Children’s street crossing performance when auditory information about traffic is lacking

PurposeThe current study examined the impact on children’s street crossing behaviors of not having auditory-based information about traffic when crossing streets.MethodUsing a fully-immersive virtual reality system, numerous indices of children’s street crossing behaviors were measured both when they had auditory-based information about traffic and when this was lacking.ResultsThe lack of traffic sounds did not influence the inter-vehicle gap size that children crossed into but it did result in slower initiations and, ultimately, more high-risk outcomes (close calls and hits).ConclusionTraffic sounds significantly contribute to enhance children’s safety when crossing streets. Cars with reduced sounds (e.g., electric) and anything that interferes with children accessing auditory-based traffic information (e.g., wearing headphones) could increase their risk of pedestrian injury.     

Evaluating pedestrian interaction preferences with a game theoretic autonomous vehicle in virtual reality

Localisation and navigation of autonomous vehicles (AVs) in static environments are now solved problems, but how to control their interactions with other road users in mixed traffic environments, especially with pedestrians, remains an open question. Recent work has begun to apply game theory to model and control AV-pedestrian interactions as they compete for space on the road whilst trying to avoid collisions. But this game theory model has been developed only in unrealistic lab environments. To improve their realism, this study empirically examines pedestrian behaviour during road crossing in the presence of approaching autonomous vehicles in more realistic virtual reality (VR) environments. The autonomous vehicles are controlled using game theory, and this study seeks to find the best parameters for these controls to produce comfortable interactions for the pedestrians. In a first experiment, participants’ trajectories reveal a more cautious crossing behaviour in VR than in previous laboratory experiments. In two further experiments, a gradient descent approach is used to investigate participants’ preference for AV driving style. The results show that the majority of participants were not expecting the AV to stop in some scenarios, and there was no change in their crossing behaviour in two environments and with different car models suggestive of car and last-mile style vehicles. These results provide some initial estimates for game theoretic parameters needed by future AVs in their pedestrian interactions and more generally show how such parameters can be inferred from virtual reality experiments.     

Analyzing pedestrian behavior when crossing urban roads by combining RP and SP data

Considering the high crash rates involving pedestrians on urban roads, it is highly relevant to understanding pedestrian crossing behavior. This paper is the first to combine stated preference (SP) and revealed preference (RP) data to evaluate the impact that individual attributes, trip characteristics, built environment, strategies to prevent unauthorized crossing, and traffic flows have on pedestrians crossing decisions in an urban context. SP and RP surveys were designed and collected in Barranquilla (Colombia) near pedestrian bridges or signalized intersections where direct crossings and a high concentration of pedestrian fatalities related to traffic accidents exist. A logit model was estimated using the data enrichment paradigm. Results show that pedestrians weigh risks and costs when choosing how to cross the road. The trajectories observed in the RP component suggest that people prefer direct crossings; nevertheless, pedestrian bridges and signalized intersections can be attractive alternatives if their location matches the origin or destination of the crossing, and no detour is needed to use them. Waiting time; safety; the fine imposed for jaywalking; personal security, and previous decisions are also variables that influence pedestrian behavior when crossing urban roads. These results can be helpful to urban planners and decision-makers interested in proposing appropriate pedestrian infrastructure. The data pooling technique and the inclusion of a cost-related variable (i.e., fine) allowed computing the willingness to pay and marginal substitution rates for attributes of the built environment and other characteristics associated with the crossing decision. Also, the inclusion of several crossing alternatives and situations allowed assessing pedestrian crossing preferences under different scenarios.     

A method in modeling interactive pedestrian crossing and driver yielding decisions during their interactions at intersections

Investigating pedestrian crossing and driver yielding decisions should be an important focus considering the high risks of pedestrians in exposed to motorized traffic. Limitations, however, exist in previous studies – variables considered previously have been limited; how their behavior affect each other (defined as interactive impacts) were not sufficiently considered. This paper aims to provide a methodological approach for pedestrian crossing and driver yielding decisions during their interactions, considering of different variable types including interactive impact variables, traffic condition variables, road design variables, and environment variables. A Distance-Velocity (DV) framework proposed in an earlier study is introduced for definitions and concepts in studying pedestrian-vehicle interactions. Logistic regression, support vector machines, neural networks and random forests, are introduced as candidate models. A case study involving six crosswalk locations is conducted, focusing on interactions between pedestrians and right-turn vehicles. The proposed methodological approach is applied, with the performance of the four machine learning methods compared in terms of model generalization and confusion matrix. The model with the best performance is further compared to the typical gap-based model. Results show that random forest and logistic regression models performed the best in modeling pedestrian crossing and driver yielding decisions respective, in terms of model generalization. Besides, the DV-based modeling method (average accuracy of over 90% for pedestrians and 80% for drivers) outperformed the traditional gap-based method in all test seeds. As a key finding, interactive impacts from each other (the pedestrian and the driver) act as a key contributing variable on their decisions.     

Effects of aging on whole body and segmental control while obstacle crossing under impaired sensory conditions

The ability to safely negotiate obstacles is an important component of independent mobility, requiring adaptive locomotor responses to maintain dynamic balance. This study examined the effects of aging and visual–vestibular interactions on whole-body and segmental control during obstacle crossing. Twelve young and 15 older adults walked along a straight pathway and stepped over one obstacle placed in their path. The task was completed under 4 conditions which included intact or blurred vision, and intact or perturbed vestibular information using galvanic vestibular stimulation (GVS). Global task performance significantly increased under suboptimal vision conditions. Vision also significantly influenced medial–lateral center of mass displacement, irrespective of age and GVS. Older adults demonstrated significantly greater trunk pitch and head roll angles under suboptimal vision conditions. Similar to whole-body control, no GVS effect was found for any measures of segmental control. The results indicate a significant reliance on visual but not vestibular information for locomotor control during obstacle crossing. The lack of differences in GVS effects suggests that vestibular information is not up-regulated for obstacle avoidance. This is not differentially affected by aging. In older adults, insufficient visual input appears to affect ability to minimize anterior–posterior trunk movement despite a slower obstacle crossing time and walking speed. Combined with larger medial–lateral deviation of the body COM with insufficient visual information, the older adults may be at a greater risk for imbalance or inability to recover from a possible trip when stepping over an obstacle.     

Pedestrians’ road crossing decisions and body parts’ movements

This study aims to examine pedestrians' crossing decision, body parts' movement and full body movement, just before and during road crossing in a simulated setup. To accomplish this, a novel experimental setup for analyzing pedestrians’ crossing behavior and motion was developed where the simulated display was synchronized with a 3D motion capturing system. Twenty participants, divided into control and an experimental time pressure group, observed sixteen short (less than 30 s) and long road (70 s or more) crossing scenarios with varying crossing opportunities. Based on the crossing opportunities they were asked to cross a 3.6 m wide one-lane one way urban road. It was found that the crossing initiation process consists of four incremental movements of body parts: the head and the shoulder first; the hip, wrist and elbow second; the knee as a separate joint, and finally the ankle. Results showed that pedestrians’ decision to cross and body parts movement are influenced by time pressure and wait time for a safe crossing opportunity. Specifically, pedestrians prepare their body parts earlier, initiate their crossing earlier, and adjust their speed to compensate for the risk taken in less safe or non-safe crossing opportunities. Within the control group, women tended to be more risk avoiding than men, however those differences disappeared in the time pressure group. Most importantly, the findings provide initial evidence that this novel simulation configuration can be used to gain precise knowledge of pedestrians’ decision-making and movement processes.     

The estimation of vehicle speed and stopping distance by pedestrians crossing streets in a naturalistic traffic environment

The ability to estimate vehicle speed and stopping distance accurately is important for pedestrians to make safe road crossing decisions. In this study, a field experiment in a naturalistic traffic environment was conducted to measure pedestrians’ estimation of vehicle speed and stopping distance when they are crossing streets. Forty-four participants (18–45 years old) reported their estimation on 1043 vehicles, and the corresponding actual vehicle speed and stopping distance were recorded. In the speed estimation task, pedestrians’ performances change in different actual speed levels and different weather conditions. In sunny conditions, pedestrians tended to underestimate actual vehicle speeds that were higher than 40 km/h but were able to accurately estimate speeds that were lower than 40 km/h. In rainy conditions, pedestrians tended to underestimate actual vehicle speeds that were higher than 45 km/h but were able to accurately estimate speeds ranging from 35 km/h to 45 km/h. In stopping distance estimation task, the accurate estimation interval ranged from 60 km/h to 65 km/h, and pedestrians generally underestimated the stopping distance when vehicles were travelling over 65 km/h. The results show that pedestrians have accurate estimation intervals that vary by weather conditions. When the speed of the oncoming vehicle exceeded the upper bound of the accurate interval, pedestrians were more likely to underestimate the vehicle speed, increasing their risk of incorrectly deciding to cross when it is not safe to do so.     

Children's Road Crossing: A Window Into Perceptual–Motor Development

ABSTRACT— Most research on perceptual–motor development has focused on changes occurring during infancy and toddlerhood. In this paper, we describe our work on the development of perceptual–motor development during late childhood and early adolescence in the context of an important applied problem: bicycling across traffic-filled roads. Specifically, we have examined the gaps between cars that children and adults accept when bicycling across intersections, using an immersive, interactive bicycling simulator. This work highlights both methodological advances in using immersive, interactive virtual environments to study perceptual–motor functioning as well as theoretical advances in understanding the problem of moving the self in relation to other moving objects. We conclude with ideas for future research and practical implications of this work.     

Examining Transfer Effects of Dual-Task Training Protocols for a Complex Locomotor Task

Training protocols designed to improve dual-task performance of an obstacle crossing and auditory Stroop task (OBS+Stroop) were tested. In Experiment 1, following baseline collection of OBS+Stroop trials, proximally related walking training was performed, and participants were then retested on the OBS+Stroop test. After training, participants adopted a more cautious obstacle crossing strategy, indicating a potentially safer navigation strategy. Transfer effects from distally related training were then examined (Experiment 2); a computer game training paradigm was examined using the same testing protocol as Experiment 1. Computer training demonstrated improved dual-task performance on some measures, but did not induce a more cautious stepping strategy. Results indicate that dual-task training needs to be similar to targeted tasks to yield reliable, positive training outcomes.     

Evaluation of an integrated lighting-warning system on motorists’ yielding at unsignalized crosswalks during nighttime

Drivers’ yielding behavior to pedestrians during nighttime was assessed in seven different conditions of crosswalk lighting: (a) baseline condition with standard road lighting; (b) enhanced LED lighting that increased lighting level from 70 to 120 lx; (c) flashing orange beacons on top of the backlit pedestrian crossing sign; (d) in-curb LED strips on the curbsides of the zebra crossing with steady light emission; (e) in-curb LED strips with flashing light emission; (d) all previous devices activated with in-curb LED strips in steady mode; (e) all previous devices activated with in-curb LED strips in flashing mode. For every condition 100 trials were recorded with a staged pedestrian that initiated a standardized crossing when a vehicle was approaching. The frequency of drivers’ yielding was computed for each condition. A significant increase for yielding compliance was recorded from standard road lighting to enhanced dedicated lighting (19–38.21%), and from enhanced dedicated lighting to the seventh condition with the flashing beacons and the flashing in-curb LED strips activated (38.21–63.56%). The results showed that the integrated lighting-warning system for pedestrian crossings was effective in increasing motorists’ yielding to pedestrians during nighttime.