Pokemon gaming causes pedestrians to run a red light: An observational study of crossing behaviours at a signalised intersection in Taipei City

Since the launch of the smartphone game “Pokemon Go”, the worldwide craze has led to numerous traffic crashes and injuries resulting from falling or tripping. This paper investigates the effects of several smartphone distracting activities (gaming, talking, texting, Web surfing, and listening to music) on the street-crossing behaviours of pedestrians in Taipei City, Taiwan. A field study using video cameras was conducted to observe pedestrian crossing behaviours (e.g., crossing time, sudden movements, running a red light, and walking outside the crosswalk) at a selected signalised intersection. Data such as phone features, distracting activities, and personal attributes of the pedestrians were obtained in interviews conducted after pedestrians had completed crossing the street. In total, 1995 pedestrians engaging in various smartphone activities were observed. Results indicate that unsafe crossing behaviours were more prevalent among those playing “Pokemon Go”. Texting via instant-message apps appeared to be the second-most risk distracting activity. Results of the logistic models reveal that contributing factors to unsafe behaviours include being a student, phone screen of 5 in. or larger, and having an unrestricted 4G Internet data allowance. Two interaction terms (gaming × students, and gaming × unlimited 4G data allowance) in the models appear to be important determinants of unsafe crossing behaviours. The current research suggests that to prevent potential crashes and injuries, smartphone gaming while crossing the street should be prohibited.     

Level of service of pedestrian facilities: Modelling human comfort perception in the evaluation of pedestrian behaviour patterns

The paper presents a new methodology for evaluating the quality of operation of pedestrian facilities: the methodology is based on the individual level of comfort perceived by each pedestrian that moves in the area.At each time instant, each pedestrian perceives a comfort level which is a function of the space they feel currently available and of his required space. The required space depends on the subject’s walking direction as well as on physical and psychological factors. The available space depends on the current positions of pedestrians. The proposed methodology quantifies the current discomfort due to pedestrian interactions as a continuous function of the interpersonal distances.The proposed methodology has been applied to empirical data. The experimental data are presented, discussed and compared with widely accepted level of service assessment methods.     

DETECTION OF THE VELOCITY OF MOVEMENT OF VISUAL STIMULI BY PIGEONS

Nine pigeons were trained to discriminate a moving stimulus from a stationary stimulus. In one experiment, the stimulus was a rotating disc with radial stripes. In a second experiment, the stimulus was a vertically moving film strip with horizontal bars. Several psychophysical procedures were used to determine the minimal detectable velocity of movement. The detection thresholds for most of the pigeons fell in the range of 4.4 to 6.5 millimeters per second, corresponding to a retinal velocity of 4.1 to 6.01 degrees per second. A signal detection analysis of the psychophysical data indicated systematic changes in response bias that were related to the ordinal position of the stimulus velocity in the sequence.     

Analysis of the occurrence and severity of vehicle-pedestrian conflicts in marked and unmarked crosswalks through naturalistic driving study

BackgroundAlthough many studies have been conducted on the safety of pedestrian crossings, few researches have been focused on drivers' behavior in unmarked crosswalk and marked crosswalk areas. Considering that statistics of pedestrian accidents are not the same in the two types of crossing area, based on the last report of the World Health Organization, it is very critical to evaluate driver yielding behavior to determine the differences in the actions of drivers when encountering pedestrians in the two areas.MethodsThis study was conducted based on surrogate measures of safety (SMoS) collected through a Naturalistic Driving Study on 52 participants in Iran. The study was carried out from April 2017 to April 2018 using the installation of cameras in the private vehicle of the participants. The analysis of the recorded films showed that 956 conflicts have occurred in unmarked crosswalks and 392 conflicts in marked crosswalks, respectively.ResultsA model was developed for driver yielding behavior using binary logistic regression, and showed that yielding rates in unmarked crosswalsk were about fifty percent of the yielding rates in marked crosswalks. Based on the model, it is indicated that the aggressive behavior of pedestrians during the crossing, such as running, zigzag and diagonal crossing, as well as the late detection of pedestrians by drivers resulting from high-speed driving in the unmarked crossing areas, will reduce the yielding behavior rate. Also, using the Swedish traffic conflicts technique, the severity of the conflicts was classified into four general categories: encounter, potential, slight, and serious conflict, through 30 different levels on the basis of conflicting speed and time to the accident. The results showed that pedestrians behavior during conflicts of the group “encounter” and drivers’ behavior during conflicts of the groups of “potential”, “slight” and “serious”, were the principal factors in preventing collision through an evasive maneuver. The results showed that increasing the level of conflict severity, which indicates an increase of the conflicting speed and a decrease of the time remaining to point of a possible collision with pedestrian, causes drivers to yield a harsh-maneuver to prevent collision. Soft-maneuvers such as deceleration and acceleration, as well as harsh-maneuvers such as changing the lane/stop during conflicts were most driver yielding behavior during conflict groups of slight and serious. According to the results of the analysis, the behavior of drivers in marked crossing areas is better than in the unmarked crossing area, leading to safer crossing for pedestrians.ConclusionsThis study suggests that the significant differences in driver yielding behavior in the two areas is due to the late detection of pedestrians by drivers and also the less proper action by them in unmarked crosswalk areas. Thus, the probability of accidents in Unmarked Crossing areas is higher than in marked crossing areas. Consequently, the design of improved advanced driver assistance systems to identify the risk of pedestrian accident may improve the driver yielding behavior and thus increase the safety of pedestrians.     

Pedestrians at the kerb – Recognising the action intentions of humans

Aim of the presented research is the development of a cognitive driver assistance system, which can capture the traffic situation, analyse it, and warn the driver in case a pedestrian is a potential hazard. Hence parameters have to be identified by which the intention of the pedestrian can be unambiguously predicted. Two approaches to the topic are addressed. First, the pedestrian’s perspective was taken. The question was how crossing decisions were influenced by the parameters distance and velocity of the car. Following a signal, participants had to choose to cross the road in front of or behind the car. The data analysis showed that pedestrians relied on the distance of the car rather than the time to collision for their decision. In the second experiment the observer’s perspective raised the question what parameters humans use to predict pedestrians’ intentions. Videos of natural traffic scenes were presented. Participants had to make statements about whether the shown pedestrian would cross the street during the next moment. In a baseline and four experimental conditions, certain information was masked in the videos. Just the condition in which only the trajectory information of the pedestrian was available produced a higher error rate.     

Differential Method of Characterizing Gait Strategies From Step Lengths and Frequencies: Strategy of Velocity Modulation

The differential method consists of the analysis of the variation of gait parameters length, frequency, and velocity with respect to their mean values, respectively, ΔL = L — L_m , Δf = f — f_m , and Δv = v – v_m , where L_m , f_m , and v_m represent the mean values of those parameters. Assuming that the strategy of modulation of velocity implies that L and f are functions of v and that statistical analyses of ratios ΔL/Δv and Δf/Δv have established that there is a very significant linear correlation, close to 1, between those ratios, the mathematical procedure allows one to determine the equation of step length, L = a · f + b · v + K, where a and b are the slope and the intercept of the linear regression and K is close to L_m . The equation was experimentally tested on 140 gait sequences performed by 6 participants and for gait velocities ranging from 0.6 to 2.2 m/s and was found to be very representative of all individual values. The differential method provides another way of using the derivative of velocity, v = L·f, to characterize the strategy of velocity modulation, which then permits one to determine the linear equation of velocity, v = f · L_m + L · f_m — L_m · f_m , and to show that the respective parts played by each parameter in the progression velocity are approximately equal. The author establishes the uniqueness of the different linear adjustments and discusses the differential method's own modes of use, that is, interindividually or globally.     

Event-related cerebral hemodynamics reveal target-specific resource allocation for both “go” and “no-go” response-based vigilance tasks

Transcranial Doppler sonography was used to measure cerebral blood flow velocity (CBFV) in the right and left cerebral hemispheres during the performance of a 50-min visual vigilance session. Observers monitored a simulated flight of unmanned aerial vehicles for cases in which one of the vehicles was flying in an inappropriate direction relative to its cohorts. Two types of vigilance tasks were employed: a traditional task in which observers made button press (“go”) responses to critical signals, and a modification of the traditional task called the Sustained Attention to Response Task (SART) in which “go” responses acknowledged nonsignal events and response withholding (“no-go”) signified signal detection. Signal detections and global CBFV scores declined over time. In addition, fine-grained event-related analyses revealed that the detection of signals was accompanied by an elevation of CBFV that was not present with missed signals. As was the case with the global scores, the magnitude of the transient CBFV increments associated with signal detection also declined over time, and these findings were independent of task type. The results support the view of CBFV as an index of the cognitive evaluation of stimulus significance, and a resource model of vigilance in which the need for continuous attention produces a depletion of information-processing assets that are not replenished as the task progresses. Further, temporal declines in the magnitude of event-related CBFV in response to critical signals only is evidence that the decrement function in vigilance is due to attentional processing and not specific task elements such as the required response format.     

Roles of personal and environmental factors in the red light running propensity of pedestrian: Case study at the urban crosswalks

Pedestrian is vulnerable to mortality and severe injury in road crashes. Red light running violation of pedestrians is one of the leading causes to the crashes at signalized intersections, at which the crash involvement rates of pedestrians are high. Therefore, it is important to identify the factors that affect the propensity of red light running of pedestrian. In this study, effects of both personal factors (pedestrians’ demographics and behavior) and environmental factors (presence and behavior of other pedestrians, signal time, and traffic condition) on the individual decision of red light running violation are examined, using the video observation surveys at the signalized crossings that are prone to pedestrian-vehicle crashes and have moderate pedestrian and vehicular traffic volumes in the urban area. Crossing behaviors of 6320 pedestrians are captured. Results of a random parameter logit model indicate that pedestrian gender, age, number of lanes, presence of a companion, number of pedestrians around, presence of other violators in the same cycle, time to green, red time, traffic volume, and percentage of heavy vehicles all affect the propensity of red light running violation of pedestrians. Also, there are significant interaction effects by pedestrian’s gender and age, presence of other violators, with a companion, and traffic volume on the propensity. Findings are indicative to the development of effective engineering, enforcement and educational initiatives combating the red light running violation behavior of pedestrians. Therefore, pedestrian safety level at the signalized intersections can be enhanced.     

Staying on or getting off the sidewalk? Testing the Mehrabian-Russell Model on pedestrian behavior

Social and environmental psychology provide a variety of models based on which to understand how built environments can elicit people’s behavioral responses. The Mehrabian-Russell model (MRM), initially presented in 1974, provides a framework that explains avoid–approach behavior towards a place based on a primary emotional response (PER) and affective states elicited by the perceived stimuli from the environment. However, despite the potential applications of the MRM in travel behavior studies, traditional models (e.g., discrete choice models and integrated choice latent variable) do not incorporate this specific psychological process that converts environmental stimuli into behavioral responses. Hence, this paper aims to test the applicability of MRM to urban sidewalks. To fulfill this objective, we developed a two-level structural equation model using latent variables (LV) identified from a confirmatory factor analysis (CFA) based on 1056 in-person surveys on 30 different sidewalks in Bogotá, Colombia. We then evaluated the effect of the PER on declared avoidance as a proxy of behavioral intention. The CFA uncovered three LV equivalent to the three affective dimensions of the MRM—arousal, pleasure, and dominance—followed by a fourth LV, representing the PER, which explains the three previous LVs. This confirms the applicability of these kinds of psychological and environmental models in pedestrian behavior evaluation. We found that PER can explain the declared intention of avoidance towards the sidewalk in an urban setting. Proving that this kind of model can explain the way in which the built environment can elicit pedestrians’ emotional responses and subsequent behaviors, provides information that can be used as input in travel behavior studies focusing on the promotion of active traveling and mode change.     

Introducing human factors in pedestrian crossing behaviour models

The objective of this research is the development of pedestrian crossing choice models on the basis of road, traffic and human factors. For that purpose, a field survey was carried out, in which a panel of 75 pedestrians were asked to take 8 short walking trips (each one corresponding to a different walking and crossing scenario) in the Athens city centre in Greece, allowing to record their crossing behaviour in different road and traffic conditions. The same individuals were asked to fill in a questionnaire on their travel motivations, their mobility characteristics, their risk perceptions and preferences with respect to walking and road crossing, their opinion on drivers, etc. The walking and crossing scenarios’ data were used to develop mixed sequential logit models of pedestrian behaviour on the basis of road and traffic characteristics. The modelling results showed that pedestrian crossing choices are significantly affected by road type, traffic flow and traffic control. The questionnaire data were used to estimate human factors (components) of pedestrian crossing behaviour by means of principal component analysis. The results showed that three components of pedestrian crossing behaviour emerge, namely a “risk-taking and optimisation” component reflecting the tendency to cross at mid-block in order to save time, etc., a “conservative” component, concerning individuals with increased perceived risk of mid-block crossing, who also appear to be frequent public transport users, and a “pedestrian for pleasure” component, bringing together frequent pedestrians, walking for health or pleasure, etc. The introduction of these components as explanatory variables into the choice models resulted in improvement of the modelling results, indicating that human factors have additional explanatory power over road and traffic factors of pedestrian behaviour. Therefore, the development of integrated choice and latent variables models appears to be an appropriate field for further research.