Search

Physical distancing has been an important asset in limiting the SARS-CoV-2 virus spread during the COVID-19 pandemic. This study aims to assess compliance with physical distancing and to evaluate the combination of observed and self-reported data used. This research shows that it is difficult to operationalize new rules, that context affects compliance, that there needs to be a need for compliance, and that rules require upkeep. From a methodological point of view, this study found that the combined methods provide a comprehensive picture of compliance behaviour, that it is challenging but essential to mitigate response fatigue in long-term monitoring studies, and that it would be interesting in future research to learn how actual behaviour is influenced by personal narratives., Transport and Planning, Transport and Planning, Corporate Innovations

SARS-CoV-2 transmission in indoor spaces, where most infection events occur, depends on the types and duration of human interactions, among others. Understanding how these human behaviours interface with virus characteristics to drive pathogen transmission and dictate the outcomes of non-pharmaceutical interventions is important for the informed and safe use of indoor spaces. To better understand these complex interactions, we developed the Pedestrian Dynamics—Virus Spread model (PeDViS): an individual-based model that combines pedestrian behaviour models with virus spread models that incorporate direct and indirect transmission routes. We explored the relationships between virus exposure and the duration, distance, respiratory behaviour, and environment in which interactions between infected and uninfected individuals took place and compared this to benchmark ‘at risk’ interactions (1.5 metres for 15 minutes). When considering aerosol transmission, individuals adhering to distancing measures may be at risk due to build-up of airborne virus in the environment when infected individuals spend prolonged time indoors. In our restaurant case, guests seated at tables near infected individuals were at limited risk of infection but could, particularly in poorly ventilated places, experience risks that surpass that of benchmark interactions. Combining interventions that target different transmission routes can aid in accumulating impact, for instance by combining ventilation with face masks. The impact of such combined interventions depends on the relative importance of transmission routes, which is hard to disentangle and highly context dependent., Transport and Planning, Game Lab

When making trips in urban environments, cyclists lose time as they stop and idle at signalized intersections. The main objective of this study was to show how augmenting the situational awareness of traffic signal controllers, using observations from moving sensor platforms, can enable prioritization of cyclists and reduce lost time within the control cycle in an effective way. We investigated the potential of using observations from connected autonomous vehicles (CAVs) as a source of new information, using a revised vehicle-actuated controller. This controller exploits CAV-generated observations of cyclists to optimize the control for cyclists. The results from a simulation study indicated that with a low CAV penetration rate, prioritizing cyclists by tracking reduced cyclist delays and stops, even with a small field of view. As the delay of car directions were not taken into account in this study, the average car delay increased considerably with an increasing number of cyclists. Future work is needed to optimize the control that balances the delays and stops of cyclists and cars., Transport and Planning, Corporate Innovations, Transport and Planning

The Covid-19 pandemic has had a large impact on the world. The virus spreads especially easily among people in indoor spaces such as restaurants. Hence, tools that can assess how different restaurant settings can impact the potential spread of an airborne virus and that can assess the effectiveness of mitigation policies are of high value. Microscopic pedestrian models provide the tools necessary to assess the detailed movements of people in a restaurant and with that the risk of virus transmission. This paper presents the application of a microscopic pedestrian model, including a novel activity choice and scheduling model, to assess virus transmission risks in restaurants. Simulation experiments identify that different factors impact virus transmission risks in a restaurant. Contacts between restaurant staff and customers are the driving factor for virus transmission in a restaurant whereby especially staff presents a big risk. Hence, mitigation policies focussing on these interactions and on preventing staff from transmitting the virus can be highly effective. The results also show that different restaurant layouts and setups lead to distinctly different transmission risks. Therefore, insights obtained from simulating one restaurant cannot be just transferred to any other restaurant. Together, these results show the added value of including pedestrian models in disease transmission risk modelling exercises to mitigate the impact of a pandemic caused by an airborne virus. However, the research also shows that, to better utilize the potential of pedestrian models for disease transmission risk modelling, future research of pedestrian activity scheduling behaviour in indoor spaces is necessary., Transport and Planning

Bicycle networks are made up of different types of infrastructure for cars, bikes and mixed use, which has resulted in various definitions being used to describe them. However, it’s crucial to bring these definitions together to understand the structural differences among them and the impact of choices and investments in bike infrastructure. This study examines different definitions of bicycle networks in 47 cities, analysing scaling effects and various network metrics for four different definitions. Understanding structural characteristics of different bicycle networks definitions contributes to the body of knowledge necessary for design interventions by policymakers., Transport and Planning, Policy Analysis

In the study of pedestrian dynamics, the consideration of group behaviours is essential, as group interaction within crowds is a common phenomenon and significantly influences pedestrian behaviours. This special issue highlights the importance of pedestrian group behaviours and examines the subject using a wide range of methods, such as experiments, modelling, and algorithms. The works comprising this special issue can hence provide ideas for future studies on pedestrian dynamics and can also serve as a long-term reference for modelling pedestrian group behaviours., Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public., Transport and Planning

Sufficient cycle track width is important to prevent single-bicycle crashes and collisions between cyclists. The assumptions on which the minimum width is based in guidelines is founded on only a few studies. The aim of the present study is to investigate the relationship between cycle track width and lateral position of cyclists. Method: We conducted an experiment to evaluate the lateral position of cyclists along cycle tracks with different widths (Study 1). Participants cycled on an instrumented bicycle with a LIDAR to measure their lateral position. Five conditions were defined: cycle track width of 100 cm, 150 cm and 200 cm without interaction, and cycle track width of 150 cm and 200 cm with an oncoming cyclist simulated by a parked bicycle. The cross-sectional Study 2 is based on the collected lateral position measurements at cycle tracks with varying width reported in Dutch studies since 2010. Results: The experimental Study 1 with 24 participants shows that an increase in cycle track width causes cyclists to ride further away from the verge and keep more distance from an oncoming cyclist. The cross-sectional Study 2 was based on lateral position measured at 33 real-life Dutch cycle tracks. Study 2 yielded similar results, indicating that doubling pavement width increases lateral position by some 50%. Study 2 shows that, compared with a solo cyclist without interaction, a right-hand cyclist of a duo and a cyclist meeting an oncoming cyclist ride around 30% closer to the verge. Conclusions: The wider the cycle track, the more distance cyclists maintain from the verge. Cyclists ride closer to the verge due to oncoming cyclists. Practical applications: Given a cyclists’ lateral position while meeting, common variations between cyclists’ steering behavior, and vehicle width and circumstances, a cycle track width of 250 cm is needed for safe meeting maneuvers., Transport and Planning

Pedestrian tactical choices and operational movement in evacuations essentially pertain to decision-making under risk and uncertainty. However, in microscopic evacuation models, this attribute has been greatly overlooked, even lacking a methodology to delineate the related decision characteristics (bounded rationality and risk attitudes), let alone their effects on evacuation processes. This work presents an innovative two-layer floor field cellular automaton model framework, where three intertwined sub-modules respectively dedicated to modelling the exit choice, the locomotion movement and the exit-choice changing behaviours are proposed and integrated as an entity. By introducing various decision-making elements computed by the proposed algorithm, Cumulative Prospect Theory (CPT) is proposed for the first time to model the exit choice and locomotion decision-making under risk and uncertainty. In the exit-choice changing module, attractive and repulsive forces are invented to jointly describe the tendency to revisit the routing decision. Each sub-module and the whole framework are validated in manifold indoor environments. The simulation results of the modules with CPT accord with the empirics from the evacuation experiments and are superior over those from the state-of-the-art models. The degree of rationality and risk attitudes are proven to have significant impacts on tactical and operational decisions. Furthermore, irrational behaviour in decision-making is not variably detrimental to locomotion efficiency of pedestrians. The proposed framework can serve as an elegant tool to predict pedestrian dynamics. The behavioural findings shed new light on understanding and modelling the tactical and operational decisions in evacuations., Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public., Transport and Planning

Currently, the research on ship behavior during encounters focuses on evasive behavior during specific situations with existing risks of collision. However, the preliminary selection of encounters to refine the presented ship behavior is biased. To obtain a full understanding of all ship behavior during different encounters in ports and waterways, the encounter is defined from the viewpoint of the spatial-temporal co-existence of ships in the same waterway segments during the same period. Based on this definition, this paper investigates ship behavior through the encounter process with other ships. The proposed approach starts from the moment when the distance in between is minimum as the critical moment to recognize ship behavior change (course alteration and speed change) based on the Sliding Window algorithm. Thus, the encounter process is identified by the key behavior feature point into phases, being before decision-making, before the critical moment, after the critical moment, and after being past and clear. The relative movement factors are calculated according to the behavior status of both ships to describe the conditions, timing, and objective of behavior change during the dynamic process of encounters. The empirical findings based on one-year Automatic Identification System data in the port of Rotterdam are presented. In the overtaking encounters, as the give-way ship, about 14% of the overtaking ships do not take any evasive actions. Among the ships with behavior changes, the preference for course alteration and speed change is equal. As the stand-on ship, about 87% of the overtaken ships take cooperative maneuvers to facilitate the encounter, in which deceleration seems the primary choice. The timing of overtaken ship's behavior change is later than overtaking ship. For overtaking ships, the objective of course alteration is a clear passing distance of about 5 times her beam, 100m for overtaken ships irrespective of her own size. Regarding speed, the, Rivers, Ports, Waterways and Dredging Engineering, Transport and Planning, Transport and Planning

Similarly to Maslow’s pyramid of human needs, we theorize that cities have a pyramid of bicycle network needs that depends on their level of bicycle culture. As an increasing number of data sources emerge for bicycle data collection, transport authorities face the challenge of understanding how to use the data and which data sources are fit for their network needs. This article defines a framework that relates the bicycle network needs of cities with data collection systems. We showcase the need-driven framework through a case study of Melbourne, Australia, a bicycle ignorant city, and surveying 15 municipalities (and their consultancies) of the Netherlands. By using the proposed need-driven framework cities can understand how to fully exploit bicycle data collection systems and make a systematic plan., Transport and Planning, Transport and Planning, Aerospace Engineering

Numerous evacuation performance data for the utilization in evacuation modelling and simulations have been established for the conventional/widely studied scenarios, such as building evacuation scenarios. However, such data are typically scarce for a new scenario in literature — evacuation from high-deck coaches. This paper fulfills this gap by presenting empirical high-deck coach evacuation data-sets that can be used for model configuration and validation. To this end, firstly, five essential and commonly used performance metrics, i.e., evacuation time, flow rate, alighting time gap, velocity on stairways and exit choice, were collected and derived from two series of controlled experiments with 7 and 22 runs that involved 44 and 96 participants respectively. Then, all these datasets were structured in the distribution form, based on which three critical behavioural insights are revealed regardless of the evacuation conditions (the types of high-deck coaches, lighting conditions, and age groups). First, the evacuation behaviour in normal (experimental) conditions conforms to a multi-stage pattern (a modified four-stage pattern, i.e., reaction, acceleration, fluctuation and saturation stages). Second, the instantaneous flow rate can be well captured by the Burr, Loglogistic and Lognormal distributions, and the alighting time gap can be represented by the Burr distribution. Third, more than 50% of passengers evacuate through the rear door in the front-and-rear-door evacuations. The frequency of choosing the front door is found to shift towards the direction of the rear door compared to the ideal results (based on the shortest distance calculation) with a magnitude of approximately 1.95 seat rows. The presented data-sets are valuable resources for the development of high-deck coach evacuation models. The empirical findings promote the understanding upon the evacuation behaviour of high-deck coach passengers., Transport and Planning

Pedestrians are among the travelers most vulnerable to collisions that are associated with high fatality and injury rates. The increasing rate of urbanization and mixed land-use construction make walking (along with other non-motorized travel) a predominant transportation mode with a wide variety of behaviors expected. Because of the inherent safety concerns seen in pedestrian transportation infrastructures, especially those with conflicting multimodal movements expected (crosswalks, transit platforms, etc.), it is important that pedestrian behavior is modeled as a risk-taking stochastic behavior that may lead to errors and thus collision formation. In previous work, the complexity and cost associated with building pedestrian models in a cognitive-based environment weighted down the construction of simulation tools that can capture pedestrian-involved collisions, including those seen in shared space environments. In this paper, a tool that will help evaluate the safety of pedestrian traffic is initiated: an extended modeling framework of pedestrian walking behavior is adopted while incorporating different physiological, physical, and decision-making elements. The focus is on operational decisions (i.e., path choices defined by longitudinal and lateral trajectories) with a pre-specified set of origins and destinations. The model relies on the prospect theory paradigm where pedestrians evaluate their acceleration and directional alternatives while considering the possibility of colliding with other ‘‘particles.’’ Using a genetic algorithm method, the new model is calibrated using detailed trajectory data. This model can be extended to model the interactions between a variety of different modes that are present in different mixed land-use environments., Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public., Transport and Planning

In this paper, we study observed cycling distances within an accessibility framework, using data from the Netherlands, the Copenhagen Metropolitan Area and the Freiburg Region. As a scope, we look at outbound trips in home-based tours which include a single destination. We relate these observed cycling distances to a rich set of explanatory variables using both quantile and ordinary least square regression models. The results provide evidence that cycling distances are similarly distributed in all three regions. Most cycling distances are rather short, with a median of only two and a mean of three kilometers. These values vary depending on the type of activity at the destination, gender and age of the traveler and the type of bicycle that has been used. Moreover, a few remarkable differences have been found between the three regions, such as substantially different effects of age and e-bike use on observed cycling distances. Noteworthy is the missing effect of urban density. The findings of this research provide urban planners with differentiated information about how far people cycle to daily-life destinations. As shown for the example of the “15 minutes city,” the outcomes can also be used to refine existing concepts of bicycle accessibility. Finally, this research offers valuable insights into three of Europe’s most developed bicycle cultures., Transport and Planning, Transport and Planning

Cycling contributes to public health because it requires physical effort [1] and offers economic and environmental advantages over motorized transport [2]. However, 41,000 cyclists die every year in traffic crashes, 3% of the total worldwide [3]. Most fatal bicycle crashes are collisions with motor vehicles. Severe injuries among cyclists, however, are mostly due to single bicycle crashes and their numbers are increasing [4, 5]. An international review showed that the share of hospitalised casualties due to single-bicycle crashes varied from 3% to 41 % of the total number of hospitalised casualties [ 6]. ... The aim of the present study is to investigate the relationship between cycle track width and lateral position. We conducted an experiment in which the cycle track width was manipulated to determine its effect on lateral position. The results have been compared with previous findings from literature., Transport and Planning

The increase in perception capabilities of connected mobile sensor platforms (e.g., self-driving vehicles, drones, and robots) leads to an extensive surge of sensed features at various temporal and spatial scales. Beyond their traditional use for safe operation, available observations could enable to see how and where people move on sidewalks and cycle paths, to eventually obtain a complete microscopic and macroscopic picture of the traffic flows in a larger area. This paper proposes a new method for advanced traffic applications, tracking an unknown and varying number of moving targets (e.g., pedestrians or cyclists) constrained by a road network, using mobile (e.g., vehicles) spatially distributed sensor platforms. The key contribution in this paper is to introduce the concept of network bound targets into the multi-target tracking problem, and hence to derive a network-constrained multi-hypotheses tracker (NC-MHT) to fully utilize the available road information. This is done by introducing a target representation, comprising a traditional target tracking representation and a discrete component placing the target on a given segment in the network. A simulation study shows that the method performs well in comparison to the standard MHT filter in free space. Results particularly highlight network-constraint effects for more efficient target predictions over extended periods of time, and in the simplification of the measurement association process, as compared to not utilizing a network structure. This theoretical work also directs attention to latent privacy concerns for potential applications., Transport and Planning, Transport and Planning

In this paper, we study observed cycling distances within an accessibility framework, using data from the Netherlands, the Copenhagen Metropolitan Area and the Freiburg Region. As a scope, we look at outbound trips in home-based tours which include a single destination. We relate these observed cycling distances to a rich set of explanatory variables using both quantile and ordinary least square regression models. The results provide evidence that cycling distances are similarly distributed in all three regions. Most cycling distances are rather short, with a median of only two and a mean of three kilometers. These values vary depending on the type of activity at the destination, gender and age of the traveler and the type of bicycle that has been used. Moreover, a few remarkable differences have been found between the three regions, such as substantially different effects of age and e-bike use on observed cycling distances. Noteworthy is the missing effect of urban density. The findings of this research provide urban planners with differentiated information about how far people cycle to daily-life destinations. As shown for the example of the “15 minutes city,” the outcomes can also be used to refine existing concepts of bicycle accessibility. Finally, this research offers valuable insights into three of Europe’s most developed bicycle cultures., Transport and Planning, Transport and Planning

Similarly to Maslow’s pyramid of human needs, we theorize that cities have a pyramid of bicycle network needs that depends on their level of bicycle culture. As an increasing number of data sources emerge for bicycle data collection, transport authorities face the challenge of understanding how to use the data and which data sources are fit for their network needs. This article defines a framework that relates the bicycle network needs of cities with data collection systems. We showcase the need-driven framework through a case study of Melbourne, Australia, a bicycle ignorant city, and surveying 15 municipalities (and their consultancies) of the Netherlands. By using the proposed need-driven framework cities can understand how to fully exploit bicycle data collection systems and make a systematic plan., Transport and Planning, Transport and Planning, Aerospace Engineering

Pedestrians are among the travelers most vulnerable to collisions that are associated with high fatality and injury rates. The increasing rate of urbanization and mixed land-use construction make walking (along with other non-motorized travel) a predominant transportation mode with a wide variety of behaviors expected. Because of the inherent safety concerns seen in pedestrian transportation infrastructures, especially those with conflicting multimodal movements expected (crosswalks, transit platforms, etc.), it is important that pedestrian behavior is modeled as a risk-taking stochastic behavior that may lead to errors and thus collision formation. In previous work, the complexity and cost associated with building pedestrian models in a cognitive-based environment weighted down the construction of simulation tools that can capture pedestrian-involved collisions, including those seen in shared space environments. In this paper, a tool that will help evaluate the safety of pedestrian traffic is initiated: an extended modeling framework of pedestrian walking behavior is adopted while incorporating different physiological, physical, and decision-making elements. The focus is on operational decisions (i.e., path choices defined by longitudinal and lateral trajectories) with a pre-specified set of origins and destinations. The model relies on the prospect theory paradigm where pedestrians evaluate their acceleration and directional alternatives while considering the possibility of colliding with other ‘‘particles.’’ Using a genetic algorithm method, the new model is calibrated using detailed trajectory data. This model can be extended to model the interactions between a variety of different modes that are present in different mixed land-use environments., Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public., Transport and Planning

Numerous evacuation performance data for the utilization in evacuation modelling and simulations have been established for the conventional/widely studied scenarios, such as building evacuation scenarios. However, such data are typically scarce for a new scenario in literature — evacuation from high-deck coaches. This paper fulfills this gap by presenting empirical high-deck coach evacuation data-sets that can be used for model configuration and validation. To this end, firstly, five essential and commonly used performance metrics, i.e., evacuation time, flow rate, alighting time gap, velocity on stairways and exit choice, were collected and derived from two series of controlled experiments with 7 and 22 runs that involved 44 and 96 participants respectively. Then, all these datasets were structured in the distribution form, based on which three critical behavioural insights are revealed regardless of the evacuation conditions (the types of high-deck coaches, lighting conditions, and age groups). First, the evacuation behaviour in normal (experimental) conditions conforms to a multi-stage pattern (a modified four-stage pattern, i.e., reaction, acceleration, fluctuation and saturation stages). Second, the instantaneous flow rate can be well captured by the Burr, Loglogistic and Lognormal distributions, and the alighting time gap can be represented by the Burr distribution. Third, more than 50% of passengers evacuate through the rear door in the front-and-rear-door evacuations. The frequency of choosing the front door is found to shift towards the direction of the rear door compared to the ideal results (based on the shortest distance calculation) with a magnitude of approximately 1.95 seat rows. The presented data-sets are valuable resources for the development of high-deck coach evacuation models. The empirical findings promote the understanding upon the evacuation behaviour of high-deck coach passengers., Transport and Planning

This paper presents a novel microscopic modelling framework for bicycle flow operations. The modelling principles are based on similar principles successfully applied in our previous work on pedestrian and vessel flow. The main contributions of the paper are in the extension towards modelling cyclists that has not been proposed in literature before, and in the insights gained by simulation with the model using different scenarios, showing how the model outcomes depend on the modelling choices and parameters. The generalisation entails two major changes compared to our previous pedestrian model. First of all, the model does justice to the kinematics of cyclists. Contrary to pedestrians, cyclist are more restricted in their movement. The model approximates these restrictions by considering speed and movement direction and changes therein. Secondly, the model includes different strategies (cooperative, zero-acceleration, demon opponent) in its underlying game-theoretical framework, and allows including traffic rules. This allows us to model different attitudes towards risk representing different types of cyclists. The (qualitative) insights gained by application of the model pertain to one-on-one interactions between cyclists and the impact of the strategy assumptions and parameter choices on those interactions as well as on the collective phenomena that occur in the cyclist flow and their sensitivity to parameters (reflecting the extent of the prediction horizon, the level of anisotropy, and the relative importance of keeping the desired path). With respect to the collective phenomena, we look at efficiency and self-organised patterns. We conclude that the model acts in a plausible manner. While we do not aim to show empirical validity, we see that the qualitative behaviour of one-on-one interactions is plausible if compared to experimental or field data. We also observe plausible collective patterns, including forms of self-organisation under specific parameter se, Transport and Planning, Transport and Planning

In dit artikel worden de effecten van COVID-19 op de (relevante onderdelen van de) aanbodkant van het mobiliteitssysteem beschreven. Gezien de verwachte impact ligt de focus op voetgangersstromen, fietsstromen, het gebruik van deeldiensten en openbaar vervoer voertuigen. We kijken naar het effect op de capaciteit, via gemeten of theoretisch verwachte effecten op het gedrag. We maken hierbij onderscheid tussen eenvoudige infrastructuur elementen (een voetpad, een fietspad) en netwerken of knooppunten, waarbij meer complexe interacties optreden. Dit is relevant om te kunnen inschatten welke vraag door het mobiliteitssysteem kan worden verwerkt, voordat overbelasting (congestie, vertragingen, verdrukking) ontstaat. Het artikel start met een theoretisch raamwerk waarin we de verschillende aspecten die invloed hebben op de aanbodkant van het mobiliteitssysteem in kaart brengen. Vervolgens gaan we in op de verschillende (exit) scenario’s die internationaal zijn uitgerold en waarop deze impact hebben. De effecten zijn zo goed mogelijk gekwantificeerd op grond van a) bevindingen uit de literatuur, b) theoretische analyses, en - waar mogelijk - c) analyse van beschikbare data.De belangrijkste bevinding van dit onderzoek is dat de doorstroomcapaciteit van enkelvoudige infrastructuur elementen met 60 tot 70 procent kan afnemen, mits mensen zich strikt aan de 1,5 meter afstand houden. Indien we naar netwerken of (multimodale) knooppunten kijken, dan zien we dat deze afname groter wordt, afhankelijk van hoe effectief de ruimte in het knooppunt wordt - of kan worden - benut. We laten zien hoe lokale kenmerken zich doorvertalen naar het gehele knooppunt en we laten zien hoe de spreiding in ruimte leidt tot extra reductie van de doorstroomcapaciteit. De effecten met betrekking tot de opslagcapaciteit – hoeveel verkeersdeelnemers kunnen zich maximaal in een netwerk of knooppunt bevinden - zijn nog groter dan voor de doorstroomcapaciteit, wederom gegeven de opvolging van de 1,5 meter, Transport and Planning, Transport and Planning

A fully separated bicycle network from vehicular traffic is not realistic even for the most bicycle-friendly cities. Thus, all around the world urban cycling entails switching between streets of different safety, convenience, and comfort levels. As a consequence, the quality of bicycle networks should be evaluated not based on one but multiple factors and by considering the different user preferences regarding these factors. More comprehensive methodologies to assess urban bicycle networks are essential to the operation and planning of modern city transportation. This work proposes a multi-objective methodology to assess—what we refer to as—bikeability between origin–destination locations and over the entire network, useful for evaluation and planning of bicycle networks. We do so by introducing the concept of bikeability curves which allows us to assess the quality of cycling in a city network with respect to the heterogeneity of user preferences. The application of the proposed methodology is demonstrated on two cities with different bike cultures: Amsterdam and Melbourne. Our results suggest the effectiveness of bikeability curves in describing the characteristic features and differences in the two networks., Transport and Planning, Transport and Planning

High-deck coaches form an essential component of mass transportation systems in China. Safe evacuation from high-deck coaches is facing dire challenges. However, evacuation behaviour from high-deck coaches has not been deeply understood yet. In this study, a novel conceptual framework is firstly proposed to capture the evacuation behaviour of coach passengers, and next based on which 22 full-scale experiments have been conducted to examine the effect of three selected factors: available exits, lighting conditions and age groups on the evacuation behaviour of Chinese passengers in a high-deck coach, in a systematic and quantitative way. Four performance indicators of evacuation behaviour, i.e., evacuation time, pre-evacuation time, flow rate and crowdedness, were collected and analysed. The results indicate that limited available exits and the dim lighting condition (less than 1 lux) significantly reduce the evacuation efficiency and increase the crowdedness within the aisle area regardless of the age groups. Compared to young students, the evacuation of middle-aged people is observed to have a significantly longer pre-evacuation time, lower evacuation efficiency, and higher level of crowdedness. In addition, young students’ pre-evacuation times are found to conform to the Weibull distribution, whereas middle-aged people’ pre-evacuation times could be modelled with the Loglogistic distribution. Empirical results of this study could be helpful for the improvement of the safety design of high-deck coaches, and provide valuable benchmarks for the development of coach evacuation behaviour and simulation models., Transport and Planning

A largely overlooked mode choice factor of cycling is the mode-dependent capability of visiting several activity locations within a trip chain. Due to the bicycle’s limited reach in comparison to the car, this capability can be increased by urban environments that facilitate trip chaining by bicycle. In the present paper, we empirically study travel distances between activity locations that facilitate trip chaining by the example of Dutch commute tours. More precisely, we address the question of how much cyclists extend commute tour distances compared to car travellers to include a secondary activity. For this purpose, a Bayesian regression model is proposed to analyse the effects of travel mode, secondary activity type and a series of control variables such as age and time of the day on commute tour extensions. The model results propose that people make on average detours of 7.4 km by car and 1.3 km by bicycle. These values strongly differ depending on the type of secondary activity, gender, the distance of the home-work tour and the duration of the secondary activity. In addition, the comparison between car and bicycle travel revealed some behavioural peculiarities of the active modes, which have implications for bicycle-friendly urban planning and several transport-related concepts., Transport and Planning, Transport and Planning

City events are getting popular and are attracting a large number of people. This increase needs for methods and tools to provide stakeholders with crowd size information for crowd management purposes. Previous works proposed a large number of methods to count the crowd using different data in various contexts, but no methods proposed using social media images in city events and no datasets exist to evaluate the effectiveness of these methods. In this study we investigate how social media images can be used to estimate the crowd size in city events. We construct a social media dataset, compare the effectiveness of face recognition, object recognition, and cascaded methods for crowd size estimation, and investigate the impact of image characteristics on the performance of selected methods. Results show that object recognition based methods, reach the highest accuracy in estimating the crowd size using social media images in city events. We also found that face recognition and object recognition methods are more suitable to estimate the crowd size for social media images which are taken in parallel view, with selfies covering people in full face and in which the persons in the background have the same distance to the camera. However, cascaded methods are more suitable for images taken from top view with gatherings distributed in gradient. The created social media dataset is essential for selecting image characteristics and evaluating the accuracy of people counting methods in an urban event context., Transport and Planning, Human-Centred Artificial Intelligence, Transport and Planning

In the pursuit of promoting cycling and providing better cycling infrastructure, its design is of great importance. One of the critical locations in a network are intersections, and specifically T-junctions, due to the inverted perception of priority. In this paper, we investigate the behaviour at T-junctions dedicated to cyclists and the effect on bicycle flow efficiency resulting from the introduction of lane markings that advise through cyclists to shift to the left so that merging cyclists can occupy the space on the right hand side of the cycle path. A comprehensive framework is proposed for the assessment of the T-junction efficiency. Empirical trajectory data from a large-scale cycling experiment are used for the analyses. The findings suggest that cyclist heterogeneity can be even more influential on the efficiency than the infrastructure design. Moreover, a form of self-organisation is observed, as through cyclists are willing to move to the left and allow merging cyclists to fit in the cycle path without the provision of any instructions. This means that the lane marking is both redundant and not improving the efficiency of the T-junction., Transport and Planning, Transport and Planning

Collecting pedestrian behaviour data is vital to understand pedestrian behaviour. This systematic review of 145 studies aims to determine the capability of contemporary data collection methods in collecting different pedestrian behavioural data, identify research gaps and discuss the possibilities of using new technologies to study pedestrian behaviour. The review finds that there is an imbalance in the number of studies that feature various aspects of pedestrian behaviour, most importantly (1) pedestrian behaviour in large complex scenarios, and (2) pedestrian behaviour during new types of high-risk situations. Additionally, three issues are identified regarding current pedestrian behaviour studies, namely (3) little comprehensive data sets featuring multi-dimensional behaviour data simultaneously, (4) generalizability of most collected data sets is limited, and (5) costs of pedestrian behaviour experiments are relatively high. A set of new technologies offers opportunities to overcome some of these limitations. This review identifies three types of technologies that can become a valuable addition to pedestrian behaviour research methods, namely (1) applying VR experiments to study pedestrian behaviour in the environments that are difficult or cannot be mimicked in real-life, repeat experiments to determine the impact of factors on pedestrian behaviour and collect more accurate behavioural data to understand the decision-making process of pedestrian behaviour deeply, (2) applying large-scale crowd monitoring to study pedestrian movements in large complex environments and incident situations, and (3) utilising the Internet of Things to track pedestrian movements at various locations that are difficult to investigate at the moment., Transport and Planning, Transport and Planning

This paper presents a novel microscopic modelling framework for bicycle flow operations. The modelling principles are based on similar principles successfully applied in our previous work on pedestrian and vessel flow. The main contributions of the paper are in the extension towards modelling cyclists that has not been proposed in literature before, and in the insights gained by simulation with the model using different scenarios, showing how the model outcomes depend on the modelling choices and parameters. The generalisation entails two major changes compared to our previous pedestrian model. First of all, the model does justice to the kinematics of cyclists. Contrary to pedestrians, cyclist are more restricted in their movement. The model approximates these restrictions by considering speed and movement direction and changes therein. Secondly, the model includes different strategies (cooperative, zero-acceleration, demon opponent) in its underlying game-theoretical framework, and allows including traffic rules. This allows us to model different attitudes towards risk representing different types of cyclists. The (qualitative) insights gained by application of the model pertain to one-on-one interactions between cyclists and the impact of the strategy assumptions and parameter choices on those interactions as well as on the collective phenomena that occur in the cyclist flow and their sensitivity to parameters (reflecting the extent of the prediction horizon, the level of anisotropy, and the relative importance of keeping the desired path). With respect to the collective phenomena, we look at efficiency and self-organised patterns. We conclude that the model acts in a plausible manner. While we do not aim to show empirical validity, we see that the qualitative behaviour of one-on-one interactions is plausible if compared to experimental or field data. We also observe plausible collective patterns, including forms of self-organisation under specific parameter se, Transport and Planning, Transport and Planning

In dit artikel worden de effecten van COVID-19 op de (relevante onderdelen van de) aanbodkant van het mobiliteitssysteem beschreven. Gezien de verwachte impact ligt de focus op voetgangersstromen, fietsstromen, het gebruik van deeldiensten en openbaar vervoer voertuigen. We kijken naar het effect op de capaciteit, via gemeten of theoretisch verwachte effecten op het gedrag. We maken hierbij onderscheid tussen eenvoudige infrastructuur elementen (een voetpad, een fietspad) en netwerken of knooppunten, waarbij meer complexe interacties optreden. Dit is relevant om te kunnen inschatten welke vraag door het mobiliteitssysteem kan worden verwerkt, voordat overbelasting (congestie, vertragingen, verdrukking) ontstaat. Het artikel start met een theoretisch raamwerk waarin we de verschillende aspecten die invloed hebben op de aanbodkant van het mobiliteitssysteem in kaart brengen. Vervolgens gaan we in op de verschillende (exit) scenario’s die internationaal zijn uitgerold en waarop deze impact hebben. De effecten zijn zo goed mogelijk gekwantificeerd op grond van a) bevindingen uit de literatuur, b) theoretische analyses, en - waar mogelijk - c) analyse van beschikbare data.De belangrijkste bevinding van dit onderzoek is dat de doorstroomcapaciteit van enkelvoudige infrastructuur elementen met 60 tot 70 procent kan afnemen, mits mensen zich strikt aan de 1,5 meter afstand houden. Indien we naar netwerken of (multimodale) knooppunten kijken, dan zien we dat deze afname groter wordt, afhankelijk van hoe effectief de ruimte in het knooppunt wordt - of kan worden - benut. We laten zien hoe lokale kenmerken zich doorvertalen naar het gehele knooppunt en we laten zien hoe de spreiding in ruimte leidt tot extra reductie van de doorstroomcapaciteit. De effecten met betrekking tot de opslagcapaciteit – hoeveel verkeersdeelnemers kunnen zich maximaal in een netwerk of knooppunt bevinden - zijn nog groter dan voor de doorstroomcapaciteit, wederom gegeven de opvolging van de 1,5 meter, Transport and Planning, Transport and Planning

High-deck coaches form an essential component of mass transportation systems in China. Safe evacuation from high-deck coaches is facing dire challenges. However, evacuation behaviour from high-deck coaches has not been deeply understood yet. In this study, a novel conceptual framework is firstly proposed to capture the evacuation behaviour of coach passengers, and next based on which 22 full-scale experiments have been conducted to examine the effect of three selected factors: available exits, lighting conditions and age groups on the evacuation behaviour of Chinese passengers in a high-deck coach, in a systematic and quantitative way. Four performance indicators of evacuation behaviour, i.e., evacuation time, pre-evacuation time, flow rate and crowdedness, were collected and analysed. The results indicate that limited available exits and the dim lighting condition (less than 1 lux) significantly reduce the evacuation efficiency and increase the crowdedness within the aisle area regardless of the age groups. Compared to young students, the evacuation of middle-aged people is observed to have a significantly longer pre-evacuation time, lower evacuation efficiency, and higher level of crowdedness. In addition, young students’ pre-evacuation times are found to conform to the Weibull distribution, whereas middle-aged people’ pre-evacuation times could be modelled with the Loglogistic distribution. Empirical results of this study could be helpful for the improvement of the safety design of high-deck coaches, and provide valuable benchmarks for the development of coach evacuation behaviour and simulation models., Transport and Planning

A fully separated bicycle network from vehicular traffic is not realistic even for the most bicycle-friendly cities. Thus, all around the world urban cycling entails switching between streets of different safety, convenience, and comfort levels. As a consequence, the quality of bicycle networks should be evaluated not based on one but multiple factors and by considering the different user preferences regarding these factors. More comprehensive methodologies to assess urban bicycle networks are essential to the operation and planning of modern city transportation. This work proposes a multi-objective methodology to assess—what we refer to as—bikeability between origin–destination locations and over the entire network, useful for evaluation and planning of bicycle networks. We do so by introducing the concept of bikeability curves which allows us to assess the quality of cycling in a city network with respect to the heterogeneity of user preferences. The application of the proposed methodology is demonstrated on two cities with different bike cultures: Amsterdam and Melbourne. Our results suggest the effectiveness of bikeability curves in describing the characteristic features and differences in the two networks., Transport and Planning, Transport and Planning

City events are getting popular and are attracting a large number of people. This increase needs for methods and tools to provide stakeholders with crowd size information for crowd management purposes. Previous works proposed a large number of methods to count the crowd using different data in various contexts, but no methods proposed using social media images in city events and no datasets exist to evaluate the effectiveness of these methods. In this study we investigate how social media images can be used to estimate the crowd size in city events. We construct a social media dataset, compare the effectiveness of face recognition, object recognition, and cascaded methods for crowd size estimation, and investigate the impact of image characteristics on the performance of selected methods. Results show that object recognition based methods, reach the highest accuracy in estimating the crowd size using social media images in city events. We also found that face recognition and object recognition methods are more suitable to estimate the crowd size for social media images which are taken in parallel view, with selfies covering people in full face and in which the persons in the background have the same distance to the camera. However, cascaded methods are more suitable for images taken from top view with gatherings distributed in gradient. The created social media dataset is essential for selecting image characteristics and evaluating the accuracy of people counting methods in an urban event context., Transport and Planning, Human-Centred Artificial Intelligence, Transport and Planning

A largely overlooked mode choice factor of cycling is the mode-dependent capability of visiting several activity locations within a trip chain. Due to the bicycle’s limited reach in comparison to the car, this capability can be increased by urban environments that facilitate trip chaining by bicycle. In the present paper, we empirically study travel distances between activity locations that facilitate trip chaining by the example of Dutch commute tours. More precisely, we address the question of how much cyclists extend commute tour distances compared to car travellers to include a secondary activity. For this purpose, a Bayesian regression model is proposed to analyse the effects of travel mode, secondary activity type and a series of control variables such as age and time of the day on commute tour extensions. The model results propose that people make on average detours of 7.4 km by car and 1.3 km by bicycle. These values strongly differ depending on the type of secondary activity, gender, the distance of the home-work tour and the duration of the secondary activity. In addition, the comparison between car and bicycle travel revealed some behavioural peculiarities of the active modes, which have implications for bicycle-friendly urban planning and several transport-related concepts., Transport and Planning, Transport and Planning

In the pursuit of promoting cycling and providing better cycling infrastructure, its design is of great importance. One of the critical locations in a network are intersections, and specifically T-junctions, due to the inverted perception of priority. In this paper, we investigate the behaviour at T-junctions dedicated to cyclists and the effect on bicycle flow efficiency resulting from the introduction of lane markings that advise through cyclists to shift to the left so that merging cyclists can occupy the space on the right hand side of the cycle path. A comprehensive framework is proposed for the assessment of the T-junction efficiency. Empirical trajectory data from a large-scale cycling experiment are used for the analyses. The findings suggest that cyclist heterogeneity can be even more influential on the efficiency than the infrastructure design. Moreover, a form of self-organisation is observed, as through cyclists are willing to move to the left and allow merging cyclists to fit in the cycle path without the provision of any instructions. This means that the lane marking is both redundant and not improving the efficiency of the T-junction., Transport and Planning, Transport and Planning

Collecting pedestrian behaviour data is vital to understand pedestrian behaviour. This systematic review of 145 studies aims to determine the capability of contemporary data collection methods in collecting different pedestrian behavioural data, identify research gaps and discuss the possibilities of using new technologies to study pedestrian behaviour. The review finds that there is an imbalance in the number of studies that feature various aspects of pedestrian behaviour, most importantly (1) pedestrian behaviour in large complex scenarios, and (2) pedestrian behaviour during new types of high-risk situations. Additionally, three issues are identified regarding current pedestrian behaviour studies, namely (3) little comprehensive data sets featuring multi-dimensional behaviour data simultaneously, (4) generalizability of most collected data sets is limited, and (5) costs of pedestrian behaviour experiments are relatively high. A set of new technologies offers opportunities to overcome some of these limitations. This review identifies three types of technologies that can become a valuable addition to pedestrian behaviour research methods, namely (1) applying VR experiments to study pedestrian behaviour in the environments that are difficult or cannot be mimicked in real-life, repeat experiments to determine the impact of factors on pedestrian behaviour and collect more accurate behavioural data to understand the decision-making process of pedestrian behaviour deeply, (2) applying large-scale crowd monitoring to study pedestrian movements in large complex environments and incident situations, and (3) utilising the Internet of Things to track pedestrian movements at various locations that are difficult to investigate at the moment., Transport and Planning, Transport and Planning

Large-scale events are becoming more frequent in contemporary cities, increasing the need for novel methods and tools that can provide relevant stakeholders with quantitative and qualitative insights about attendees’ characteristics. In this work, we investigate how social media can be used to provide such insights. First, we screen a set of factors that characterize crowd behavior and introduce a set of proxies derived from social media data. We characterize the crowd in two city-scale events, Sail 2015 and King’s Day 2016, analyzing several properties of their attendees, including demographics, city-role, crowd temporal distribution, social media post locations, Point of Interest (PoI.) preferences, and word use. We show that it is possible to characterize crowds in city-scale events using social media data, thus paving the way for new real-time applications on crowd monitoring and management for city-scale events., Accepted Author Manuscript, Transport and Planning, Human-Centred Artificial Intelligence, Web Information Systems, Transport and Planning

A tool for travel time estimation of cyclists approaching a traffic light can monitor level of service of intersections in bike crowded cities. This work represents a first step in developing such a tool. Neural Network models are evaluated on how they perform in estimating individual travel time of cyclists approaching a signalized intersection. Based on simulated scenarios, in cities with low bicycle levels (deterministic scenario), Neural Networks are good travel time estimators whereas, in places with high bike volumes (where cyclists depart with a discharge rate) information on queued cyclists is crucial for travel time information., Accepted Author Manuscript, Transport and Planning, Team DeSchutter, Transport and Planning

Due to the increasing use of the bicycle as access and egress mode to public transport hubs, bicycle parking facilities are being constructed and extended. The provision of appropriate infrastructure requires the understanding of the needs and preferences of the cyclists. In order to gain insights into the parking spot choices of the cyclists, we have collected data at a bicycle parking facility in Delft train station (the Netherlands). This dataset is used to estimate discrete choice models that distinguish between an uncongested (i.e. many empty spots) and a congested (i.e. almost full) state of the facility. The findings reveal that cyclists want to park close to the exit of the parking facility which promotes the design in tiers. At the same time, they want to exert minimal effort, which calls for an easier mechanism to park in the top tier. Last but not least, providing real-time information signs is advisable, as it facilitates the parking spot choice as by reducing searching time., Accepted Author Manuscript, Transport and Planning

Density is one of the most relevant variables in a traffic flow description. For objects in 2 dimensions, density can be determined by the space that is allocated to each of the objects. This paper introduces a new way of computing the space available for a bicyclist, accounting for speed and accounting for the non-zero size of a bicycle. This changes local densities. The proposed method modifies the Voronoi densities, and assigns space to a bicycle. We assign space to bicycle A if it has a closer proximity to any point of bicycle A than any point of any other bicycle. The proximity is determined by the distance and the angle in relation to velocity of the bicycle. Specific proximity functions need to be formulated and calibrated to match cyclist behavior. This method helps to define a density level for cyclists, which in turn can for instance lead to a better indication of a Level of Service., Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public., Transport and Planning, Transport and Planning

The Urban Mobility Observatory (UMO) will gather, store, and disseminate empirical multi-modal traffic, transport and mobility data, using a well-balanced set of innovative data collection methods. It will make these comprehensive data available for scientific research to develop and test new theories and models to better understand, predict and facilitate multi-modal mobility in large urbanized regions. UMO is located in the Netherlands, being one of the densest urbanized countries in the world, facing severe accessibility problems and environmental pressures from transport., Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public., Transport and Planning, Transport and Planning

This paper describes a method to estimate the parameters of a Recursive link-based Logit model (RL) using measurements of a set of spatially fixed proximity sensors, with limited hit rates, which can uniquely identify people, such as Wi-Fi-, RFID- or Bluetooth-sensors. The observed ‘route’ of an individual, where we focus on pedestrians in an urban or event context, is modelled as the sequence of sensors that have identified the individual during his or her trip. Obviously, these ‘routes’ contain large gaps, which makes traditional estimation techniques not applicable. Although we do not exactly know what happens within these gaps, we do have some specific insight about the individuals behavior between two identifications; we know with a certain probability which is related to the hit rate of the sensors, that the individual did not cross another sensor location between the two identifications. This paper therefore describes a method to estimate the parameters of an RL model that specifically exploits this knowledge. The framework also allows us to formulate a probabilistic link utilization estimation method, which can be used to estimate link flows in a network based on the sensor observations. The effectiveness of the methodology is demonstrated in simulation using an artificial network, after which the methodology is tested on a real data set, collected at a Dutch music event., Transport and Planning, Transport and Planning

We present a design for a novel mobile sensing system (AMSense) that uses vehicles as mobile sensing nodes in a network to capture spatiotemporal properties of pedestrians and cyclists (active modes) in urban environments. In this dynamic, multi-sensor approach, real-time data, algorithms, and models are fused to estimate presence, positions and movements of active modes with information generated by a fleet of mobile sensing platforms. AMSense offers a number of advantages over the traditional methods using stationary sensor systems or more recently crowd-sourced data from mobile and wearable devices, as it represents a scalable system that provides answers to spatiotemporal resolution, intrusiveness, and dynamic network conditions. In this paper, we motivate the need and show the potential of such a sensing paradigm, which supports a host of new research and application development, and illustrate this with a practical urban sensing example. We propose a first design, elaborate on a variety of requirements along with functional challenges, and outline the research to be performed with the generated data., Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public., Transport and Planning, Information and Communication Technology, Transport and Planning

In ports and waterways, the impacts of external navigational factors may lead to serious incidents due to limited space for ship maneuvering. Using nautical traffic models, these incidents can be predicted in advance. In current studies of nautical traffic models, the impacts of wind and current on ship behavior are seldom considered when modeling the ship behavior in a port area. The numerical maneuvering models simulate the individual ship behavior under such impacts by calculating the hydrodynamic forces working on the ship's hull. However, the input, maneuvering particulars of individual ships, are not available in ports. In order to fill the knowledge gap of estimating ship behavior under external impacts without detailed ship maneuvering information, the impacts of wind and current on the observed dynamic ship behavior (speed over ground and leeway and drift angle) in ports and waterways have been investigated by analyzing Automatic Identification System data (showing ship paths over time) and the meteorological and hydrological data collected from the port of Rotterdam. The relation between unhindered speed variation and ship size is revealed. The regression analysis results on ships with similar size indicate the differences between wind and current impacts. Especially for small ships, the current impact on speed over ground outweighs the wind, while the wind influences the leeway and drift angle more than the current. Based on the quantified impact variation over ship size, the proposed impact mechanism explains the variance of speed over ground and leeway and drift angle. Some conventional sailing habits based on good seamanship, such as a series of small-angle alterations rather than direct turning at waypoints, are also revealed by the statistical analyses. Considering the variation of wind and current conditions in the study area, the analysis result provides generic quantitative insights into the wind and current impacts on the individual behavior o, Rivers, Ports, Waterways and Dredging Engineering, Transport and Planning, Transport and Planning

Travel information has the potential to influence travellers choices, in order to steer travellers to less congested routes and alleviate congestion. This paper investigates, on the one hand, how travel information affects route choice behaviour, and on the other hand, the impact of the travel time representation on the interpretation of parameter estimates and prediction accuracy. To this end, we estimate recursive models using data from an innovative data collection effort consisting of route choice observation data from GPS trackers, travel diaries and link travel times on the overall network. Though such combined data sets exist, these have not yet been used to investigate route choice behaviour. A dynamic network in which travel times change over time has been used for the estimation of both recursive logit and nested models. Prediction and estimation results are compared to those obtained for a static network. The interpretation of parameter estimates and prediction accuracy differ substantially between dynamic and static networks as well as between models with correlated and uncorrelated utilities. Contrary to the static results, for the dynamic, where travel times are modelled more accurately, travel information does not have a significant impact on route choice behaviour. However, having travel information increases the travel comfort, as interviews with participants have shown., Transport and Planning, Transport and Planning

This paper studies the relationship between trip chain complexity and daily travel behaviour of travellers. While trip chain complexity is conventionally investigated between travel modes, our scope is the more aggregated level of a person’s activity-travel pattern. Using data from the Netherlands Mobility Panel, a latent class cluster analysis was performed to group people with similar mode choice behaviour in distinct mobility pattern classes. All trip chains were assigned to both a travel mode and the mobility pattern class of the traveller. Subsequently, differences in trip chain complexity distributions were analysed between travel modes and between mobility pattern classes. Results indicate considerable differences between travel modes, particularly between multimodal and unimodal trip chains, but also between the unimodal travel modes car, bicycle, walking and public transport trip chains. No substantial differences in trip chain complexity were found between mobility pattern classes. Independently of the included travel modes, the distributions of trip chain complexity degrees were similar across mobility pattern classes. This means that personal circumstances such as the number of working hours or household members are not systematically translated into specific mobility patterns., Transport and Planning, Transport and Planning

We present a transit model that, based on automated fare collection and train tracking data, describes pedestrian movements in train stations and vehicle-specific train ridership distributions. Our approach differs from existing models in that we describe on-board passenger dynamics and pedestrian dynamics at stations in a joint framework. We assume that travelers first decide on the train(s) they will take, and then pursue their journey through the network by successively choosing pedestrian paths, waiting positions on platforms, and specific train cars. Travelers explicitly maximize their travel utility. We model how crowding influences their walking speeds, and how it affects travel utility both at stations and on-board. To illustrate the framework, we present a real case study of a major Dutch rail corridor, for which we collect a rich set of passenger, pedestrian and train operation data. We observe a good agreement of model estimates with empirical observations, and discuss the use of the model for various transit-related problems including level-of-service assessment, crowding estimation, transit optimization, and integrated investment appraisal., Transport and Planning, Transport and Planning

Macroscopic pedestrian models are theoretically simpler than microscopic models, and they can potentially be solved faster while producing reasonable predictions of crowd dynamics. Therefore, they can be very useful for applications such as large-scale simulation, real-time state estimation and crowd management. However, the numerical methods presently used to solve macroscopic pedestrian models, which are mostly grid-based, have some shortcomings that limit their applicability. More specifically, they usually include complex procedures for grid generation and remeshing, and they produce simulation results that may not be sufficiently accurate (for example, because of unclear boundaries between flow states). Smoothed Particle Hydrodynamics (SPH) constitutes an alternative numerical method that could potentially overcome these limitations. SPH is a meshfree method where a crowd is represented by a set of particles that possess material properties and move according to macroscopic laws. Relevant state variables at each particle are approximated using information about the material properties of the neighboring particles and a smoothing function. This paper puts forward for the first time a generic SPH framework for solving macroscopic pedestrian models; in addition, it demonstrates that an SPH-based simulation model can produce meaningful and accurate results by means of three case studies. The first case study shows that the proposed numerical method can approximate well the analytical solution of a simple macroscopic model applied to a queue-discharge scenario. The second case study demonstrates that the proposed numerical method can potentially reproduce density dispersion (a phenomenon observed in real crowds) more accurately than grid-based methods, due to its meshfree, Lagrangian, and particle-based nature. The third case study highlights the need to reformulate the acceleration equation of the basic macroscopic model in order to reproduce lane formation in bi-d, Transport and Planning, Transport and Planning

Large-scale events are becoming more frequent in contemporary cities, increasing the need for novel methods and tools that can provide relevant stakeholders with quantitative and qualitative insights about attendees’ characteristics. In this work, we investigate how social media can be used to provide such insights. First, we screen a set of factors that characterize crowd behavior and introduce a set of proxies derived from social media data. We characterize the crowd in two city-scale events, Sail 2015 and King’s Day 2016, analyzing several properties of their attendees, including demographics, city-role, crowd temporal distribution, social media post locations, Point of Interest (PoI.) preferences, and word use. We show that it is possible to characterize crowds in city-scale events using social media data, thus paving the way for new real-time applications on crowd monitoring and management for city-scale events., Accepted Author Manuscript, Transport and Planning, Human-Centred Artificial Intelligence, Web Information Systems, Transport and Planning

A tool for travel time estimation of cyclists approaching a traffic light can monitor level of service of intersections in bike crowded cities. This work represents a first step in developing such a tool. Neural Network models are evaluated on how they perform in estimating individual travel time of cyclists approaching a signalized intersection. Based on simulated scenarios, in cities with low bicycle levels (deterministic scenario), Neural Networks are good travel time estimators whereas, in places with high bike volumes (where cyclists depart with a discharge rate) information on queued cyclists is crucial for travel time information., Accepted Author Manuscript, Transport and Planning, Team Bart De Schutter, Transport and Planning

Due to the increasing use of the bicycle as access and egress mode to public transport hubs, bicycle parking facilities are being constructed and extended. The provision of appropriate infrastructure requires the understanding of the needs and preferences of the cyclists. In order to gain insights into the parking spot choices of the cyclists, we have collected data at a bicycle parking facility in Delft train station (the Netherlands). This dataset is used to estimate discrete choice models that distinguish between an uncongested (i.e. many empty spots) and a congested (i.e. almost full) state of the facility. The findings reveal that cyclists want to park close to the exit of the parking facility which promotes the design in tiers. At the same time, they want to exert minimal effort, which calls for an easier mechanism to park in the top tier. Last but not least, providing real-time information signs is advisable, as it facilitates the parking spot choice as by reducing searching time., Accepted Author Manuscript, Transport and Planning