Jon M. Kerridge

Agent-Based Modelling of Pedestrian Movements: The Questions That Need to Be Asked and Answered

Vulnerable road users have steadily attracted increased importance in transport and planning. The behaviour of pedestrian movements (especially in the areas off but adjacent to roads) requires improved tools to address the issues now being raised. Such behaviour and interactions can now be modelled by using a combination of massively parallel processes simulating individual pedestrians, and a series of behaviours of these simulated pedestrians in the interactions with each other and their environment. The PEDFLOW model has been implemented in the parallel processing language Occam as an agent-based evolutionary system, which allows extensive modelling of detailed pedestrian behaviour with minimal complication. The principles and methodology of its development and application are specified.

PEDFLOW: Development of an Autonomous Agent Model of Pedestrian Flow

The need for an autonomous agent approach for the modeling of pedestrians in urban environments is discussed, and PEDFLOW is placed in the context of existing models. PEDFLOW is a microscopic model of pedestrians’ movement; each pedestrian is represented as an agent capable of making its own decisions on the basis of a part of the observable scene local to that pedestrian. The model, implemented in Java, provides a framework in which agents are visualized as squares in a grid and movement is modeled as a change of grid position with a delay that characterizes the speed of the agent. A single rule set that is made specific to each agent by the incorporation of parameters characterizing types of pedestrians is used. The rules originate from computer-aided analysis of video footage and are transformed into a form that can be efficiently processed by the agent. By adding tools to extract measures of pedestrian flow, the PEDFLOW model will be made useful to urban planners to evaluate infrastructural changes intended to promote walking in the urban environment.

A product line based aspect-oriented generative unit testing approach to building quality components

The quality of component-based systems highly depends on how effectively testing is carried out. To achieve the maximal testing effectiveness, this paper presents a product line based aspect oriented approach to unit testing. The aspect product line facilitates the automatic creation of aspect test cases that deal with specific quality requirements. An expandable repository of reusable aspect test cases has been developed. A prototype tool is built to verify and lever up the approach.

Collecting Pedestrian Trajectory Data In Real-time

The ability to collect pedestrian flow data, without the need for subsequent post-processing and analysis to extract measurements such as density and flow rate is a goal, which up to now, has proved infeasible on a large scale for a number of reasons, such as the cost of processing the data, the ability of the people observing the scene or subsequent video tapes and the effects of variation in the lighting conditions of the area being observed. A system using low cost infrared sensors is described that can be used to track the movement of pedestrians within their field of view and the resulting data stream is then used to generate density, flow-rate and speed data and instantaneous counts every two seconds. This data is displayed and also saved in a file. In addition, the path taken by each pedestrian can also be written to file for post-processing. The processing system associated with the sensors has been designed to be scalable from the outset and we describe how this been achieved to ensure that the it can be used in a variety of application environments.

Scenario based Generative component Adaptation in .NET framework

Mismatches between pre-qualified existing components and the particular reuse context in applications have been a major factor hindering component reusability. Although component adaptation has acted as a key solution of eliminating these mismatches, it often appears impossible for adaptation at a deep level with tolerable code overheads and human work. In this paper, we address the above problem by realizing the Scenario based Generative component Adaptation (SAGA) approach in the .NET framework. The developed prototype tool (SAGA Bench) helps to achieve deep adaptation with little code overhead through three key techniques: XML-based component specification, interrelated adaptation scenarios, and corresponding component adaptation and generation. The whole process aims to be highly automatic, with necessary user interaction only at XML document level.

Achieving seamless component composition through scenario-based deep adaptation and generation

Mismatches between pre-qualified existing components and the particular reuse context in applications have been a major factor hindering component reusability and successful composition. Although component adaptation has acted as a key solution of eliminating these mismatches, deep adaptation is often either impossible or incurring heavy overheads in the components. This paper proposes an approach, namely Scenario-based dynamic component Adaptation and Generation (SAGA), to achieve deep adaptation with little code overhead through XML-based component specification, interrelated adaptation scenarios and corresponding component adaptation and generation.

USING LOW-COST INFRARED DETECTORS TO MONITOR MOVEMENT OF PEDESTRIANS: INITIAL FINDINGS

Monitoring the movement of pedestrians in everyday environments is difficult, especially if accurate data are required. Typically, data pertaining to the origins and destinations of pedestrians as they move around a space can be obtained only by either locating many observers in the area that is under surveillance or analyzing closed-circuit television footage. The former is error prone and perturbs the space being analyzed; the latter is expensive in regard to the technology and time required. Technical advances in low-cost infrared detectors provide an opportunity to observe pedestrian spaces unobtrusively and determine individual pedestrian trajectories automatically. The underpinning detector technology is described, and the way arrays of such detectors can be used to monitor larger spaces is shown. An outline of the algorithm used to create complete trajectories as pedestrians move between detectors is presented. A series of experiments is described: pedestrians were asked to move in a set of defined patterns in a controlled environment. Initial results from these experiments are discussed. It was found that at Fruin Levels of Service A to C, 93% of pedestrian trajectories could be tracked; that count dropped to 79% at Level of Service D.

Automated responsive web service evolution through generative aspect-oriented component adaptation

When building service oriented systems, it is often the case that existing web services do not perfectly match user requirements in target systems. To achieve smooth integration and high reusability of web services, mechanisms to support automated evolution of web services are highly in demand. This paper advocates achieving the above evolution by applying a highly automated aspect-oriented adaptation approach to the underlying components of web services by generating and then applying the adaptation aspects under designed weaving process according to specific adaptation requirements. An expandable library of reusable adaptation aspects at multiple abstraction levels has been developed. A prototype tool is developed to scale up the approach.

Generative aspect-oriented component adaptation

As a solution to eliminating component mismatches, a generative aspect- oriented approach to component adaptation is presented. The approach enjoys high level of automation and capability of deep level adaptation, which is achieved in an aspect-oriented component adaptation framework by generating and then applying the adaptation aspects under designed weaving process. The aspect generation mechanism facilitates the creation of adaptation aspects that support specific adaptation requirements. An expandable repository of reusable adaptation aspects has been developed based on the proposed two-dimensional aspect model. A prototype tool is built to as a leverage of the approach.

Achieving Dependable Component-Based Systems Through Generative Aspect Oriented Component Adaptation

Mismatches between pre-qualified existing components and the particular reuse context in applications are often inevitable and have been a major hurdle of component reusability and smooth composition. Although component adaptation has acted as a key solution of eliminating these mismatches, existing practices are either only capable for adaptation at a rather simple level, or requires too much intervention from software engineers. This paper presents a highly automated approach to component adaptation at adequately deep level. Its aspect-oriented nature makes the approach particularly suitable for constructing highly dependable component-based software. The adaptability and automation is achieved in an aspect-oriented component adaptation framework by generating and then applying the adaptation aspects under designed weaving process according to specific adaptation requirements. An expandable library of reusable adaptation aspects at multiple abstraction levels has been developed. A prototype tool is developed to scale up the approach