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&#39; 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&#39; 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. (C) 2015 Elsevier Ltd. All rights reserved.</p

Pedestrians' crossing behaviors and safety at unmarked roadway in China

Pedestrians&#39; crossing out of crosswalks (unmarked roadway) contributed to many traffic accidents, but existing pedestrian studies mainly focus on crosswalk crossing in developed countries specifically. Field observation of 254 pedestrians at unmarked roadway in China showed that 65.7% of them did not look for vehicles after arriving at the curb. Those who did look and pay attention to the traffic did so for duration of time that followed an exponential distribution. Pedestrians preferred crossing actively in tentative ways rather than waiting passively. The waiting time at the curb, at the median, and at the roadway all followed exponential distributions. During crossing, all pedestrians looked at the oncoming vehicles. When interacting with these vehicles, 31.9% of them ran and 11.4% stepped backwards. Running pedestrians usually began running at the borderline rather than within the lanes. Pedestrians preferred safe to short paths and they crossed second half of the road with significantly higher speed. These behavioral patterns were rechecked at an additional site with 105 pedestrians and the results showed much accordance. In terms of safety, pedestrians who were middle aged, involved in bigger groups, looked at vehicles more often before crossing or interacted with buses rather than cars were safer while those running were more dangerous. Potential applications of these findings, including building accurate simulation models of pedestrians and education of drivers and pedestrians in developing countries were also discussed. (C) 2011 Elsevier Ltd. All rights reserved

Modeling Pedestrian Crossing Paths at Unmarked Roadways

At the unmarked roadway, pedestrians cross the road with changing speeds and directions that result in curved paths and high chances of road accidents. However, few computational models have been built to address the mechanisms underlying the curved paths in crossing unmarked roadways. To better understand pedestrian behaviors and finally facilitate their safety, this paper modeled pedestrian paths at the unmarked roadway as a result of the decision-making process in which pedestrians try to minimize discomfort by weighing perceived risk (PR) with efficiency. PR is assumed to come from vehicles and specific positions on the road. Efficiency is modeled by the deviation from destination. The modeling mechanisms are consistent with existing theories, enhancing the understanding of pedestrian crossing behavior mechanisms at the unmarked roadway rather than treating the crossing process as a black box. The observed 135 pedestrian paths at two unmarked roadways in the real world were compared with the model&#39;s predictions. The potential applications of the model in exploring pedestrian position distribution at a crossing site and improving pedestrian presentation in existing driving simulators and intelligent transportation systems are discussed, as well as its limitations

Cross or wait? Pedestrian decision making during clearance phase at signalized intersections

Pedestrians arriving at clearance phase (Flashing Don&#39;t Walk) face different levels of risk depending on behavioral choice afterwards. However, few studies have focused on the choices pedestrians make during this phase. This field study analyzed pedestrian choices after arrival, evaluated safety of the choices, and built a model to identify the predictors of pedestrian choices. It was found that pedestrians arriving during clearance phase made dynamic decisions based on the changing contexts. Specifically, the majority made the decision to &quot;cross&quot; as opposed to &quot;wait&quot; (85.2% vs. 14.8% respectively), although only the latter choice is legal. Seventy-nine percent of the pedestrians did not finish crossing the intersection before the traffic light turned red, and they walked 41% of the road width during a red light. For those waited, roughly half of them waited until green or crossed at an intersecting crosswalk, while others finally started on red light. Nevertheless, the waited pedestrians still faced lower risk than those crossed prematurely in terms of running behaviors, and conflicts with vehicles. Pedestrians are more likely to cross immediately after arrival when they are younger, are not engaged in secondary tasks, arrived at a position farther from approaching vehicles at the near side of the road, or arrived at a time when there are more pedestrians crossing the road. Although fewer pedestrians choose to cross when the required speed is higher (due to a wider road or less remaining time), the required speed they choose to cross at is far higher than their actual speed. These findings are essential for realistic pedestrian simulations and targeted safety countermeasures. They also imply the need for changes to certain traffic regulations and signal design to facilitate safe decision making at clearance phase.</p

A Framework of Pedestrian-Vehicle Interaction Scenarios for eHMI Design and Evaluation

The emergence of autonomous vehicles has brought new challenges for pedestrian-vehicle interaction (PVI). To facilitate such interactions, many external human-machine interface (eHMI) concepts have been proposed. However, the development and evaluation of these eHMIs should be based on representative PVI scenarios in daily life, which have not been systematically constructed. The goal of this study is to: 1) Identify typical PVI scenarios and analyze their constituent elements; 2) Provide a practical method to generate PVI scenarios to support the development and evaluation of eHMIs. With a literature review and a focus group interview, we concluded four typical sets of PVI scenarios: street-crossing scenarios, starting scenarios, parking scenarios, and following scenarios. After analyzing key elements of these scenarios, we constructed, from the perspective of the human-machine-environment system, a three-dimension scenario analysis framework that consisted of pedestrian, vehicle, and environmental variables. We then used our framework to generate several common or challenging PVI scenarios where eHMIs can play a role and needs to be evaluated. Our work contributes to the development and evaluation of eHMIs in both academia and industry.</p

Pedestrian reported activity and information preference while waiting at a red light

Abstract The development of pedestrian signal lights made it a promising information center to distribute information to assist safe road crossing and provide “controlled engagement” to improve waiting experience. To determine what types of information to display, this study surveyed 555 pedestrians on frequency of their existing activities while waiting at a red light and preference of several types of information based on results of a structured interview. Pedestrian reported 14 types of activities, from which the four categories with decreasing frequency were extracted based on factor analysis: scene perception, recreation, mental activity, and anxiety activity. The participants reported more mental and anxiety activity have higher need for external displayed information on signal lights. Overall, among the four information categories extracted from 24 specific information types with factor analysis, pedestrians preferred road crossing and contextual information the most, with less preference on learning and appreciation information. The least preferred information is entertainment information, within which they even disliked entertainment news and general commercial ads ( vs. local ones). There are also individual differences in preference for these information categories. The findings have implications on information design for the roadside signal lights as well as advanced traveller information system in general

Pedestrian gaze pattern before crossing road in a naturalistic traffic setting

Abstract Background Gaze is the primary way for pedestrians to obtain clues from traffic scenes before making decisions. Therefore, understanding pedestrian gaze pattern is vital for traffic safety in general and for the design of autonomous vehicles. Methods In this study, participants made road-crossing decisions in a naturalistic traffic scene, with an eye-tracker recording their gaze behaviors. We manually encoded the recorded videos with 14,898 fixations, and then analyzed the gaze pattern at three levels from general to specific: gaze towards overall scenes, gaze towards vehicles and gaze towards components of vehicles. Findings At the first level, our findings indicate that frequent fixations began to appear at the distance of 100 m and peaked around 5–30 m away from pedestrians. Transversely pedestrians mainly gazed at the two lanes adjacent to themselves. Pedestrians allocated 53% gaze duration to motor vehicles. For a specific vehicle, which is the second level, the gaze duration varied with vehicles' attributes such as distances, sizes, and types. Finally, at the third level, we discovered that pedestrians’ gaze duration on different vehicle components varied with the longitudinal distance. As vehicles approach, the main area of fixation expanded from the near side headlight to the whole front and near side, and finally shift to the near side of a vehicle. Implications The distribution of fixations in space and vehicle components before pedestrian crossing can provide fundamental information for understanding and modeling of pedestrian's road-crossing behaviors. In practice, our findings can guide the timing and position of information displays on autonomous vehicles to facilitate friendly interaction with pedestrians

Measuring early-stage attentional bias towards food images using saccade trajectory deviations

Food-related attentional bias has been studied for many years, yet the time course of attentional bias is not well characterized. Probe detection and Stroop paradigms are commonly utilized to examine food-related attentional bias, however, these methods are relatively rough in reflecting attentional processing. Thus, we used a modified food-house task combined with eye-tracking to investigate restrained and unrestrained eaters' food-related attentional bias in different time courses. Saccade trajectory deviations and fixation durations were collected as eye movement measures to examine unconscious detection bias in the early stage of attentional processing and conscious maintenance bias in the later stage. An approach-avoidance conflict towards low-calorie food cues was found in restrained eaters, showing that food-related attentional bias changes with the different time courses. The saccade curvature demonstrated an early-stage attentional bias towards low-calorie foods in restrained eaters, whereas fixation measurements suggested a later-stage attentional avoidance of low-calorie foods in restrained eaters. The processing accumulation of food cues in human consciousness can probably explain the results. With the increase of the priming effect of high-calorie foods, attentional bias towards low-calorie foods disappears. In this study, saccade curvature was confirmed to be useful for directly revealing early-stage unconscious food-related attentional processing, and the role of time courses in attention allocation was also demonstrated

The safety margin and perceived safety of pedestrians at unmarked roadway

Many pedestrians cross out of crosswalks (i.e., unmarked roadway) in developing countries, but researches about their safety are under reported. This study explored safety related factors and their casual relations at unmarked roadway. Videos of 254 pedestrians' crossing process were analyzed objectively on safety and evaluated subjectively on perceived safety. The two safety indexes are consistent on important factors, with higher running frequency reduce safety while bigger group size increase safety. The two factors had contrary effect on pedestrian speed, which is positively related with safety. Higher looking frequency before crossing also enhance safety, partly by reducing running frequency and increasing going backwards with its planning nature. Longer waiting time before crossing can facilitate this planning behavior while at the same time leads to bigger group size. Buses are safer than cars, but they are not perceived as safer. In situations where only some vehicles yield, yielding ones bring danger due to sight blocking of unyielding ones in adjacent lanes. These findings can be applied to the design of intelligent transportation systems and the education of drivers and pedestrians to improve safety. (C) 2011 Elsevier Ltd. All rights reserved