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.     

Pedestrian temporal gap acceptance behavior at unsignalized intersections in Kanpur,India

Vehicle heterogeneity, lack of lane discipline, lack of infrastructure facilities, and weak enforcement of traffic rules are all characteristics of Indian traffic. These characteristics make Indian roads difficult for non-motorized road users, especially pedestrians. Most intersections in urban areas in India are unsignalized, which results in complex interactions between pedestrians and motorists. This study aims to understand pedestrian gap acceptance behavior at unsignalized intersections in India under heterogeneous traffic conditions. Pedestrian data were collected from six unsignalized intersections in the city of Kanpur. The critical gap was estimated using Wu’s (2006) macroscopic model, and then the effects of several variables on the critical gap were studied. A discrete choice model (binary logit model) was developed to understand the choice of accepted and rejected vehicular gaps depending on traffic, road, and peer pedestrian characteristics. The mean critical headway was 3.76 s using Wu’s model. The behavioral analysis revealed that pedestrians accept rolling gaps to cross unsignalized intersections, resulting in a reduction of the size of the critical gap. The adoption of rolling gap behavior can be attributed to the unyielding behavior of motorists, which forces pedestrians to accept short vehicular gaps in the traffic stream.     

The implications of situation and route familiarity for driver-pedestrian interaction at uncontrolled mid-block crosswalks

Most routine daily trips take place along the same route, a fact that previous studies have not investigated together with the repeated situation of conflicting with other road users. Consequently, our study addresses driver behaviour by separating the driving experience into three categories: (i) drivers unfamiliar with the route, (ii) those route-familiar, and (iii) situation-familiar drivers. The specific case of driver-pedestrian interaction at uncontrolled mid-block crosswalks is investigated. A multi-level factorial experiment including (i) crosswalk design (linear sidewalk and curb extension), (ii) driver familiarity, and (iii) pedestrian time gap acceptance (4, 6, and 8 s) was conducted using a driving simulator. Fifty-two participants were divided into four groups and stratified by age, gender, and driving experience. The minimum instantaneous time to collision, post-encroachment time, maximum car deceleration, and maximum car speed were all used as surrogate safety measures (SSM).Route-familiarity led to higher speed, while situation-familiarity positively affected driving behaviour making drivers more inclined to decrease their speed at circa 100 m before a crosswalk. The curb extension layout enhanced pedestrian safety and mitigated any adverse effects due to familiarity, with a particularly relevant impact on SSM at low accepted time gaps for pedestrians. Situation- and route-familiarity treatment protocols lead to different behaviours among drivers, indicating a clear need to account for these two familiarity levels in experiments on safety-related countermeasures.     

Changes in road-user behaviors following the installation of raised pedestrian crosswalks combined with preceding speed humps,on urban arterials

In this study, raised pedestrian crosswalks were installed at non-signalized mid-block crosswalks situated on urban arterial and collector roads. A raised crosswalk is built by installing a trapezoidal speed hump on the crosswalk area, building a preceding circular speed hump, in each travel direction, and adding traffic signs. A controlled field-study was conducted at eight sites, sixteen pedestrian crosswalks, where road user behaviors were compared in the after versus before the treatment periods. Two settings of raised crosswalks were applied at the study sites: a 15 cm high trapezoidal hump combined with 8–10 cm high circular humps, and a 10–12 cm high trapezoidal hump combined with 6–8 cm high circular humps. Field observations included video-recordings and free-flow speed measurements. Following the installation of the raised crosswalks, at most sites, a substantial decrease was observed in vehicle travel speeds while approaching the crosswalks, which was maintained over-time. In addition, at some crosswalks, improvements were found in the rates of giving-way to pedestrians by the vehicles, vehicle-pedestrian conflicts and shares of pedestrians who cross within the crosswalk boundaries, while the changes in keeping safe crossing rules by pedestrians were mixed. Overall, the changes in road user behaviors following the installation of the raised crosswalks were positive and associated with safety improvement of pedestrian crossing conditions. Based on the study results, raised crosswalks with preceding speed humps can be promoted as a pedestrian safety-improving measure on busy urban roads.     

Modeling the influence of mobile phone use distraction on pedestrian reaction times to green signals: A multilevel mixed-effects parametric survival model

Understanding and modeling the influence of mobile phone use on pedestrian behaviour is important for several safety and performance evaluations. Mobile phone use affects pedestrian perception of the surrounding traffic environment and reduces situation awareness. This study investigates the effect of distraction due to mobile phone use (i.e., visual and auditory) on pedestrian reaction time to the pedestrian signal. Traffic video data was collected from four crosswalks in Canada and China. A multilevel mixed-effects accelerated failure time (AFT) approach is used to model pedestrian reaction times, with random intercepts capturing the clustered-specific (countries) heterogeneity. Potential reaction time influencing factors were investigated, including pedestrian demographic attributes, distraction characteristics, and environment-related parameters. Results show that pedestrian reaction times were longer in Canada than in China under the non-distraction and distraction conditions. The auditory and visual distractions increase pedestrian reaction time by 67% and 50% on average, respectively. Pedestrian reactions were slower at road segment crosswalks compared to intersection crosswalks, at higher distraction durations, and for males aged over 40 compared to other pedestrians. Moreover, pedestrian reactions were faster at higher traffic awareness levels.     

Pedestrian behaviour of 6th grade Estonian students: Implications of social factors and accident-prevention education at school

Children as pedestrians are one of the most vulnerable groups of road users. Therefore factors associated with risky pedestrian behaviour should be carefully studied. The aim of this article is to clarify how the traffic behaviour of 6th grade students as pedestrians is associated with the behaviour of their traffic companions and prevention activities at school, also taking gender into consideration. The research was conducted based on a randomly-selected sample of 1033 6th-grade students with the mean age of 12.77 ± 0.38 (SD) years. The results showed that compared to girls boys take significantly more risks as pedestrians: they rarely use reflectors during periods of darkness and often cross the road against the red light. The most important role models for adolescents in traffic behaviour are their parents. The role model behaviour with the strongest effect on adolescent high-risk behaviour in traffic is the role model not using crosswalks to cross the street. The results also showed that higher-risk traffic behaviour by adolescent pedestrians is predicted by higher-risk behaviour on the part of their companions (parents, teachers), walking alone on the street, as well as by an adolescent’s lower involvement in the less active prevention activities in the classroom. To improve adolescent pedestrians’ traffic behaviour social environment and school-based factors should be considered more thoroughly in prevention work at school.     

Modelling pedestrian crossing behaviour in urban roads: A latent variable approach

As pedestrians are the most exposed and vulnerable road users to traffic accidents, urban planners frequently propose alternatives to improve their safety. However, some solutions, such as pedestrian bridges and crosswalks at signalized intersections, usually imply longer walking distances compared to the direct crossing alternative which, in its turn, involves a higher risk.In this article, a hybrid framework is proposed to analyse the pedestrians’ choice on how to cross an urban road where three crossing options are available: crossing directly, crossing by using a pedestrian bridge or using a crosswalk at a signalized intersection. The decision process is modelled as a discrete choice model incorporating latent variables to consider perceptions and psychological factors, using stated preference data coming from a survey applied in Bogotá, Colombia.Results show that the latent variables security/safety and attractiveness of each crossing alternative are relevant to understand the pedestrian crossing behaviour. These latent variables are strongly determined by socioeconomic characteristics of the individual (age, gender, level of study) and conditioned by the circumstances of the trip (main mode of transport, walking or not with children). It was found that a longer walking distance to a pedestrian bridge or a signalized crosswalk increases the probability of direct crossing, having a more relevant effect in the case of the pedestrian bridge.     

Pedestrian behaviors at and perceptions towards various pedestrian facilities: an examination based on observation and survey data

This paper presents findings from an observational study of pedestrian behaviors at various urban crosswalks and a pedestrian user survey which sought pedestrian perceptions toward various pedestrian facilities in a divided urban boulevard located next to a large university campus, Michigan State University, East Lansing, MI, USA. Such facilities included signalized and unsignalized intersection crosswalks, unsignalized marked and non-striped midblock crosswalks, physical barriers (vegetation and two-foot high concrete wall), midblock crosswalk shelters, colored paving (red brick pavement) at medians and curbs, and pedestrian warning signs at midblock crossing locations, messaging “cross only when traffic clears.” Pedestrian behavior data were obtained from the reduction of video images of pedestrian movements recorded throughout the study site. Pedestrian perceptions information was obtained through a user survey completed by pedestrians using the study site. It was found that unsignalized midblock crosswalks were the treatment of preference to pedestrians (83% reported a preference to cross) and also showed high crossing compliance rate of pedestrians (71.2%). It was also evident that the crosswalk location, relative to the origin and destination of the pedestrian, was the most influential decision factor for pedestrians deciding to cross at a designated location (90% said so). Proper traffic control can further encourage pedestrian crossings at designated locations since the effect of the availability of pedestrian signal to influence pedestrians’ decisions to cross at a specific location was quite high (74% said so). Moreover, vegetation and concrete barriers influenced the decision to cross of a significant number of pedestrians surveyed (65%). It is expected that the findings from this study will help traffic engineers, urban planners and policy makers understand pedestrian behaviors and attitudes at/towards pedestrian crosswalks.     

Hazard-based duration approach for understanding pedestrian crossing risk exposure at signalised intersection crosswalks – A case study of Kolkata,India

Pedestrian signal violation is a significant concern among policymakers and traffic engineers as this leads to a pedestrian-vehicle crash. The waiting time for a pedestrian at intersections is crucial in street-crossing decision-making. Once pedestrians terminate their waiting behaviour during the red-light period, they would cross in the red light and put themselves in danger. A total of 2089 red-light arriving pedestrian observations were made at eight intersection crosswalks across Kolkata city (India). With the help of hazard-based duration models, the waiting duration till signal violation has been analysed. Kaplan–Meier curve has been plotted to understand the survival probabilities. A semi-parametric Cox Proportional Hazard model was used to understand the different factors influencing signal violation behaviour. However, the proportional hazard assumption was not satisfied. Therefore, a parametric Accelerated Failure Time (AFT) model was used to understand the various covariates that affect the waiting duration. The results highlighted that 49.5% of pedestrians crossed immediately after arriving at the intersection in the red-light phase. A pedestrian’s probability of crossing the road when it is unsafe, i.e., motor vehicles still have green or yellow, varies with the waiting time. As waiting time increases, pedestrians get impatient and violate the traffic signal. This violation places them at an increased risk of being struck by a motor vehicle. The covariate analysis using the AFT model showed that pedestrian glance/looking behaviour, different types of distractions, signal cycle length, carrying luggage, and traffic plying on the road impacted signal violation behaviour. Signal modifications by reducing red-light phase length for pedestrians might be the most efficient means of reducing the likelihood of signal violation and being hit by a motor vehicle.     

Gap acceptance at stop-controlled T-intersections in a simulated rural environment

A high proportion of road crashes occur at intersections: in Victoria, Australia, 15% of fatal crashes and 25% of serious injury crashes occur at T-intersections, with similar proportions occurring at cross intersections. Many of these crashes can be attributed to drivers’ inappropriate gap selection. The current study used a driving simulator to examine the influence of both the driver’s intended manoeuvre and the gap duration on gap acceptance behaviour at stop-controlled T-intersections. Drivers completed 18 gap acceptance trials, with manoeuvre (turning across traffic, merging with traffic) and gap duration (3–11 s) manipulated within-subjects. There was a trend whereby drivers accepted shorter gaps when turning across traffic compared to merging with traffic, which was significant at longer gaps (⩾9 s) but not at shorter, safety–critical gaps (⩽8 s). In addition, accepted lag times varied with manoeuvre. When merging with traffic drivers demonstrated longer accepted lag times, suggesting that turn strategies differ depending on traffic direction and intended manoeuvre. Overall the results suggest that the drivers’ intended manoeuvre influences gap acceptance, although gap duration remains the most influential factor. Implications of these findings for the development and design of intersection decision support systems are discussed.     

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.     

Pedestrians’ road crossing behaviour in front of automated vehicles: Results from a pedestrian simulation experiment using agent-based modelling

The objective of this research is to explore the relation between personal characteristics of pedestrians and their crossing behaviour in front of an automated vehicle (AV). For this purpose, a simulation experiment was developed using Agent-Based Modelling (ABM) techniques. Sixty participants were asked to cross the road in a virtual environment displayed on a computer screen, allowing to record their crossing behaviour when in the presence of AVs and conventional vehicles (CVs). In some experimental configurations, the AVs communicated their intention to continue or not to continue their trajectories through the use of lights. The ABM allowed controlling the behaviour of the vehicles when interacting with the simulated avatar of the respondents. The subjects of the experiment were also asked to fill in a questionnaire about usual behaviour in traffic, as well as attitudes and risk perceptions toward crossing roads. The questionnaire data were used to estimate individual specific behavioural latent variables by means of principal component analysis which resulted in three main factors named: violations, lapses, and trust in AVs. The results of generalized linear mixed models applied to the data showed that besides the distance from the approaching vehicle and existence of a zebra crossing, pedestrians’ crossing decisions are significantly affected by the participants’ age, familiarity with AVs, the communication between the AV and the pedestrian, and whether the approaching vehicle is an AV. Moreover, the introduction of the latent factors as explanatory variables into the regression models indicated that individual specific characteristics like willingness to take risks and violate traffic rules, and trust in AVs can have additional explanatory power in the crossing decisions.     

Investigating temporal variations in pedestrian crossing behavior at semi-controlled crosswalks: A Bayesian multilevel modeling approach

“Semi-controlled” crosswalks are unsignalized, but have clear pavement markings and “yield to pedestrian” signs. At these locations, pedestrians and motorists frequently interact to determine who should proceed first. When interacting with drivers, pedestrian crossing decisions are complex events that involve a variety of human responses, as well as vehicle dynamics, traffic characteristics, and environmental conditions. In addition, these complexities can be subject to temporal effects. Without considering temporal variations in pedestrian-motorist interaction, statistical methods could lead to biased coefficient estimates and inaccurate conclusions.The study developed a Bayesian multilevel logistic regression (BMLR) model to capture heterogeneities in pedestrian interaction behavior during four different time periods. The proposed method incorporates time-specific effects that vary randomly between time-periods based on a weakly informative prior. The results indicate significant factors, some of which confirm previous research and some that are new ways to explain pedestrian behavior at the individual level. The identification of variables such as FlowOn and FlowWait sheds light on the interactions between pedestrians – providing more information than the single GroupSize measure.Some consequent safety implications are discussed from the perspectives of vehicle dynamics, vehicle flow rate and pedestrian volume. The more detailed metrics developed in this paper will provide a valuable starting point. for the design of crosswalk controls that will foster a higher degree of compliance and less delay.     

Mixed-effects logistic regression for estimating transitional probabilities in sequentially coded observational data

This article demonstrates the use of mixed-effects logistic regression (MLR) for conducting sequential analyses of binary observational data. MLR is a special case of the mixed-effects logit modeling framework, which may be applied to multicategorical observational data. The MLR approach is motivated in part by G. A. Dagne, G. W. Howe, C. H. Brown, & B. O. Muthén (2002) advances in general linear mixed models for sequential analyses of observational data in the form of contingency table frequency counts. The advantage of the MLR approach is that it circumvents obstacles in the estimation of random sampling error encountered using Dagne and colleagues' approach. This article demonstrates the MLR model in an analysis of observed sequences of communication in a sample of young adult same-sex peer dyads. The results obtained using MLR are compared with those of a parallel analysis using Dagne and colleagues' linear mixed model for binary observational data in the form of log odds ratios. Similarities and differences between the results of the 2 approaches are discussed. Implications for the use of linear mixed models versus mixed-effects logit models for sequential analyses are considered.     

Effects of pedestrian prompts on motorist yielding at crosswalks

Pedestrian safety is a serious concern at busy intersections and pedestrian campuses across the nation. Although crosswalks and signs inform pedestrians where to cross, there is no standard protocol for pedestrians to signal drivers that they wish to use the crosswalks, except to stand in or at the crosswalk. We examined the effects of two pedestrian prompts, a raised hand and extended arm, on motorist yielding at uncontrolled crosswalks. The two prompts were effective at increasing yielding.     

Drug awareness in adolescents attending a mental health service: analysis of longitudinal data

One of the procedures used most recently with longitudinal data is linear mixed models. In the context of health research the increasing number of studies that now use these models bears witness to the growing interest in this type of analysis. This paper describes the application of linear mixed models to a longitudinal study of a sample of Spanish adolescents attending a mental health service, the aim being to investigate their knowledge about the consumption of alcohol and other drugs. More specifically, the main objective was to compare the efficacy of a motivational interviewing programme with a standard approach to drug awareness. The models used to analyse the overall indicator of drug awareness were as follows: (a) unconditional linear growth curve model; (b) growth model with subject-associated variables; and (c) individual curve model with predictive variables. The results showed that awareness increased over time and that the variable 'schooling years' explained part of the between-subjects variation. The effect of motivational interviewing was also significant.     

Analysing driver’s decision in dilemma zone at signalized intersections under disordered traffic conditions

Delay in the decision-making process of stop or go during the amber phase of the signal cycle often leads to abrupt hard deceleration or red light violations at signalized intersections. The indecisiveness or the dilemma in decision making often results in compromised safety of the road users. The present study attempts to analyze the driver’s behaviour in order to make the decision of stop or go and developed a binary logistic regression model while considering different traffic behaviour parameters exhibited and observed after the onset of the amber phase. Empirical vehicular trajectory data from three signalized intersections covering 121 signal cycles and 1347 vehicles are used in the study. The study presents two dilemma zone identification models based on distance from the stop line, focusing on easy-to-use and static driver assistance and dynamic-realtime driver assistance systems. Both the models are observed to show good fit and prediction accuracy. The models are validated internally and externally for their adaptability in the field. The effect of different traffic parameters on the dilemma zone is explored, and a possible real-time application of the dynamic model as a driver assistance system in decision-making is explored.     

The impact of leaving a voicemail,environment familiarity,and pedestrian predictability on driving behavior

Talking on a cell phone can impair driving performance, but the dynamics of this effect are not fully understood. We examined the effects of leaving a voicemail message on driving when there are critical driving targets to attend to (crosswalks and pedestrians). Participants engaged in an ecologically-valid “voicemail” task while navigating a virtual environment using a driving simulator. We also examined the potential weakening or strengthening of effects of leaving a voicemail message on driving as the familiarity and predictability of critical targets changed. Participants completed four experimental runs through the same driving environment in a driving simulator. There were two crosswalks, one with a pedestrian entering the roadway and one without a pedestrian and the location of the pedestrian was predictable (the same pedestrian consistently used the same crosswalk) for the first three runs and then unpredictable for the fourth. Half of the participants left voicemail messages using a hands-free headset, while the other half drove in silence. Leaving a voicemail message increased steering deviation and velocity. Drivers who were leaving a voicemail message decelerated for pedestrians in the roadway to a similar speed as drivers who were not leaving a voicemail message, but they were delayed in braking. Drivers who were leaving a voicemail message also had worse memory for roadway landmarks. These effects were relatively stable across runs through the same driving environment, suggesting that familiarity and predictability did not impact the effects of leaving a voicemail message while driving. Therefore, leaving a voicemail message leads to poorer driving behavior; faster speed, variable steering, and worse memory for roadway landmarks. Interestingly, although drivers who were leaving a voicemail message were slower to react to local targets, they slowed as much as drivers who were not leaving a voicemail message and familiarity with the driving environment did not impact the effects of leaving a voicemail message on driving.