arXiv subjects

Esther Bosch

Publications and source records attributed to Esther Bosch.

7 recordsLinked to original sources

arXiv2026

Multisensor Measurement of Train Driver Mental Fatigue: From Simulation to Reality

Increasing automation in rail transport shifts the train driver's role from active control to prolonged supervisory monitoring. This creates conditions for mental fatigue (MF) and reduced vigilance. Despite the safety relevance of this issue, evidence on the feasibility and robustness of physiological indicators of MF under operational rail conditions remains limited. Most prior work relies on simulators or lab studies. The present study investigated multiple subjective, physiological, and behavioral indicators of MF in professional train drivers across two complementary settings: a high-fidelity train simulator (n=14) and a real-world rail environment (n=6). To our knowledge, this is the first study to deploy a full multisensor battery under actual train operating conditions. In both settings, a standardized protocol was used comprising a baseline drive, a one-hour auditory n-back task as an MF induction procedure, and a second drive. Heart rate variability and breathing rate showed consistent and theoretically expected changes across both environments, suggesting reduced physiological arousal following the fatigue induction task. In contrast, EEG-based frontal theta power and parietal alpha and beta power, electrodermal activity, blink duration, and behavioral indicators did not show clear mental fatigue-related patterns. Real-world data collection revealed substantial technical challenges related to vibration, sensor connectivity, and concurrent high-frequency data acquisition. These findings suggest that autonomic indicators, particularly HRV and breathing rate, represent the most promising and ecologically robust measures for operational fatigue monitoring in train drivers. However, neurophysiological measures require further validation under realistic conditions before deployment in driver monitoring systems, and larger samples are needed to confirm these preliminary patterns.

cs.HC↗

arXiv2026

Urban Context and Travel Experience Events: An Exploratory Comparison of Two German Cities

The presented study investigates events influencing public transportation experience in both urban (Hamburg) and rural (Tuttlingen) areas in Germany, with the aim of identifying events that affect travel experience and as a result travel behavior. Using a mobile application, 21 participants in Tuttlingen and 70 participants in Hamburg tracked everyday trips, providing real-time evaluations of travel experiences along with situational data. Multi-level regression analyses were applied to assess the impact of events such as punctuality, capacity offer, information about public transportation and others on the ontrip experience. Results indicate that a sufficient public transportation capacity offer has the strongest positive effect in Tuttlingen, whereas a lack of punctuality and low personal well-being have the strongest negative effects. In Hamburg, a lack of punctuality and a negative information event have the largest impacts. These identified effects provide a foundation for decision-making and measures to improve local public transportation.

cs.HC↗

arXiv2026

Separating Acute Psychological Stress from Physical Exertion in Biometric Signals

Acute psychological stress occurs in a wide range of everyday contexts, including transportation, occupational settings, and physical activity, where its reliable detection could enable adaptive system responses and support human well-being. A persistent challenge in automated stress recognition is disentangling the biometric signatures of acute psychological stress from those of concurrent physical exertion. This study examined how five physiological signals (tonic electrodermal activity, trapezius electromyography, heart rate, heart rate variability, and respiration rate) respond to cognitive stress and physical activity, independently and in combination. Nineteen participants completed a 2x3 within-subjects design in which acute psychological stress was induced via an n-back arithmetic task combined with social pressure and financial reward, across three activity conditions: idle sitting, walking, and stationary cycling. Multilevel linear mixed models and repeated-measures ANOVA were used to decompose main effects and interactions for each sensor. Tonic electrodermal activity showed a robust, additive response to both cognitive stress (r=0.48) and physical exertion (r=0.67), with no interaction, making it the most promising candidate for stress detection during physical activity. Heart rate and trapezius electromyography were driven almost exclusively by physical exertion, with no reliable sensitivity to the stress task. RMSSD was strongly suppressed by physical activity and showed only marginal sensitivity to cognitive load. Respiration rate was dominated by physical activity, with no reliable stress effect in the primary analysis. These findings provide a sensor-specific hierarchy for real-world stress detection and highlight tonic electrodermal activity as the most informative channel when cognitive stress must be identified in physically active populations.

cs.HC↗

arXiv2026

Which Moments Matter? Heuristics of Remembered Travel Experience in Public Transport

Understanding how travelers form overall evaluations of public transport journeys is critical for improving travel satisfaction and encouraging sustainable mode choice. While travel satisfaction is discussed to influence attitudes and future behavior, the cognitive rules by which moment-to-moment experiences are aggregated into retrospective evaluations remain poorly understood in transport research. Drawing on psychological theories of experienced and remembered utility, this study investigates which temporal aggregation heuristics best predict post-trip travel satisfaction. Using a smartphone-based experience sampling approach, we collected high-frequency on-trip experience ratings and post-trip evaluations for 2576 real-world public transport trips across three German cities. Travel experience was assessed every five minutes during trips using a multi-item scale, allowing direct comparison of competing aggregation rules, including mean experience, peak-end, minimum-end, final moment, and trip duration. Multilevel regression models were estimated to evaluate the explanatory power of each heuristic. Results show that retrospective travel satisfaction is best predicted by a Minimum-End heuristic, combining the most negative moment of the journey and the final experience. Models based on mean experience, peak-end rules, final moment alone, or trip duration performed substantially worse. This pattern indicates that both negative extremes and the final phase of a journey independently contribute to remembered evaluations, rather than overall satisfaction reflecting an average of momentary experiences. The results have important implications for theory and practice, suggesting that targeted interventions at critical negative moments and at trip endings may yield substantial improvements in remembered satisfaction and, ultimately, support shifts toward sustainable mobility.

cs.HC↗

arXiv2026

Mapping Travel Experience in Public Transport: Real-Time Evidence and Spatial Analysis in Hamburg

Shifting travel from private cars to public transport is critical for meeting climate and related mobility goals, yet passengers will only choose transit if it offers a consistently positive experience. Previous studies of passenger satisfaction have largely relied on retrospective surveys, which overlook the dynamic and spatially differentiated nature of travel experience. This paper introduces a novel combination of real-time experience sampling and spatial hot spot analysis to capture and map where public transport users report consistently positive or negative experiences. Data were collected from 239 participants in Hamburg between March and September 2025. Using a smartphone application, travelers reported their momentary journey experience every five minutes during everyday trips, yielding over 21,000 in-situ evaluations. These geo-referenced data were analyzed with the Getis-Ord $Gi^{*}$ statistic to detect significant clusters of positive and negative travel experience. The analysis identified distinct hot and cold spots of travel experience across the network. Cold spots were shaped by heterogeneous problems, ranging from predominantly delay-dominated to overcrowding or socially stressful locations. In contrast, hot spots emerged through different pathways, including comfort-oriented, time-efficient or context-driven environments. The findings highlight three contributions. First, cold spots are not uniform but reflect specific local constellations of problems, requiring targeted interventions. Second, hot spots illustrate multiple success models that can serve as benchmarks for replication. Third, this study demonstrates the value of combining dynamic high-resolution sampling with spatial statistics to guide more effective and place-specific improvements in public transport.

cs.HC↗

arXiv2024

Travel experience in public transport: Experience sampling and cardiac activity data for spatial analysis

The transportation sector has the potential to enable a greener future if aligned with increasing mobility needs. Making public transport an attractive alternative to individual transportation requires real-world data to investigate reasons and indicators of positive and negative travel experiences. These experiences manifest not only in subjective evaluations but also in physiological reactions like cardiac activity. We present a geo-referenced dataset where participants wore electrocardiograms and reported real-time stress, satisfaction, events, and emotions while traveling by tram, train, and bus. An interactive experience map helps to visually explore the data, with benchmark analyses identifying significant stress hot spots and satisfaction cold spots during journeys. Events and emotions in these spots highlight positive and negative travel experiences in an ecologically valid setting. Data on age and self-identified gender provide insights into differences between user groups. Despite including only 44 participants, the dataset offers a valuable foundation for transportation researchers and mobility providers to combine qualitative and quantitative methods for identifying public transportation users' needs.

cs.HC↗

arXiv2024

The Illusion of Performance: The Effect of Phantom Display Refresh Rates on User Expectations and Reaction Times

User expectations impact the evaluation of new interactive systems. Increased expectations may enhance the perceived effectiveness of interfaces in user studies, similar to a placebo effect observed in medical studies. To showcase the placebo effect, we conducted a user study with 18 participants who performed a target selection reaction time test with two different display refresh rates. Participants saw a stated screen refresh rate before every condition, which corresponded to the true refresh rate only in half of the conditions and was lower or higher in the other half. Results revealed successful priming, as participants believed in superior or inferior performance based on the narrative despite using the opposite refresh rate. Post-experiment questionnaires confirmed participants still held onto the initial narrative. Interestingly, the objective performance remained unchanged between both refresh rates. We discuss how study narratives influence subjective measures and suggest strategies to mitigate placebo effects in user-centered study designs.

cs.HC↗