Despite a burgeoning research effort directed at the design and modelling of effective urban spaces for pedestrians, remarkably little is known about how pedestrians actually negotiate urban spaces. This paper reports the results of a video-based observational study aimed at exploring: (1) individuals' movement preferences within uncluttered environments, in particular: (a) desired walking speed, (b) microscopic position preferences, and (c) interpersonal distances between companions while walking; and (2) the ways in which these variables might be influenced by the various personal, situational, and environmental factors that characterise the context in which pedestrians move. The microscopic movement trajectories of 2613 participants were investigated in a covert, video-based observational study of three mixed-use (residential/retail) urban environments close to the city centres of Edinburgh and York, United Kingdom. Age, gender, level of mobility, group size, time of day, and location were found to have significant effects on movement preferences across the range of locations studied. We concluded that a number of influential factors affect how humans negotiate urban spaces, and suggested how these factors may be taken into account in attempts to design and model effective urban spaces for pedestrians.

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.

The paper discusses the need for an autonomous agent approach for the modeling of pedestrians in urban environments and places PEDFLOW in the context of existing models. PEDFLOW is a microscopic model of pedestrians' movement, where each pedestrian is represented as an agent capable of making its own decisions based upon a part of the observable scene local to that pedestrian. The model, implemented in Java, provides a framework where agents are visualised as squares in a grid and movement is modelled as a change of grid position with a delay that characterises the speed of the agent. A single rule set is utilised that is made specific to each agent by the incorporation of parameters characterising 'types' of pedestrians. 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.

No abstract

No abstract