Every young man, especially students, wanted to be part of that adventurous age. ...if there was anything close to giving up, that was the day I almost did. ...she was scared and couldn't fathom my ...reasons and relationship with the desert or the things happening there. Like every good thought, the idea wouldn't leave me, but this time the need became even more lively in my spirit, because after a period of about two years, the zeal to return to the desert was still there and the feeling as strong as ever.
•88 studies relating to risk at rail level crossing were reviewed.•The influencing factors identified were mapped using a systems thinking framework.•The findings suggest little progress in ...implementing systems thinking approaches.•A ‘many models’ research agenda is proposed.
Collisions between road users (drivers, cyclists, motorcyclists, pedestrians) and trains at rail level crossings (RLXs) remain an intractable issue. This systematic review aimed to determine what is known regarding the factors influencing risk at RLXs, with a focus on understanding the causal relationships across the entire sociotechnical system. A systematic search identified 88 published studies. The studies were categorised according to the type of outcome measured or analysed: (1) rates and severity of crashes; (2) unsafe and non-compliant road user behaviours; and (3) road user risk perception, attitudes and beliefs. Most studies focused on unsafe and/or non-compliant road user behaviour. The factors identified within the studies as influencing risk at RLXs were classified using the Accident Mapping (AcciMap) technique, a systems analysis framework. AcciMap maps the factors that influence behaviour across six system levels ranging from Government to the operating environment. Most of the factors identified within the studies related to physical attributes of the crossing itself, its operation, and the behaviours and attributes of road users. Comparatively fewer systemic factors were identified (i.e. policy and budgeting). Few relationships between factors were identified, indicating that little consideration has been given interactions between factors (i.e. how crossing design influences end-user decision making). A research agenda is proposed based on systems thinking and the use of a ‘many model’ approach to understand and address risk at RLXs.
•There is a knowledge gap on how pedestrians will interact with automated vehicles.•55 individuals participated in a 360° video-based virtual reality experiment.•A mixed-model binomial logistic ...regression was applied on the data for analysis.•No difference in crossing intentions was found between vehicles’ types.•However, participants with higher trust in automation had higher crossing intentions.
Partially and fully automated vehicles (AVs) are being developed and tested in different countries. These vehicles are being designed to reduce and ultimately eliminate the role of human drivers in the future. However, other road users, such as pedestrians and cyclists will still be present and would need to interact with these automated vehicles. Therefore, external communication interfaces could be added to the vehicle to communicate with pedestrians and other non-automated road users. The first aim of this study is to investigate how the physical appearance of the AV and a mounted external human-machine interface (eHMI) affect pedestrians’ crossing intention. The second aim is to assess the perceived realism of Virtual reality based on 360° videos for pedestrian crossing behavior for research purposes. The speed, time gap, and an eHMIs were included in the study as independent factors. Fifty-five individuals participated in our experiment. Their crossing intentions were recorded, as well as their trust in automation and perceived behavioral control. A mixed binomial logistic regression model was applied on the data for analysis. The results show that the presence of a zebra crossing and larger gap size between the pedestrian and the vehicle increase the pedestrian’s intention to cross. In contrast to our expectations, participants intended to cross less often when the speed of the vehicle was lower. Despite that the vehicle type affected the perceived risk of the participants, no significant difference was found in crossing intention. Participants who recognized the vehicle as an AV had, overall, lower intentions to cross. A strong positive relationship was found between crossing intentions and perceived behavioral control. A difference in trust was found between participants who recognized the vehicle as automated, but this did not lead to a difference in crossing intentions. We assessed the research methodology using the presence questionnaire, the simulation sickness survey, and by comparing the results with previous literature. The method scored highly on the presence questionnaire and only 2 out of 55 participants stopped prematurely. Thus, the research methodology is useful for crossing behavior experiments.
Objective:
In this article, we investigated the effects of external human-machine interfaces (eHMIs) on pedestrians’ crossing intentions.
Background:
Literature suggests that the safety (i.e., not ...crossing when unsafe) and efficiency (i.e., crossing when safe) of pedestrians’ interactions with automated vehicles could increase if automated vehicles display their intention via an eHMI.
Methods:
Twenty-eight participants experienced an urban road environment from a pedestrian’s perspective using a head-mounted display. The behavior of approaching vehicles (yielding, nonyielding), vehicle size (small, medium, large), eHMI type (1. baseline without eHMI, 2. front brake lights, 3. Knightrider animation, 4. smiley, 5. text WALK), and eHMI timing (early, intermediate, late) were varied. For yielding vehicles, the eHMI changed from a nonyielding to a yielding state, and for nonyielding vehicles, the eHMI remained in its nonyielding state. Participants continuously indicated whether they felt safe to cross using a handheld button, and “feel-safe” percentages were calculated.
Results:
For yielding vehicles, the feel-safe percentages were higher for the front brake lights, Knightrider, smiley, and text, as compared with baseline. For nonyielding vehicles, the feel-safe percentages were equivalent regardless of the presence or type of eHMI, but larger vehicles yielded lower feel-safe percentages. The Text eHMI appeared to require no learning, contrary to the three other eHMIs.
Conclusion:
An eHMI increases the efficiency of pedestrian-AV interactions, and a textual display is regarded as the least ambiguous.
Application:
This research supports the development of automated vehicles that communicate with other road users.
Introduction: Little is known about how characteristics of the environment affect pedestrians’ road crossing behavior. Method: In this work, the effect of typical urban visual clutter created by ...objects and elements in the road proximity (e.g., billboards) on adults and children (aged 9–13) road crossing behavior was examined in a controlled laboratory environment, utilizing virtual reality scenarios projected on a large dome screen. Results: Divided into three levels of visual load, results showed that high visual load affected children’s and adults’ road crossing behavior and visual attention. The main effect on participants’ crossing decisions was seen in missed crossing opportunities. Children and adults missed more opportunities to cross the road when exposed to more cluttered road environments. An interaction with age was found in the dispersion of the visual attention measure. Children, 9–10 and 11–13 years old, had a wider spread of gazes across the scene when the environment was highly loaded—an effect not seen with adults. However, unexpectedly, no other indication of the deterring effect was found in the current study. Still, according to the results, it is reasonable to assume that busier road environments can be more hazardous to adult and child pedestrians. Practical Applications: In that context, it is important to further investigate the possible distracting effect of causal objects in the road environment on pedestrians, and especially children. This knowledge can help to create better safety guideline for children and assist urban planners in creating safer urban environments.
► Despite official investigation, the Kerang tragedy remains ambiguous. ► We use systems and individual psychological approaches to examine the incident. ► Various contributing systems factors were ...identified. ► The schema approach suggests a faulty activation of schema error was the primary causal factor. ► It is concluded that the two juxtaposed approaches can be used together for accident analysis.
In 2007 a loaded semi-trailer truck struck a passenger train on a railway level crossing in Northern Victoria, Australia, killing eleven train passengers. Although the incident was formally investigated, why the truck driver proceeded through the crossing in the presence of a train remains unexplained. This article uses two juxtaposed Human Factors approaches to provide insight into the contributory factors underlying the incident. A systems analysis framework is used to examine the rail level crossing system in which the incident occurred and an individual psychological schema theory account is used to examine the failures which led the truck driver to proceed through the crossing in the presence of a train. The findings suggest that the primary cause of the incident was a looked-but-failed-to-see error driven by a faulty activation of schema error, leading the truck driver to assume initially that the crossing was in fact in a non-activated state with no train present. Moreover, various system-wide factors that shaped the rail level crossing ‘system’ and thus the incident are identified.
•A computer vision (CV) algorithm is developed using grade crossing surveillance video data.•The CV algorithm can automatically detect trespassing near misses.•The near miss data can support ...proactive safety improvements at grade crossings.
Grade-crossing trespasses are one of the greatest sources of injuries and fatalities on railways. While there is a wealth of data regarding grade-crossing accidents, near misses (or precursor events) associated with unsafe trespassing on railroad tracks are not reported, and therefore a comprehensive dataset is unavailable. This paper presents a Computer Vision (CV) algorithm to automatically detect trespassing near misses based on surveillance video footage of railway-road grade crossings. The CV algorithm is designed to be robust under changing lighting conditions over the course of the day-night cycle and works well under varying weather conditions. The algorithm is currently implemented based on data from one grade crossing in New Jersey. With minimal configuration changes, the algorithm can be adapted to various other grade crossings. Ultimately, the CV methodology can support data-driven grade-crossing near-miss risk analysis and contribute to proactive safety improvements at grade crossings.
Purpose
Rail level crossing removals to improve transport performance across metropolitan Melbourne (state of Victoria) resulted in new rail fencing and grade-separation of tracks from the ...surrounding environment at several sites. These design changes restricted pedestrian access to the rail tracks, which is a countermeasure known to prevent railway suicide in other settings. We examined whether any such suicide prevention effect followed the removals.
Methods
We used a multiple-arm pre-post design to test whether a decrease in monthly frequency of railway suicides occurred at level crossing removal sites (intervention sites), compared to randomly matched sites where level crossings had not yet been removed (control sites). We used data available in the Victorian Suicide Register covering the period 1st January 2008 to 30th June 2021.
Results
The mean monthly number of railway suicides decreased by 68% within a 500 m radius of intervention sites (RR: 0.32; CI 95% 0.11–0.74) and by 61% within a 1000 m radius of intervention sites (RR: 0.39; CI 95% 0.21–0.68). There was no evidence that the mean monthly number of railway suicides changed at the control sites, either within a 500 m radius (RR: 0.88; CI 95% 0.47–1.56) or a 1000 m radius (RR: 0.82; CI 95% 0.52–1.26).
Conclusion
The reduction in railway suicides at locations where level crossings were removed, demonstrates the suicide prevention benefits that can be derived from a major infrastructure project even if not initially intended. Planning for major infrastructure projects should include consideration of these benefits, with designs incorporating features to maximise suicide prevention impact.
•Encouraging walking requires addressing experienced barriers.•Pedestrian crossings perceived as barriers to walking are objectively characterised.•Characteristics are compared with local design ...guidelines and Healthy Streets.•Technical documents are shown to be not specific enough to inform retrofit.•Recommendations are made towards retrofit-ready evidence-base.
Pedestrian crossings are a staple of city design and a key feature both in terms of risk of road trauma and impacts on pedestrian experience. In car-dominated environments, the challenge is in retrofitting existing infrastructure to enable and encourage walking. It is unclear what diverse people might find difficult and to what extent existing design recommendations identify those needs.
This study aims to provide a real-world perspective on local design guidelines and the Healthy Streets metrics, by triangulating them with objective measures of the built environment and users’ perceptions of unfeasibility or difficulty. The study builds on previous research having identified non-signalised crossing points experienced by interview participants (half of whom were disabled) as barriers to access. These non-walkable crossings are characterised objectively, using a range of potentially relevant metrics and specific thresholds. The study then sought the simplest way to describe those crossings, identifying the importance of three metrics: (a) peak-hour traffic; (b) complexity; and (c) turning radii for traffic. The results also identified important gaps in local design guidelines and Healthy Streets metrics, which are currently not set up to enable cities to easily identify these difficult crossings.
These findings are important because they can be used to identify crossings that are likely to cause difficulties walking and should be retrofitted to support walking. They also provide indications of complementary information needed to improve local guidelines and Healthy Streets metrics to enable them to support proactive retrofit.
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