<?xml version="1.0" encoding="utf-8"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>TRB Publications Index</title><link>http://pubsindex.trb.org/</link><atom:link href="http://pubsindex.trb.org/common/TRIS Suite/feeds/rss.aspx?tc=NN%3AMsyx" rel="self" type="application/rss+xml" /><description></description><language>en-us</language><copyright>Copyright © 2015. National Academy of Sciences. All rights reserved.</copyright><docs>http://blogs.law.harvard.edu/tech/rss</docs><managingEditor>tris-trb@nas.edu (Bill McLeod)</managingEditor><webMaster>tris-trb@nas.edu (Bill McLeod)</webMaster><image><title>TRB Publications Index</title><url>http://pubsindex.trb.org/Images/PageHeader-wTitle.png</url><link>http://pubsindex.trb.org/</link></image><item><title>Analysis of Pedestrians’ Road Crossing Behavior, in Social Groups</title><link>http://pubsindex.trb.org/view/2209718</link><description><![CDATA[A significant percentage of pedestrians walk in social groups (friends, families, or acquaintances who walk together). Although patterns generated by social interactions among group members have been shown to affect crowd dynamics, studies on the effect of social interactions at different crossing phases under low pedestrian density are limited. This study aims to comprehensively examine the influence of size and sex composition on pedestrians’ behaviors when walking alone and with friends in different phases before, during, and after the road crossing. For this, experiences were carried out with controlled small groups of friends (varying size and sex composition) at three unsignalized crosswalks with low pedestrian density. The average speed and distance between the young pedestrians in six segments of the trajectories (two in each phase), extracted from video recordings, were analyzed with linear mixed models. Results show that pedestrians reduce their speed when approaching the curb, they accelerate while on the crosswalk, and reduce again when they reach the other side. In all phases, the average speed of the groups was lower than the single pedestrians, and the females’ groups walked slower than the males, except during the crossing, where no sex-related differences were found. On the contrary, before the crossing, the distance increased and decreased from the second segment in the crosswalk. The smallest distance was observed between the female groups and dyads. These findings have relevant implications for research on pedestrian behavior, helping to better understand the complexity of pedestrian dynamics and improve pedestrian safety.]]></description><pubDate>Mon, 17 Jul 2023 09:06:30 GMT</pubDate><guid>http://pubsindex.trb.org/view/2209718</guid></item><item><title>Pedestrians’ Road Crossing Behavior at Unprotected Mid-Blocks among Adolescents and Adults</title><link>http://pubsindex.trb.org/view/2078678</link><description><![CDATA[Traffic crashes involving pedestrians often occur when the gap acceptance selected is below the minimum critical gap. Social cues and situational awareness play a key role in pedestrians’ choices when crossing roads at unprotected mid-blocks. This paper investigates the effects of conformist behavior on pedestrians’ cautiousness relative to their age group. In particular, we examine differences between adolescents (aged 13–18?years) and adults (aged 18?years or over). Video cameras were set at three urban locations in Auckland City, New Zealand. A total of 1,330 pedestrians were divided into four age groups, with adolescence used as the reference group. Risk ratios and regression analysis were used to measure the association between variables. The key finding from the observed behavior shows that group dynamics can reduce individuals’ attention to the road crossing regardless of age and gender. Although both adolescents and adults display self-regulation with various cautious behaviors, the presence of others affects their selection of the safety margin (time left to spare after crossing). Differences in the safety margins for groups of adolescents and adults largely involved the relationship amongst the group members rather than the number of people. Such findings present evidence that injury prevention strategies need to reflect the instincts and behavioral habits of different pedestrians. Encouraging a safety culture targeted specifically at various age groups that aligns with road design facilities and recognizes these behaviors will assist in the reduction of crashes involving pedestrians.]]></description><pubDate>Thu, 08 Dec 2022 16:29:34 GMT</pubDate><guid>http://pubsindex.trb.org/view/2078678</guid></item><item><title>Analyzing Count Data with Endogenous Peering Effects: How Spatial Activities and Our Connections Mutually Influence Each Other</title><link>http://pubsindex.trb.org/view/1496104</link><description><![CDATA[The rapid development in social media networks and information technology innovations has brought revolutions in regional development and transportation systems. For example, in the hospitality business, short-term rental of residential houses/apartments is challenging the traditional hotel business, and ridesharing is changing people’s travel behavior in both short term (e.g., departure time and route choice) and long term (e.g., car ownership). People no longer make decisions individually; instead, they connect with each other more closely both geographically and virtually (i.e., via social media online). Most traditional spatial econometric models address the interdependencies among decision makers using an exogenous weight matrix, which is usually specified by geographic distances or socioeconomic distances. However, such specification becomes limited and inappropriate when the peer effect is formed by virtual connections online, and thus the weight matrix becomes endogenous. Therefore, this paper develops an innovative spatial count data model with endogenous peer effects, which will enrich the traditional spatial research by considering the influence of “virtual space”, i.e., how the spatial activities are enforced or influenced by the peer effects generated by socioeconomic interactions. Specifically, the proposed model consists of three parts: the first part is a Poisson spatial autoregressive regression model for count data (i.e., small positive integers); the second part characterizes virtual connections among observations by introducing an entry equation, which enters the definition of the weight matrix; and the last part takes into account the endogenous peer effect by allowing the first two parts to be correlated with each other. For model estimations, the Bayesian Blocked Metropolis Hasting within Gibbs Sampling algorithm is used, and the model is validated using Monte Carlo simulations. To do so, a series of simulated datasets are generated to evaluate the robustness of the model, and all validation results show satisfactory parameter recovery capability. In the end, the proposed model is used to analyze popular sharing economy activities in the hospitality business. An empirical application, focusing on the number of Airbnb establishments in each census block group is analyzed using the proposed model. Based on the model estimates, the potential influential factors of Airbnb establishments are identified, and the applicable value of the proposed model is demonstrated.]]></description><pubDate>Thu, 25 Jan 2018 09:33:00 GMT</pubDate><guid>http://pubsindex.trb.org/view/1496104</guid></item><item><title>Intra-household bargaining for school trip accompaniment of children: A group decision approach</title><link>http://pubsindex.trb.org/view/1439539</link><description><![CDATA[This paper tests a group decision-making model to examine the school travel behavior of students 6-18 years old in the Minneapolis-St. Paul Metropolitan area. The school trip information of 1,737 two-parent families with a student is extracted from Travel Behavior Inventory data collected by the Metropolitan Council between the Fall 2010 and Spring 2012. The model has four distinct characteristics including: (1) considering the student explicitly in the model, (2) allowing for bargaining or negotiation within households, (3) quantifying the intra- household interaction among family members, and (4) determining the decision weight function for household members. This framework also covers a household with three members, namely, a father, a mother, and a student, and unlike other studies it is not limited to dual-worker families. To test the hypotheses the authors build two models, each with and without the group-decision approach. The models are separately built for different age groups, namely students 6-12 and 12-18 years old. This study considers a wide range of variables such as work status of parents, age and gender of students, mode of travel, and distance to school. The findings of this study demonstrate that the elasticities of the two modeling approaches differ not only in the value, but in the sign in some cases. In 63% of the cases the unitary household model underestimates the results. More precisely, the elasticities of the unitary household model are as large as 2 times more than that of the group-decision model in 20% of cases. This is a direct consequence of model misspecification that misleads both long- and short-term policies where the intra-household bargaining and interaction is overlooked in travel behavior models.]]></description><pubDate>Wed, 15 Feb 2017 17:03:12 GMT</pubDate><guid>http://pubsindex.trb.org/view/1439539</guid></item><item><title>Analysis of Pedestrian Group Behavior</title><link>http://pubsindex.trb.org/view/1438888</link><description><![CDATA[It  is  always  interesting  to  study  about  the  self-organization  phenomena  existing  among pedestrians.  One  such  phenomena  is  the  organization  of  pedestrian  groups.  To  estimate  the capacity  of  the  system,  most  of  the  researchers  consider  the  individual  pedestrian  walking speeds. However, pedestrians mostly walk in groups. Earlier research shows that presence of groups severely influences the crowd movements  thus  affects capacity of  the system. Hence understanding  the  behaviour  of  pedestrian  groups  on  crowd  movements  is  essential.  In  this regard the current study examines the effect of group size, composition on pedestrian walking speeds and time headways adhered by different groups. Video graphic technique was adopted for the collection of pedestrian data. A semi-automatic process using MATLAB® based tool was employed to extract the relevant data. The present study reveals some interesting insights related to pedestrian group behaviour. Further analysis shows that with the increase in group size  the  mean  walking  speed  decreases.  Group  sizes  follow  logarithmic  distribution.  It  is noticed that mean time headway increases with the increase in the group size. Also the gender proportion influences the group speeds and headways. Finally it was observed that there is a significant  difference  between  speeds  as  well  as  time  headways  maintained  by  groups  with respect to individuals. The results confirm that pedestrian behaviour is different when they are in groups and thus influences the capacity of the infrastructure. Hence it is necessary to consider the pedestrian group dynamics in estimating the capacity of the facilities.]]></description><pubDate>Tue, 24 Jan 2017 15:15:23 GMT</pubDate><guid>http://pubsindex.trb.org/view/1438888</guid></item><item><title>A Collision Avoidance Model for Two-Pedestrian Groups: Considering Random Avoidance Patterns</title><link>http://pubsindex.trb.org/view/1438280</link><description><![CDATA[Group  is  a  common  phenomenon  in  pedestrian  crowds  and  group  modeling  is  still  an  open  challenging problem.  When group  pedestrians  avoid  each  other,  different  patterns  can  be observed.  Pedestrians  can  keep close  with group  members  and  avoid  other groups  in  cluster.  Also,  they  can avoid  other groups  separately. Considering this randomness in avoidance patterns, the authors propose a collision avoidance model for two-pedestrian groups. In this paper, the avoidance model is proposed based on velocity obstacle method at first. Then group model  is  established  using distance  constrained  line  (DCL),  by  transforming  DCL  into  the  framework  of velocity  obstacle,  the  avoidance  model  and group  model  are successfully  put  into  one  unified calculation structure.  Within  this structure,  an  algorithm  is  developed  to  solve  the  problem  when  solutions  of  the  two models conflict with each other. Two groups of bidirectional pedestrian experiments are designed to verify the model. The accuracy of avoidance behavior and group behavior is validated in the microscopic level, while the lane formation phenomenon and fundamental diagrams is validated in the macroscopic level. The experiments results show the authors' model is convincing and has a good expansibility to describe three or more pedestrian group]]></description><pubDate>Tue, 24 Jan 2017 15:15:20 GMT</pubDate><guid>http://pubsindex.trb.org/view/1438280</guid></item><item><title>Impacts of Different Angles and Speeds on Behavior of Pedestrian Crowd Merging</title><link>http://pubsindex.trb.org/view/1337698</link><description><![CDATA[Many forms of complex pedestrian crowd behaviors, including merging, can be identified in built environments such as public transport stations and public buildings. Understanding and capturing this phenomenon in a robust model is a challenging task; it is also a significant opportunity for research, given the international demand for models of this type. Despite the frequent occurrence of merging of crowd streams, this complex behavior has not received enough attention so far. The literature that is related to crowd merging is limited to T-shaped intersections and studies conducted on staircases. In this study using experimental data, the crowd merging phenomenon was investigated. The impacts of different merging angles and different pedestrian speeds were investigated. The results showed that flow rates and headway distributions are affected by variety in pedestrian speeds and merging angles.]]></description><pubDate>Mon, 23 Mar 2015 08:59:55 GMT</pubDate><guid>http://pubsindex.trb.org/view/1337698</guid></item><item><title>Interactive Behavior Characteristics of Pedestrian Traffic on Stairways</title><link>http://pubsindex.trb.org/view/1339346</link><description><![CDATA[Stairways serve as important walking facilities for pedestrians, but research of pedestrian traffic on stairways is not sufficient. This paper focuses on the characteristics study of interactive behavior on stairways, including overtaking behavior on one-way stairways and opposite avoidance behavior on two-way stairways. Two flights of stairways in a metro station in Shanghai, China were selected to collect the behavior data. Through the data analysis it is revealed that the characteristics of overtaking behavior and opposite avoidance behavior have both similarities and differences. In terms of similarities, neither of these two types of behavior would occur under extremely low or high densities. While under other ranges of density, their occurrence intensity increase first, and then decrease with the increase of density. The difference of the two types of behavior lies in their occurrence intensity within a low to medium density range, i.e., rapid increase for overtaking but keeping stable for opposite avoidance when density increases. It is pointed out that the available space for overtaking and avoidance is the main factor contributing to the above similarities and differences. And the correlation analysis between available space and occurrence intensity of the interactive behavior is also conducted to reveal their relations. Findings of this research are expected to enhance the knowledge of pedestrian behavior on stairways for a better stairway traffic design and level of service evaluation.]]></description><pubDate>Thu, 12 Mar 2015 07:52:55 GMT</pubDate><guid>http://pubsindex.trb.org/view/1339346</guid></item><item><title>Exploring Exit Jam Characteristics in Panic Evacuation Scenarios Using Animal Dynamics</title><link>http://pubsindex.trb.org/view/1339015</link><description><![CDATA[Crowd dynamics modeling and management have been the focus of researchers for several years. An important aspect of crowd analysis is to understand the movement dynamics of a group of people evacuating a closed area in a relatively short period of time. Although, numerous studies have been carried out to understand the dynamics of crowd movement in normal and emergency evacuation scenarios, few studies have been conducted to explore crowd dynamics in panic situations. The main reason for this is the lack of appropriate data providing enough information about crowd movement in these scenarios. Recently, animal experiments have been utilized as a proxy for human experiments. Using animals to study crowd dynamics in panic scenarios has shown the potential to provide some useful improvements to building designs in order to minimize the number of casualties in crowd disasters. However, more studies need to be conducted to explore the usefulness of animal dynamics to evaluate different alternative designs. This study uses animal experiments, specifically panicked woodlice experiments, to analyze exit jam characteristics in panic scenarios. In this study, the relationship between exit flow rate and exit density is investigated first. Then, crowd fundamental diagrams (speed-density, flow-density and speed-flow), drawn for jam area in front of the exit, are explored. The results reveal that change in woodlice escaping behavior cause an increasing trend in exit capacity as the jam behind the exit increases. On the other hand, number of temporary blockages is increased in panic situations. The results further suggest that there are some similarities between woodlice fundamental diagrams and traffic fundamental diagrams; however, woodlice escaping behavior in panic scenarios apply some changes in terms of jam density and capacity in the jam area. Results of this study support this hypothesis that similar phenomena can be observed in human since the main target for both human and animal is to reach the safe area to survive. However, they might show different behaviors since they behave quite differently at the individual level. In future studies, more experiments should be carried out on different species to provide more support for the hypothesis.]]></description><pubDate>Tue, 10 Mar 2015 07:50:20 GMT</pubDate><guid>http://pubsindex.trb.org/view/1339015</guid></item><item><title>Group Dynamics and Exit-Blocking Behaviors: A look at pedestrian modeling evacuations</title><link>http://pubsindex.trb.org/view/1338731</link><description><![CDATA[Pedestrian and crowd movement is increasingly gaining the interest of city planners, emergency managers, and others interested in managing the safety of certain populations. Employing agent- based modeling and simulation techniques, this paper develops and analyzes a pedestrian egress model that considers the effect of group configurations on evacuation time. This model builds upon the relatively few pedestrian models that account for group behavior, incorporating both individual and group goal-seeking behavior where individuals negotiate preferences to orient toward the exit or stay with their groups. Simulation testing revealed an exit-blocking phenomenon in which allegiance to group cohesion caused congestion at exits. Some individual agents refused to move through exits while waiting for their leaders and thus stalled the entire evacuation process. In this paper, the researchers explore this exit-blocking behavior and discuss the problem of balancing factor selection with the need to increase model complexity in order to incorporate more social and behavioral considerations. The researchers compare two versions of the model that use different interpretations of space to justify the use of spatially simpler models that can handle more complex sociological factors including speed adjustment in response to group members’ mobility levels and varying personal preferences for staying with the group.]]></description><pubDate>Thu, 26 Feb 2015 10:03:28 GMT</pubDate><guid>http://pubsindex.trb.org/view/1338731</guid></item><item><title>Fuzzy Cellular Automata Models for Crowd Movement Dynamics at Signalized Pedestrian Crossings</title><link>http://pubsindex.trb.org/view/1337046</link><description><![CDATA[Crowd movement dynamics at a signalized pedestrian crossing constitutes a complex system affected by many factors. Existing crowd simulation models seldom consider cognition and decision making of individual pedestrians. In this study, a fuzzy cellular automata (FCA) model was developed to simulate pedestrian movements at crowded signalized pedestrian crossings that incorporated pedestrian decision-making processes. The proposed FCA model incorporated fuzzy logic into a conventional cellular automata (CA) model. In contrast to existing models and applications, the proposed FCA model used fuzzy sets and membership functions to simulate individuals’ decision making process. Four fuzzy sets were applied for each decision: stop or go (stop–go) decision, moving direction, velocity change, and congregation. Membership functions of each input factor as well as weight factors of each fuzzy set at different movement zones were calibrated on the basis of field observations. Model performance was assessed by comparisons of trajectories between estimation and observation, interactions with conflicting vehicles and pedestrians, and congregation phenomena. Through a simulation experiment and comparison with existing approaches, simulation results show that the FCA model can well replicate crowd movement dynamics in real-world pedestrian crossings.]]></description><pubDate>Thu, 29 Jan 2015 09:19:02 GMT</pubDate><guid>http://pubsindex.trb.org/view/1337046</guid></item><item><title>Group Dynamics in Pedestrian Crowds: Estimating Proxemic Behavior</title><link>http://pubsindex.trb.org/view/1288441</link><description><![CDATA[Recent crowd disasters highlight the importance of properly planning and designing large urban events and public spaces to enhance the safety of people in a crowd during evacuations. Pedestrian crowd dynamics are empirically investigated with an interdisciplinary approach (i.e., social sciences, computer science, and traffic engineering) focusing on the effect of groups and their proxemic behavior and interactions while walking. Empirical evidence achieved from urban in-field observations and laboratory experiments are presented and compared. Results indicate that the proxemic behavior of walking groups has a negative effect on walking speed when flow is irregular (primarily because of the need for members to maintain spatial cohesion during locomotion). These results have important implications for the design of common metrics to characterize spatial interactions among pedestrians and for the validation of models to replicate crowd dynamics that consider the effects of groups under normal and emergency conditions.]]></description><pubDate>Tue, 25 Feb 2014 09:15:19 GMT</pubDate><guid>http://pubsindex.trb.org/view/1288441</guid></item><item><title>Pedestrian Walking Characteristics Through Angled Corridors: An Experimental Study</title><link>http://pubsindex.trb.org/view/1288258</link><description><![CDATA[Understanding pedestrian walking characteristics is important for the planning and design of mass gathering places for day-to-day activities as well as for emergency evacuations. The optimization of architectural designs and properly managing crowds at public buildings and the built environment is essential to ensure the safety and efficiency of crowd dynamics. Most previous empirical and theoretical studies highlight the behavior of a crowd as a whole system (macroscopic behavior) or interpersonal microscopic interactions within the crowd. A major gap in the knowledge is that no sufficient research has been carried out to examine solo walking characteristics, particularly when individual pedestrians interact with complex geometries such as turning. Whether the existing mathematical or simulation models can accurately reflect the characteristics related to solo human walking characteristics in these conditions is questionable. A series of experiments was conducted to understand the solo walking characteristics of individuals walking through angled corridors at different speeds. Initial results are discussed in detail. Results suggest that an individual tends to reduce speeds within a fixed region on the angled path and that the dimensions of this region are independent of turning angle but dependent on the individual’s desired speed. These findings are important for the calibration of parameters or behavioral rules for microscopic pedestrian models.]]></description><pubDate>Tue, 04 Feb 2014 09:13:27 GMT</pubDate><guid>http://pubsindex.trb.org/view/1288258</guid></item></channel></rss>