Zahra Shahhoseini

Estimation and application of a multi-class multi-criteria mixed paired combinatorial logit model for transport networks analysis

Probabilistic approach of transport network modelling has received significant attention in recent years. Despite the recent progress in this area, the full advantage of the potential capability of random utility choice models has not yet been fully realised. This research is intended to introduce a new approach of combining the state-of-the-art paired combinatorial logit route choice modelling and random coefficient choice models in traffic assignment. While the former addresses the problem of correlation among path utilities, the latter can capture the random taste heterogeneity in route choice decision-making. Including an additional monetary cost explanatory variable, the model would be able to assess a broader range of planning policies such as road pricing. In addition, distinguishing multiple classes of decision-makers, the model has allowed the introduction of demographic aspects of travellers into a network analysis process. Results showed a considerable difference between the flow patterns predicted by the proposed model and the traditional models.

How Simple Hypothetical-Choice Experiments Can Be Utilized to Learn Humans' Navigational Escape Decisions in Emergencies.

How humans resolve non-trivial tradeoffs in their navigational choices between the social interactions (e.g., the presence and movements of others) and the physical factors (e.g., spatial distances, route visibility) when escaping from threats in crowded confined spaces? The answer to this question has major implications for the planning of evacuations and the safety of mass gatherings as well as the design of built environments. Due to the challenges of collecting behavioral data from naturally-occurring evacuation settings, laboratory-based virtual-evacuation experiments have been practiced in a number of studies. This class of experiments faces the traditional question of contextual bias and generalizability: How reliably can we infer humans’ behavior from decisions made in hypothetical settings? Here, we address these questions by making a novel link between two different forms of empirical observations. We conduct hypothetical emergency exit-choice experiments framed as simple pictures, and then mimic those hypothetical scenarios in more realistic fashions through staging mock evacuation trials with actual crowds. Econometric choice models are estimated based on the observations made in both experimental contexts. The models are contrasted with each other from a number of perspectives including their predictions as well as the sign, magnitude, statistical significance, person-to-person variations (reflecting individuals’ perception/preference differences) and the scale (reflecting context-dependent decision randomness) of their inferred parameters. Results reveal a surprising degree of resemblance between the models derived from the two contexts. Most strikingly, they produce fairly similar prediction probabilities whose differences average less than 10%. There is also unexpected consensus between the inferences derived from both experimental sources on many aspects of people’s behavior notably in terms of the perception of social interactions. Results show that we could have elicited peoples’ escape strategies with fair precision without observing them in action (i.e., simply by using only hypothetical-choice data as an inexpensive, practical and non-invasive experimental technique in this context). As a broader application, this offers promising evidence as to the potential applicability of the hypothetical-decision experiments to other decision contexts (at least for non-financial decisions) when field or real-world data is prohibitively unavailable. As a practical application, the behavioral insights inferred from our observations (reflected in the estimated parameters) can improve how accurately we predict the movement patterns of human crowds in emergency scenarios arisen in complex spaces. Fully-generic-in-parameters, our proposed models can even be directly introduced to a broad range of crowd simulation software to replicate navigation decision making of evacuees.

Quantifying benefits of traveler information systems to performance of transport networks prior to implementation: a double-class structured-parameter stochastic trip assignment approach

Predicting benefits of advanced traveler information systems before implementation is one of the challenges in the area of transport modeling. Taking into consideration the differences in commuting behavior of unequipped and would be equipped drivers, as well as their different level of perception error are the key factor. Accordingly, it seems that the multi-class approach of traffic assignment (TA) can be regarded as a possible solution to the problem. However, dealing with the challenge of lack of observed data before system installation is still a major challenge. To deal with this problem, a double-class stochastic TA approach is proposed in this work. The network loading procedure follows a paired combinatorial logit (PCL) model, which addresses the classical problem of path overlapping. In addition, the model is origin-destination (OD)-specific parameter, which enables the modeler to represent different levels of uncertainty and stochasticity involved in route decision-making between different OD pairs. A heuristic practical estimation method is also proposed, which exempts the modeler from resorting to route choice data and facilitates the challenges involved in estimation of route choice models to a considerable extent. Furthermore, in the approximate proposed method of estimation, the new perspective from which the estimation parameter is considered provides a more tangible interpretation than that of the classical approach. It allows manipulation of data to obtain some sort of synthesized information as to the route choice behavior of prospective equipped travelers. The estimation method is applied to an experimental data set and the TA method is tested on an illustrative network. Authors demonstrate that, given the market penetration of the system, how the analyst would be able to provide quantitative forecasts as to the expected improvements in the network performance as a result of being introduced to advanced travelers information systems.

Pedestrian Crowd Dynamics Observed at Merging Sections: Impact of Designs on Movement Efficiency

The need for reliable crowd simulation tools has necessitated an accurate understanding of human behavior and the rules that govern their movements under normal and emergency escapes. This paper investigates the dynamics of merging streams of pedestrians. In the merging sections, the interaction between pedestrians and geometric features of merging sections can significantly impede the collective motion and can increase the possibility of flow breakdown, particularly under emergency conditions. Therefore, to create safe and efficient designs, it is important to study human movement characteristics associated with these types of conflicting geometries. In this study, empirical data collected from large numbers of high-density experiments with people at different desired speed levels were used to explore the effect of different merging configurations (i.e., design and angle) on dynamics of merging crowds. For the first time, this study examined the impact of elevated speed regimes (as a behavioral proxy of emergency escapes) on the movement efficiency of crowds in merging sections with different geometric designs. In particular, this study investigated the impact of these conflicting geometric settings on the average waiting time in the system as a measure of movement efficiency. Results suggest that the experienced delay is dramatically greater in asymmetrical setups compared with the delay in symmetrical setups and that the difference is even more pronounced at elevated levels of pedestrians’ desired speed. These findings give significant insights into the implications of inefficient designs of merging sections for pedestrians’ safety, notably when quick movement of crowds is necessary (e.g., in emergencies).

Collective movements of pedestrians: How we can learn from simple experiments with non-human (ant) crowds

Introduction Understanding collective behavior of moving organisms and how interactions between individuals govern their collective motion has triggered a growing number of studies. Similarities have been observed between the scale-free behavioral aspects of various systems (i.e. groups of fish, ants, and mammals). Investigation of such connections between the collective motion of non-human organisms and that of humans however, has been relatively scarce. The problem demands for particular attention in the context of emergency escape motion for which innovative experimentation with panicking ants has been recently employed as a relatively inexpensive and non-invasive approach. However, little empirical evidence has been provided as to the relevance and reliability of this approach as a model of human behaviour. Methods This study explores pioneer experiments of emergency escape to tackle this question and to connect two forms of experimental observations that investigate the collective movement at macroscopic level. A large number of experiments with human and panicking ants are conducted representing the escape behavior of these systems in crowded spaces. The experiments share similar architectural structures in which two streams of crowd flow merge with one another. Measures such as discharge flow rates and the probability distribution of passage headways are extracted and compared between the two systems. Findings Our findings displayed an unexpected degree of similarity between the collective patterns emerged from both observation types, particularly based on aggregate measures. Experiments with ants and humans commonly indicated how significantly the efficiency of motion and the rate of discharge depend on the architectural design of the movement environment. Practical applications Our findings contribute to the accumulation of evidence needed to identify the boarders of applicability of experimentation with crowds of non-human entities as models of human collective motion as well as the level of measurements (i.e. macroscopic or microscopic) and the type of contexts at which reliable inferences can be drawn. This particularly has implications in the context of experimenting evacuation behaviour for which recruiting human subjects may face ethical restrictions. The findings, at minimum, offer promise as to the potential benefit of piloting such experiments with non-human crowds, thereby forming better-informed hypotheses.

Traffic Flow of Merging Pedestrian Crowds: How Architectural Design Affects Collective Movement Efficiency

The need for developing reliable and rigorous models that can replicate and make predictions of pedestrian crowd evacuations has necessitated an understanding of the impact of architecture on individuals’ interactions with their surroundings and the behavioral rules that govern their movements. Due to the challenges of providing such behavioral data from natural evacuations and previous crowd incidents, simulation-based and laboratory-based evacuation experiments have recently been employed as innovative data-provision approaches to study crowd behavior notably under emergency conditions. This study explores pioneer experiments of emergency escape with a view to investigating the relationship between spatial constraints and collective behavior of human crowds. Here, we make use of two types of empirical and analytical data obtained from a large number of well-controlled laboratory and evacuation simulation experiments. This study presents findings corresponding to how and to what extent the presence of conflicting layouts in egress areas, particularly merging corridors, affect the collective motion of pedestrians. The focus of attention will be on measures of performance at macroscopic level derived from both observations. Our results suggested that the movement patterns observed in both types of experiments are sensitive to the angle between the two merging streams and the symmetry/asymmetry of the merging layouts, with symmetric layouts almost invariably outperforming the asymmetric counterparts. Also, within each symmetry/asymmetry structural type, the angle at which the flows combined with each other affected the efficiency of discharge. Our findings provide further evidence as to the significant role of the architectural structure of the movement area in facilitating the traffic flow of heavy crowds of pedestrians.