K-Median Problem on Graph

In past decades there has been a tremendous growth in the literature on location problems. However, among the myriad of formulations provided, the simple plant location problem and the k-median problem have played a central role. This phenomenon is due to the fact that both problems have a wide range of real-world applications, and a mathematical formulation of these problems as an integer program has proven very fruitful in the derivation of solution methods. In this paper we investigate the k-median problem defined on a graph. That is, each point represents a vertex of a graph

RapidBridgeBuilder-simulation tool for accelerated bridge design and construction

This paper presents RapidBridgeBuilder, a discrete-event special-purpose simulation modeling tool for accelerated bridge design and construction geared towards practitioners. The paper explores the capabilities of the system by modeling a bridge operation as a case study. The design and operation of bridge construction are initially modeled with input parameters and are successively improved based on insights obtained from the static and dynamic outputs of the previous model. The paper also describes the tools and techniques that were used to develop the simulator

Pedestrian tracking framework utilising computer vision for rapid analysis of public spaces

The ability to record the trajectories and interactions of pedestrians in public places is necessary to understand, model and analyse the performance of built environments. However, few options are available to researchers to gather this information. Traditionally, simple point-counting techniques or video analysis performed with human sight have been relied upon to collect the required data, but these methods have limitations. Tracking the movements of pedestrians in public areas with point-counters can only reveal abstract flow patterns and lacks the potential to capture fine-grained detail. Human observation is useful for capturing the fine-grained detail of individual trajectories, but is rarely a tractable solution. Recent advances in computer vision have allowed for automatic pedestrian tracking and interaction capture in open public spaces. Here, we present a framework, based on existing technology that can be used to build a pedestrian tracking and trajectory analysis application which solves the tractability issues associated with human visual analysis. Our framework is especially useful for capturing the movements of pedestrians in open public spaces such as public transport platforms, which will provide researchers with a finer level of detail than previously possible. It should be noted that this framework is aimed at researchers who wish to perform post-processing analysis of recorded video, rather than those who wish to capture the data in real time

Graph-based analysis of city-wide traffic dynamics using time-evolving graphs of trajectory data

This paper proposes a graph-based approach to representing spatio-temporal trajectory data that allows an effective visualization and characterization of city-wide traffic dynamics. With the advance of sensor, mobile, and Internet of Things (IoT) technologies, vehicle and passenger trajectories are increasingly being collected in massive scale and are becoming a critical source of insight into traffic pattern and traveller behaviour. To leverage such trajectory data to better understand traffic dynamics in a large-scale urban network, this study develops a trajectory-based network traffic analysis method that converts individual trajectory data into a sequence of graphs that evolve over time (known as dynamic graphs or time-evolving graphs) and analyses network-wide traffic patterns in terms of a compact and informative graph-representation of aggregated traffic flows. First, we partition the entire network into a set of cells based on the spatial distribution of data points in individual trajectories, where the cells represent spatial regions between which aggregated traffic flows can be measured. Next, dynamic flows of moving objects are represented as a time-evolving graph, where regions are graph vertices and flows between them are treated as weighted directed edges. Given a fixed set of vertices, edges can be inserted or removed at every time step depending on the presence of traffic flows between two regions at a given time window. Once a dynamic graph is built, we apply graph mining algorithms to detect change-points in time, which represent time points where the graph exhibits significant changes in its overall structure and, thus, correspond to change-points in city-wide mobility pattern throughout the day (e.g., global transition points between peak and off-peak periods)

Trajectory Flow Map: Graph-based approach to analyse temporal evolution of aggregated traffic flows in large-scale urban networks

This paper proposes a graph-based approach to representing spatio-temporal trajectory data that allows an effective visualization and characterization of city-wide traffic dynamics. With the advance of sensor, mobile, and Internet of Things (IoT) technologies, vehicle and passenger trajectories are being increasingly collected on a massive scale and are becoming a critical source of insight into traffic pattern and traveller behaviour. To leverage such trajectory data to better understand traffic dynamics in a large-scale urban network, this study develops a trajectory-based network traffic analysis method that converts individual trajectory data into a sequence of graphs that evolve over time (known as dynamic graphs or time-evolving graphs) and analyses network-wide traffic patterns in terms of a compact and informative graph-representation of aggregated traffic flows. First, the authors partition the entire network into a set of cells based on the spatial distribution of data points in individual trajectories, where the cells represent spatial regions between which aggregated traffic flows can be measured. Next, dynamic flows of moving objects are represented as a time-evolving graph, where regions are graph vertices and flows between them are treated as weighted directed edges. Given a fixed set of vertices, edges can be inserted or removed at every time step depending on the presence of traffic flows between two regions at a given time window. Once a dynamic graph is built, the authors apply graph mining algorithms to detect change-points in time, which represent time points where the graph exhibits significant changes in its overall structure and, thus, correspond to change-points in city-wide mobility pattern 24 throughout the day (e.g., global transition points between peak and off-peak periods)

Agent-based simulation modeling of a Bus Rapid Transit (BRT) station using smart card data

A Bus Rapid Transit (BRT) station with multiple loading zones tends to have a longer passenger-bus interface and, thus, lead to longer passenger walking times and longer bus dwell times than ordinary bus stops. As a way to reduce bus dwell times in a BRT station, this study focuses on eliminating delays in passengers' reaction to their desired bus by designing an improved passenger information system (PIS) that can increase passengers' certainty about the bus stopping location. This study develops an agent-based simulation model based on observations from a BRT station in Brisbane, Australia to reflect a real BRT operations and passenger flows. The input parameters for the simulation model are calibrated with actual data including smart card records, field measurements, and video recordings. After mapping passenger moving and waiting patterns, and allocation logic of bus loading areas, various what-if analyses can be performed to design better passenger information systems

Evaluating the impact of improvement of wayfinding at a train station: agent-based simulation study

Major commuter railway stations tend to face issues with wayfinding, including ease of use & clarity. In peak times, users stopped at wayfinding signs & boards can cause congestion at key points on the concourse and on the platform. As a result, passenger satisfaction is negatively affected, and both occasional and regular users have their experience degraded. This study thus aims to improve passenger satisfaction in the passenger experience from when they first enter the station, until they board their train. This is achieved by moving wayfinding away from high-flow areas of the concourse and platform, and improving signage by making signage easier to read from a distance, simplify the network map to make it easier to understand where a train is going, and have dynamic displays. The proposed system causes the amount of time passengers spend at wayfinding to be reduced, as well as moving stationary and slow-moving passengers away from high-flow areas. An agent-based simulation model is used to model dynamic behaviours of heterogeneous passengers along a platform as a proof of concept. This paper develops an agent-based model which enables the testing of various hypothetical scenarios, representing different positioning of wayfinding screens on the concourse & platform. The input parameters (passenger volumes and distribution of passengers along the concourse) for the simulation are prepared based on historical smart card data. The results from the simulation suggest that moving service points can ease congestion at key choke points, such as near escalators and in the middle of the concourse. Additionally, feedback on the passenger experience was obtained by an online survey to gain an understanding of the passenger experience and how it could be improved. The survey results are also used to extend the conceptual simulation model to reflect actual operations and passenger flow

Characterizing travel time distributions in earthmoving operations using GPS data

Recent advances in sensor technology have led to enhanced data acquisition capabilities in construction sites. A wealth of data are being collected from GPSequipped heavy vehicles for a wide range of monitoring, management, and analysis purposes. The availability of detailed GPS trajectory data has opened up new opportunities for modeling and simulation of real-world construction operations. One of the emerging areas in this regard is data-driven modeling and simulation, which is a modeling framework that attempts to automatically generate discrete-event simulation (DES) models based on a rich set of observed data as well as dynamically adapt the generated model to changes in data. Within the overall framework of automatically generating a DES simulation model for earthmoving operations, this paper focuses on developing methods to convert complex movement data collected from scrapers into a modeling element of activity-cycle diagram and activity scanning modeling paradigm-based DES system. Scraper changes travel routes at every cycle and its trip patterns (e.g., travel path and speed) are very difficult to generalize using a known parametric model (e.g., theoretical probability distribution), which in turn complicates the problem of automatic model generation. To deal with this issue, this paper proposes the use of relation between travel time and travel distance with regard to coefficient of variation measures, expressed in two separate distributions, to capture information needed to construct speed and path scenarios

Real-time information system for spreading rail passengers across train carriages: Agent-based simulation study

Commuter trains with multiple carriages tend to have varying distribution of passengers. At peak times, this can cause disproportionate occupancy rates of carriages, as well as crowding within the train and along the platform. As a result, passenger satisfaction is negatively affected as indicated by high sectional density and seat unavailability. This study, thus, aims to improve Queensland Rail passenger satisfaction in the boarding, riding, and alighting of trains. This is achieved via an improved passenger information system (PIS) that relays carriage occupancy levels to waiting passengers prior to the arrival of each train. The proposed system influences the passenger decision making process of where to wait along the platform by allowing them to take into account the occupancy rate of each carriage. It also offers a degree of certainty in regard to seat availability and ease of boarding. Passengers will then be capable of distributing themselves among low-occupancy train carriages in advance. An agent-based simulation approach is used to model dynamic behaviours of heterogeneous passengers along a platform as a proof of concept study. The paper develops a conceptual agent-based model that enables us to test various hypothetical scenarios representing different PIS settings as a case study focusing on a train station in Brisbane, Queensland, Australia. The input parameters (passenger volume and boarding/alighting passenger distribution) for the simulation model are prepared based on historical smart card records. The results from the simulation analysis suggest that the carriage occupancy information relay system can improve the distribution of passengers, thus increasing passenger satisfaction levels. Additionally, passenger behaviour data was obtained via an online survey to gain an understanding of passenger perceptions and tolerance of railway crowding within the Brisbane rail network. The survey results are to be used to extend the conceptual simulation model to reflect real-world operations and passenger distributions