Planning strategies for promoting environmentally suitable pedestrian pavements in cities

This paper examines the relevance of incorporating comprehensive life-cycle environmental data into the design and management of pedestrian pavements to minimize the impact on the built environment. The overall primary energy demand and global warming potential of concrete, asphalt and granite sidewalks are assessed. A design with a long functional lifetime reduces its overall primary energy demand and global warming potential due to lower maintenance and repair requirements. However, long-lived construction solutions do not ensure a lower life-cycle primary energy demand and global warming potential than for shorter-lived designs; these values depend on the environmental suitability of the materials chosen for paving. Asphalt sidewalks reduce long-term global warming potential under exposure conditions where the functional lifetime of the pavements is less than 15 years. In places where it is known that a concrete sidewalk can have a life of at least 40 years, a concrete sidewalk is the best for minimizing both long-term primary energy demand and global warming potential. Granite sidewalks are the largest energy consumers and greenhouse gas contributors.     

Turning cities inside out: transportation and the resurgence of downtowns in North America

North American urban areas have changed dramatically over the last four decades. While downtowns were thought to be in long-term decline 40 years ago, central business districts are today the most vibrant residential and commercial centers throughout a largely suburban continent. This paper examines the role of transportation technology and policy in the earlier decline and recent revival of American downtowns and examines challenges to the continuation of urban regeneration. Major recent investments in physical improvements in central cities have been complemented by a dramatic shift in the locus of logistical and goods processing activities from city centers to outlying areas. While many tout the energy efficiency and environmental benefits of walkable and denser inner cities, a more complete accounting of their impacts also requires analysis of increasing urban congestion and the steady rise in urban goods movement in support of the new development patterns.     

Driver information systems — A North American perspective

Driver information systems (DIS) are considered in North America as a major category of Intelligent Vehicle-Highway Systems (IVHS), which offers to improve the efficiency and safety of driving by means of an amalgamation of information technology with vehicle and highway technologies. Traditionally North America has basic strengths in a number of information technologies that are relevant to DIS. Due to a hiatus in federal funding in the early 1980s, DIS development in North America during the past decade has emphasized autonomous systems on the vehicles until recently. The current acceleration of IVHS development in the United States has resulted from a number of converging forces and has provided the impetus for developing advanced driver information systems (ADIS) that integrates the vehicle and the highway. Large-scale demonstration and implementation of ADIS will hinge on the major legislations in the near future, and on the successful development of public-private sector partnerships in IVHS.     

Data-driven spatio-temporal discretization for pedestrian flow characterization

We propose a novel approach to pedestrian flow characterization. The definitions of density, flow and velocity existing in the literature are extended through a data-driven spatio-temporal discretization framework. The framework is based on three-dimensional Voronoi diagrams. Synthetic data is used to empirically investigate the performance of the approach and to illustrate its advantages. Our approach outperforms the considered approaches from the literature in terms of the robustness with respect to the simulation noise and with respect to the sampling frequency. Additionally, the proposed approach is by design (i) independent from an arbitrarily chosen discretization; (ii) appropriate for the multidirectional composition of pedestrian traffic; (iii) able to reflect the heterogeneity of the pedestrian population; and (iv) applicable to pedestrian trajectories described either analytically or as a sample of points.     

Cost-based approach for sizing of pedestrian facilities

Pedestrian facility size is currently determined in direct relationship to the design level of service. However, the design level of service is chosen arbitrarily from the six levels of service, which are assumed to represent the freedom available for movement at different levels of pedestrian flow. This direct and simple approach to facility sizing is shown to have two fundamental deficiencies that contribute to wasteful over capacity. In this article, a cost-based approach is introduced to overcome the deficiencies. Two analytical models, one for determining optimal design density and another for determining optimal design flow, are presented. The optimum design parameters minimize the total cost of the facility defined as the sum of construction cost and user cost. The sensitivity of the optimum parameters to the cost and pedestrian flow parameters is demonstrated using a numerical example.     

Assessing urban sidewalk networks based on three constructs: a synthesis of pedestrian level of service literature

ABSTRACT

Pedestrian Level of Service (PLOS) models are widely used to assess walking facilities. These models have been in existence since the 1970s, wherein the process broadly consists of three steps, i.e. attribute selection, model calibration, and classification of model results into service-level categories, based on Measures of Effectiveness (MOEs). This paper reviews existing sidewalk PLOS studies based on their association with the three constructs of flow characteristics, built environment and users’ perception, which in combination represents the entire walking environment spectrum, as has been indicated by existing researchers. Forty-seven PLOS studies, along with eight review papers, written by authors from the Americas, Europe, Asia and Australia, between the years of 1971 and 2019, are analysed in this review. The review finds that although 49% of the studies employed both qualitative and quantitative data for their respective methodologies, but none of them use all the three broad constructs in a combined fashion. Also, in selecting the attributes to be used for developing the PLOS, these studies have only referred to previous literature available at that point in time, and not employed any consistent and robust method in selecting context-specific attributes. When it came to the preferred analysis technique, 60% of the studies favoured the use of the regression technique while calibrating their model, whereas 22% used a points-based marking scheme. Finally, 89% of the studies manually classifies the PLOS model results to respective service levels (i.e. letter grades), as opposed to utilising a classification algorithm. In addition, this review could identify only one paper that describes a PLOS based on pedestrian route directness, which is a measure of pedestrian network connectivity. In view of these findings, the review paper suggests the need of a robust methodology in selection of attributes and the use of innovative modelling techniques, both of which could allow the utilisation of all three constructs. Also, such advanced modelling techniques could bypass the need for categorising service levels manually. Finally, the study advocates the use of network connectivity measures in developing sidewalk PLOS, as it is an important part of the built environment.     

Validation of an agent-based microscopic pedestrian simulation model in a crowded pedestrian walking environment

This study validates a recently developed agent-based pedestrian micro-simulation model in a crowded walking environment. The model is applied to simulate pedestrian movements at a major street in the downtown Vancouver area. The street was closed for traffic to allow people attending a social event to leave the area safely. The calibration of model parameters is conducted using a Genetic Algorithm that minimizes the error between simulated and actual trajectories, acquired by means of computer vision. Validation results confirm the accuracy of the simulated trajectories, as the average error between the actual and simulated trajectories is found to be 0.28?m, and the average error in walking speed is just 0.06 m/s. Furthermore, results show that the model is capable of reproducing the actual behavior of pedestrians during different interactions with high accuracy (more than 94% for most interactions).     

Development of destination choice models for pedestrian travel

Most research on walking behavior has focused on mode choice or walk trip frequency. In contrast, this study is one of the first to analyze and model the destination choice behaviors of pedestrians within an entire region. Using about 4500 walk trips from a 2011 household travel survey in the Portland, Oregon, region, we estimated multinomial logit pedestrian destination choice models for six trip purposes. Independent variables included terms for impedance (walk trip distance), size (employment by type, households), supportive pedestrian environments (parks, a pedestrian index of the environment variable called PIE), barriers to walking (terrain, industrial-type employment), and traveler characteristics. Unique to this study was the use of small-scale destination zone alternatives. Distance was a significant deterrent to pedestrian destination choice, and people in carless or childless households were less sensitive to distance for some purposes. Employment (especially retail) was a strong attractor: doubling the number of jobs nearly doubled the odds of choosing a destination for home-based shopping walk trips. More attractive pedestrian environments were also positively associated with pedestrian destination choice after controlling for other factors. These results shed light on determinants of pedestrian destination choice behaviors, and sensitivities in the models highlight potential policy-levers to increase walking activity. In addition, the destination choice models can be applied in practice within existing regional travel demand models or as pedestrian planning tools to evaluate land use and transportation policy and investment scenarios.     

A fine discrete field cellular automaton for pedestrian dynamics integrating pedestrian heterogeneity,anisotropy, and time-dependent characteristics

This paper proposes a discrete field cellular automaton (CA) model that integrates pedestrian heterogeneity, anisotropy, and time-dependent characteristics. The pedestrian movement direction, moving/staying, and steering are governed by the transfer equations. Compared with existing studies on fine-discretized CA models, the proposed model is advantageous in terms of flexibility, higher spatial accuracy, wider speed range, relatively low computational cost, and elaborated conflict resolution with synchronous update scheme. Three different application scenarios are created by adjusting the definite conditions of the model: (1) The first one is a unidirectional pedestrian movement in a channel, where a complete jam in the high-density region is observed from the proposed model, which is missing from existing floor field CA models. (2) The second one is evacuation from a room, where the evacuation time is independent of the discretization factor, which is different from previous work. (3) The third one is an ascending evacuation through a 21-storey stair system, where pedestrians move with constant speed or with fatigue. The evacuation time in the latter case is nearly twice of that in the former.     

Diet and body size of North American mammal road mortalities

Previous studies suggest roadkill may not be evenly distributed among species or within species due to life history characteristics. We examine published data on mammalian roadkill surveys conducted in North America for a relationship between diet type, body size and roadkill frequency. Eight studies with comparable methods are used in the analysis for a combined survey mileage of 224,354 km that includes 3.101 individuals killed from 38 species. Carnivores were less likely to be found in roadkill surveys than omnivores or herbivores. After controlling for diet type, a peaked relationship was found between body size and roadkill frequency with the model predicting the highest roadkill for body sizes of about 1.06 kg. These results may be explained by both biological factors and sampling methods.     

Design and analysis of control strategies for pedestrian flows

Transportation - Exploiting the full potential of pedestrian infrastructure is becoming critical in many environments which cannot be easily expanded to cope with the increasing pedestrian demand....     

A mesoscopic model for large-scale simulation of pedestrian dynamics

A mesoscopic pedestrian model is proposed, considering pedestrians as individuals and describing their movement by means of aggregate density-flow relationships. The model builds on a stochastic process, describing transition rates among adjacent sites on a lattice. Each lattice can contain several pedestrians. The approach is minimal and fast to simulate, and, by construction, capable of capturing population heterogeneity as well as variability in walking behaviour and en-route path choice. The model is more efficient than microscopic models, and potentially more accurate than macroscopic ones. We calibrate and validate the model using real data and carry out several numerical experiments to present its key properties and possible applications for simulation of large-scale scenarios.     

A new method for evaluation of level of service in pedestrian facilities

Safe and comfortable walking is essential for pedestrian movement in modern urban transportation systems. Since pedestrian traffic cannot be restricted in some specified streets, some measures for pedestrians have to be taken everywhere in urban areas. This research describes a way to evaluate ordinary sidewalks, and two different methods are proposed. One is an evaluation based on pedestrian behaviour and the other is an evaluation based on pedestrian opinion. Using the indices of pedestrian density and sidewalk width, we can estimate the level of service of sidewalk usage. But generally speaking, since it is not often that a sidewalk is insufficient to deal with pedestrian flow, another approach is necessary for its evaluation, that is, pedestrian awareness of sidewalks must be taken into account. The former method is recommended for all sidewalks, especially with comparatively heavy pedestrian traffic, and the latter method is recommended for ones with light pedestrian traffic.     

A macroscopic loading model for time-varying pedestrian flows in public walking areas

A macroscopic loading model applicable to time-dependent and congested pedestrian flows in public walking areas is proposed. Building on the continuum theory of pedestrian flows and the cell transmission model for car traffic, an isotropic framework is developed that can describe the simultaneous and potentially conflicting propagation of multiple pedestrian groups. The model is formulated at the aggregate level and thus computationally cheap, which is advantageous for studying large-scale problems. A detailed analysis of several basic flow patterns including counter- and cross flows, as well as two generic scenarios involving a corner- and a bottleneck flow is carried out. Various behavioral patterns ranging from disciplined queueing to impatient jostling can be realistically reproduced. Following a systematic model calibration, two case studies involving a Swiss railway station and a Dutch bottleneck flow experiment are presented. A comparison with the social force model and pedestrian tracking data shows a good performance of the proposed model with respect to predictions of travel time and density.     

A hybrid simulation-assignment modeling framework for crowd dynamics in large-scale pedestrian facilities

This paper presents a hybrid simulation-assignment modeling framework for studying crowd dynamics in large-scale pedestrian facilities. The proposed modeling framework judiciously manages the trade-off between ability to accurately capture congestion phenomena resulting from the pedestrians’ collective behavior and scalability to model large facilities. We present a novel modeling framework that integrates a dynamic simulation-assignment logic with a hybrid (two-layer or bi-resolution) representation of the facility. The top layer consists of a network representation of the facility, which enables modeling the pedestrians’ route planning decisions while performing their activities. The bottom layer consists of a high resolution Cellular Automata (CA) system for all open spaces, which enables modeling the pedestrians’ local maneuvers and movement decisions at a high level of detail. The model is applied to simulate the crowd dynamics in the ground floor of Al-Haram Al-Sharif Mosque in the City of Mecca, Saudi Arabia during the pilgrimage season. The analysis illustrates the model’s capability in accurately representing the observed congestion phenomena in the facility.     

Microscopic decision model for pedestrian route choice at signalized crosswalks

In this paper, two‐tier mathematical models were developed to simulate the microscopic pedestrian decision‐making process of route choice at signalized crosswalks. In the first tier, a discrete choice model was proposed to predict the choices of walking direction. In the second tier, an exponential model was calibrated to determine the step size in the chosen direction. First, a utility function was defined in the first‐tier model to describe the change of utility in response to deviation from a pedestrian's target direction and the conflicting effects of neighboring pedestrians. A mixed logit model was adopted to estimate the effects of the explanatory variables on the pedestrians' decisions. Compared with the standard multinomial logit model, it was shown that the mixed logit model could accommodate the heterogeneity. The repeated observations for each pedestrian were grouped as panel data to ensure that the parameters remained constant for individual pedestrians but varied among the pedestrians. The mixed logit model with panel data was found to effectively address inter‐pedestrian heterogeneity and resulted in a better fit than the standard multinomial logit model. Second, an exponential model in the second tier was proposed to further determine the step size of individual pedestrians in the chosen direction; it indicates the change in walking speed in response to the presence of other pedestrians. Finally, validation was conducted on an independent set of observation data in Hong Kong. The pedestrians' routes and destinations were predicted with the two‐tier models. Compared with the tracked trajectories, the average error between the predicted destinations and the observed destinations was within an acceptable margin. Copyright © 2016 John Wiley & Sons, Ltd.     

Using automated walking gait analysis for the identification of pedestrian attributes

Collecting microscopic pedestrian behavior and characteristics data is important for optimizing the design of pedestrian facilities for safety, efficiency, and comfortability. This paper provides a framework for the automated classification of pedestrian attributes such as age and gender based on information extracted from their walking gait behavior. The framework extends earlier work on the automated analysis of gait parameters to include analysis of the gait acceleration data which can enable the quantification of the variability, rhythmic pattern and stability of pedestrian’s gait. In this framework, computer vision techniques are used for the automatic detection and tracking of pedestrians in an open environment resulting in pedestrian trajectories and the speed and acceleration dynamic profiles. A collection of gait features are then derived from those dynamic profiles and used for the classification of pedestrian attributes. The gait features include conventional gait parameters such as gait length and frequency and dynamic parameters related to gait variations and stability measures. Two different techniques are used for the classification: a supervised k-Nearest Neighbors (k-NN) algorithm and a newly developed semi-supervised spectral clustering. The classification framework is demonstrated with two case studies from Vancouver, British Columbia and Oakland, California. The results show the superiority of features sets including gait variations and stability measures over features relying only on conventional gait parameters. For gender, correct classification rates (CCR) of 80% and 94% were achieved for the Vancouver and Oakland case studies, respectively. The classification accuracy for gender was higher in the Oakland case which only considered pedestrians walking alone. Pedestrian age classification resulted in a CCR of 90% for the Oakland case study.