Influence of Obstacles on the Use of the Danger Zone on Railway Platforms

Growing passenger numbers and the lack of space available led to research on pedestrians’ behaviour on railway platforms in Switzerland. By using stereo sensors, pedestrians’ tracks were collected on a platform in the train station of Bern. The analysis of pedestrians stepping into the danger zone showed clearly that obstacles have a large influence on the frequencies of pedestrians using the danger zone. By presenting four hypotheses the effect of obstacles on pedestrians’ use of the danger zone on train station platforms is investigated

Benchmarking High-Fidelity Pedestrian Tracking Systems for Research, Real-Time Monitoring and Crowd Control

High-fidelity pedestrian tracking in real-life conditions has been an important tool in fundamental crowd dynamics research allowing to quantify statistics of relevant observables including walking velocities, mutual distances and body orientations. As this technology advances, it is becoming increasingly useful also in society. In fact, continued urbanization is overwhelming existing pedestrian infrastructures such as transportation hubs and stations, generating an urgent need for real-time highly-accurate usage data, aiming both at flow monitoring and dynamics understanding. To successfully employ pedestrian tracking techniques in research and technology, it is crucial to validate and benchmark them for accuracy. This is not only necessary to guarantee data quality, but also to identify systematic errors. Currently, there is no established policy in this context. In this contribution, we present and discuss a benchmark suite, towards an open standard in the community, for privacy-respectful pedestrian tracking techniques. The suite is technology-independent and it is applicable to academic and commercial pedestrian tracking systems, operating both in lab environments and real-life conditions. The benchmark suite consists of 5 tests addressing specific aspects of pedestrian tracking quality, including accurate line-based crowd flux estimation, local density estimation, individual position detection and trajectory accuracy. The output of the tests are quality factors expressed as single numbers. We provide the benchmark results for two tracking systems, both operating in real-life, one commercial, and the other based on overhead depth-maps developed at TU Eindhoven, within the Crowdflow topical group. We discuss the results on the basis of the quality factors and report on the typical sensor and algorithmic performance. This enables us to highlight the current state-of-the-art, its limitations and provide installation recommendations, with specific attention to multi-sensor setups and data stitching

Mobile eye tracking applied as a tool for customer experience research in a crowded train station

Train stations have increasingly become crowded, necessitating stringent requirements in the design of stations and commuter navigation through these stations. In this study, we explored the use of mobile eye tracking in combination with observation and a survey to gain knowledge on customer experience in a crowded train station. We investigated the utilization of mobile eye tracking in ascertaining customers’ perception of the train station environment and analyzed the effect of a signalization prototype (visual pedestrian flow cues), which was intended for regulating pedestrian flow in a crowded underground passage. Gaze behavior, estimated crowd density, and comfort levels (an individual’s comfort level in a certain situation), were measured before and after the implementation of the prototype. The results revealed that the prototype was visible in conditions of low crowd density. However, in conditions of high crowd density, the prototype was less visible, and the path choice was influenced by other commuters. Hence, herd behavior appeared to have a stronger effect than the implemented signalization prototype in conditions of high crowd density. Thus, mobile eye tracking in combination with observation and the survey successfully aided in understanding customers’ perception of the train station environment on a qualitative level and supported the evaluation of the signalization prototype the crowded underground passage. However, the analysis process was laborious, which could be an obstacle for its practical use in gaining customer insights

Understanding the relations between crowd density, safety perception and risk-taking behavior on train station platforms: A case study from Switzerland

Railway platforms are becoming increasingly crowded, especially at peak hours. In this observational study, we investigated how the density of people is perceived by passengers and how this perceived density correlates with safety perception and risk-taking behavior. Risk-taking behavior here means stepping into the danger zone, the area of the platform bordering the tracks where individuals are at risk to their physical integrity by a train passing through, arriving at or leaving the station. The investigation of perceived density and actual behavior on the platform poses methodological challenges. Therefore, we used a stereo sensor technology to collect anonymized behavioral data on a train station platform over two months. Data regarding passenger density and oversteps into the danger zone was collected during rush hours and analyzed for this study. Additionally, subjective data, such as estimation and perception of passenger density and safety perception were collected in a survey with 179 participants. Survey links were distributed during rush hours in three different train stations on platforms over two weeks. While distributing the links for the online survey in the field (two-hour sessions during rush hours), an observation was conducted (i.e., oversteps into the danger zone, general passenger behavior). The results indicate that increased measured passenger density is related to more oversteps. Subjective perception of crowd density, regarding how comfortable someone feels in the given situation, correlates with safety perception and also significantly predicts overstepping into the danger zone. Increased estimated density also correlates with reduced safety perception but is not a predictor of oversteps. We suggest optimizing the passenger distribution on the platform by motivating passengers to move to less crowded areas, e.g. with approaches such as “nudging” so that passengers feel more comfortable on the platform. This can both improve both safety and the customer experience on the platform