivered, particularly in health systems where trauma bay staffing and training structures vary widely between hospital types.

The findings land at a moment when trauma education is evolving rapidly. The literature the authors draw on includes studies of virtual reality simulation to enhance ATLS training, randomized controlled trials of extended reality simulators, and interprofessional in-situ simulation programs modeled on ATLS principles that have demonstrated measurable learning gains. If immersive technologies continue to lower the cost and logistical barriers of realistic team training, the inequities documented in this survey could become easier to correct, allowing smaller hospitals to offer their residents simulation experiences once reserved for major academic centers. Conversely, without deliberate policy attention, the association between hospital type and training access may persist or widen.

For now, the study’s central message is hard to ignore: a resident’s readiness to manage a crashing polytrauma patient should not be a lottery of institutional circumstance. With fewer than half of surveyed residents reporting regular simulation access, and with ATLS participation clearly linked to greater perceived safety, the authors’ data give educators across Switzerland, Austria, Germany, and beyond a concrete benchmark. The trauma bay will always be an unforgiving classroom, but the survey suggests that with standardized courses, consistent simulation, clear role identification, and supportive supervision, the medical profession can make its steepest learning curve a far safer one for both doctors and the patients who depend on them.

Subject of Research: Simulation-based trauma bay training and ATLS education for resident physicians

Article Title: Advancing trauma training: a survey study on simulation training and trauma bay management for resident doctors

Article References: Schreiber, L., Teuber, H., Pape, H.-C., & Barthel, C. (2026). Advancing trauma training: a survey study on simulation training and trauma bay management for resident doctors. Global Surgical Education – Journal of the Association for Surgical Education, 5(1), Article 128. https://doi.org/10.1007/s44186-026-00533-3

Image Credits: AI Generated

DOI: 10.1007/s44186-026-00533-3

Keywords: trauma bay, simulation-based training, ATLS, resident physicians, polytrauma, medical education, trauma surgery, perceived safety, survey study, residency training, Switzerland, Germany

The framework, called PERSCO, was developed by Sanne van Waveren, Zulfiqar Zaidi, and Matthew Gombolay at the Georgia Institute of Technology. Its central insight is that perceived safety can be treated as a tunable control problem rather than a fixed design choice. The researchers build on control barrier functions, or CBFs, mathematical constructs that guarantee a robot stays within a set of safe states by constraining its control inputs at every time step. Traditional CBFs enforce physical safety with static parameters that never change during an interaction. PERSCO instead parameterizes the CBF with two variables that directly shape how the robot’s behavior feels to nearby humans: the minimum distance the robot must keep from each person, and the maximum deceleration it is allowed to use, which in turn caps how fast it may approach anyone.

These two parameters have intuitive physical meaning. The distance parameter defines an intimate space around each person that the robot may never enter. The deceleration parameter determines the stopping distance the robot must be able to achieve at its current speed; a robot permitted stronger braking can safely travel faster, because it can halt in a shorter distance. By adjusting the pair, the controller can make the robot behave anywhere from maximally cautious to maximally assertive. The key question is which combination a given person actually perceives as safe, and that is something no designer can hard-code in advance, because perceptions vary widely between individuals and contexts.

To answer it, PERSCO treats the problem as active learning. Each person carries a hidden perceived safety function that maps any parameter pair to a judgment of safe or unsafe. The robot cannot observe this function directly, so it maintains a surrogate model, a classifier trained on feedback, and probes the boundary between safe and unsafe parameter regions. Crucially, the researchers designed the feedback to be as unobtrusive as possible. Rather than asking people to fill out Likert scales mid-task, PERSCO adopts a principle of perceived safe until proven unsafe: humans only signal when they feel uncomfortable, using a simple visual cue, in this study a handheld AprilTag sign raised toward a camera. Silence is treated as implicit safe feedback, provided the robot has logged enough close encounters with that person without any complaint.

The learning algorithm is engineered to minimize how often people must intervene. When unsafe feedback arrives, the robot updates its classifier and selects the next candidate parameters using a novel sampling strategy that balances two criteria: entropy, which targets regions where the model is most uncertain about where the boundary lies, and diversity, which favors candidates far from previously tested ones. Importantly, the sampler only considers parameters the model predicts to be safe, so the robot never deliberately behaves in a way it believes will alarm the human. When no unsafe feedback arrives after repeated close encounters, the robot gradually relaxes its parameters, stepping toward the least restrictive pair on the safety boundary, which maximizes task efficiency while remaining at the edge of what the person tolerates.

All of this runs inside a model predictive control loop with a 0.1-second time step, where the perceived safety CBF is enforced over the entire planning horizon while accounting for predicted human motion. A separate, unchanging physical safety CBF with the most aggressive parameters guarantees collision avoidance at all times, so no matter how the learned parameters evolve, the robot can always brake to a standstill before reaching anyone. When parameter updates suddenly tighten the constraints and the robot temporarily finds itself outside the new safe set, a gradual recovery strategy using a slack variable steers it back smoothly; in simulation this reduced jerk by 25 percent and angular acceleration by a factor of 3.6 compared to abrupt corrections, avoiding the jarring sidesteps that quick recovery methods would produce.

Simulation experiments validated the technical choices. Among three candidate classifiers, a support vector classifier with a radial basis function kernel proved the clear winner, updating in about 1.3 milliseconds on average, fast enough for real-time control, while the neural network and Gaussian process alternatives exceeded the control loop’s time budget. Against a battery of classical active learning baselines and black-box optimizers, including multi-armed bandits and Bayesian optimization, PERSCO sampling achieved high accuracy in recovering ground-truth safety parameters while producing the lowest ratio of unsafe feedback events. In a simulated workplace with three moving pedestrians, the system converged to near-optimal parameters in roughly eight minutes, both with and without noise injected into the feedback.

The decisive test came with real humans. Fifty-four participants, organized into eighteen groups of three, performed a workplace-inspired assembly task, walking between workstations to place LED pins on breadboards while a Boston Dynamics Spot robot navigated the space autonomously, covering 7,074 meters over the course of the study. Participants experienced three conditions: individual adaptation, in which the robot learned separate parameters for each person; collective adaptation, in which one shared parameter set was updated from anyone’s feedback; and an adversarial condition, in which the robot responded to feedback by becoming more aggressive rather than more cautious. The adversarial condition served as a control to test whether adaptation itself, or only feedback-aligned adaptation, improves how safe people feel.

The results were striking. Both aligned conditions significantly outperformed the adversarial one on perceived safety, comfort, and anxiety, all with p-values below .001 and large effect sizes. Collective adaptation scored highest overall, and participants raised their feedback signs significantly less often under collective updates, suggesting that people benefit from feedback provided by their teammates. A mediation analysis revealed that the effect of condition on perceived safety was fully mediated by the average size of the robot’s safety boundary, meaning the psychological benefit flowed directly from the geometric changes in the robot’s enforced constraints. Notably, individual adaptation offered no task-performance advantage over collective adaptation, contrary to the researchers’ hypothesis, possibly because fewer parameter changes allowed the robot to plan more consistently.

The authors are candid about limitations: the study took place in a controlled environment, sessions were capped at twelve minutes so parameters did not always converge, and treating silence as safe feedback assumes people are attentive enough to complain when they feel threatened. Still, the work marks a meaningful shift in how roboticists think about safety. By framing perceived safety as a quantity that can be measured, learned, and optimized alongside task performance, PERSCO argues that true safety encompasses psychological well-being, not just the absence of collisions. As robots move into warehouses, hospitals, and factories, the systems that earn human trust may be the ones that ask, in effect, how their presence feels, and adjust accordingly.

Subject of Research: Perceived-safe control of mobile robots using active learning from human feedback

Article Title: PERSCO: Perceived safe control of mobile robots in human groups with active learning

Article References: van Waveren, S., Zaidi, Z., & Gombolay, M. (2026). PERSCO: Perceived safe control of mobile robots in human groups with active learning. Autonomous Robots, 50(4), Article 43. https://doi.org/10.1007/s10514-026-10262-7

Image Credits: AI Generated

DOI: 10.1007/s10514-026-10262-7

Keywords: perceived safety, human-robot interaction, control barrier functions, active learning, mobile robots, model predictive control, social robotics, human-aware motion planning, adaptive control, Boston Dynamics Spot, user study, machine learning

The research team set out to test a proposition that urbanists have debated for decades: does changing the built environment actually change how safe people feel, and does it do so equitably across genders? Rather than relying on a single case study, the investigators synthesized evidence on design interventions, ranging from improved lighting and sightline management to the activation of vacant spaces and the redesign of pedestrian routes, and evaluated how these measures influenced reported fear of crime among men and women. Their analysis points to a consistent pattern: well-executed interventions reduce fear, but the size and character of that reduction depend on the specific needs and experiences of the users being considered.

At the technical heart of the study lies the distinction between crime itself and the perception of crime. Official victimization statistics capture only a fraction of the ways in which insecurity structures urban life. Fear of crime operates continuously, altering route choices, compressing the hours during which people feel comfortable outside, and imposing what researchers call a mobility tax, an invisible cost paid disproportionately by women. The study emphasizes that fear is not irrational; it is shaped by cues in the environment, including darkness, enclosure, visual isolation, signs of neglect, and the absence of other people. Because fear responds to environmental cues, it is, in principle, modifiable through design.

Lighting emerges as one of the most robust levers. The evidence reviewed indicates that improvements to the quality, uniformity, and placement of lighting can substantially lower fear, particularly along walking routes, transit access points, and underpasses where darkness compounds other stressors. But the authors caution against treating lighting as a panacea. Uniformly bright floodlighting can create glare, deepen shadows at their edges, and signal that a space is dangerous enough to require fortification. Gender-sensitive design, by contrast, treats lighting as part of a broader legibility strategy: illuminating the paths people actually take, lighting entrances and vertical circulation in parking structures and stations, and ensuring that light reaches eye level, where faces become recognizable and social presence becomes perceptible.

Sightlines and spatial configuration form a second pillar of the findings. Enclosed, convoluted spaces with limited visibility, under bridges, behind walls, along blank facades, reliably generate higher fear scores, especially among women respondents. Interventions that open up views, remove visual obstructions, introduce passive surveillance through overlooking windows and active street frontages, and avoid dead-end configurations reduce the sense of being trapped or unobserved. The study frames this in the language of prospect and refuge: people feel safest where they can see and be seen, while potential threats thrive in spaces that offer concealment. Design that maximizes prospect while minimizing anonymous refuge aligns the geometry of a place with the psychology of its users.

A third strand concerns activity and social presence. Vacant lots, boarded storefronts, and empty plazas communicate abandonment, and abandonment is read as risk. Interventions that activate space, through markets, food vendors, community programming, or simply through design that invites lingering, such as seating, shade, and accessible amenities, populate places with the ordinary social traffic that reassures passersby. The study notes that this mechanism is deeply gendered: women’s fear often centers on social disorder and the absence of help rather than on the statistical probability of assault, so interventions that increase the visible presence of other people, and especially of people likely to intervene, deliver fear reduction that lighting alone cannot achieve.

What distinguishes this analysis is its insistence that interventions be evaluated through a gender lens rather than assumed to be gender-neutral. Women and men report fear of crime at different intensities, in different locations, and in response to different cues. Men’s fear tends to concentrate around specific hotspots and nighttime contexts, whereas women report a more diffuse, ambient insecurity that shapes everyday routines, including during daylight hours. Interventions that reduce fear for men may leave this ambient anxiety untouched if they address only the most conspicuous hazards. The study therefore advocates participatory safety audits, in which women residents walk routes, identify stress points, and co-produce design responses, as a methodological complement to top-down planning. Gender-sensitive urbanism, in this framing, is not a niche concern but a diagnostic discipline that reveals where generic design fails.

The policy implications are considerable. Fear of crime suppresses the use of public transport, discourages walking and cycling, and depresses the economic life of streets after dusk. Because fear concentrates along predictable spatial patterns, poorly lit transit approaches, isolated underpasses, blank-walled corridors, municipalities can target investments with precision, achieving fear reduction at costs far below those of major infrastructure projects. The study’s gender-sensitive framing also gives cities a defensible basis for prioritizing interventions: if women’s mobility is constrained more severely than men’s, then design that disproportionately benefits women’s freedom of movement produces the largest gains in aggregate urban access and equity.

The authors are careful to delineate limits. Fear reduction is not crime reduction, and the two must not be conflated. Design interventions can redistribute offending toward less protected targets, a displacement effect that requires monitoring, and they cannot substitute for policing, social services, or the structural reforms that address violence at its roots. Moreover, perception studies must be interpreted with care, since reported fear reflects cultural context, media exposure, and personal history as much as physical environment. Yet the core result stands: when cities change the cues that environments emit, the people who move through them report feeling measurably safer, and the benefits can be tracked and differentiated by gender.

Ultimately, the study reframes fear of crime as a designable variable rather than a fixed feature of urban life. Streets that are lit where people walk, legible where they turn, watched where they linger, and animated where they pass through are not merely more pleasant; they extend the practical freedom of the people, and especially the women, who have long paid the mobility tax of urban insecurity. In an era when cities compete for density, sustainability, and livability, the evidence assembled here makes the case that gender-sensitive urban design is one of the most cost-effective instruments available for reclaiming the public realm for everyone.

Subject of Research: Gender-sensitive effects of urban design interventions on fear of crime in public spaces

Article Title: Urban design interventions reduce fear of crime in public spaces in gender-sensitive ways

Article References: Navarrete-Hernandez, P., Schlesser, T., & Luca, D. (2026). Urban design interventions reduce fear of crime in public spaces in gender-sensitive ways. Nature Cities. https://doi.org/10.1038/s44284-026-00494-0

Image Credits: AI Generated

DOI: 10.1038/s44284-026-00494-0

Keywords: urban design, fear of crime, public spaces, gender-sensitive design, urban lighting, perceived safety, women's mobility, sightlines, placemaking, Nature Cities, urban planning, social surveillance