Public transport and pedestrian access, the impact of suburban planning on adolescence

The following paper discusses the impact of suburban life for adolescents in relation to public transport and pedestrian access. The research compares the morphology and level of connectivity of two planning models, cul-de-sac and regular grid, with respect to two suburbs which share a similar socio-economic profile, Rowville and Caulfield. These are subsequently evaluated in terms of ABS statistics, in particular year 12 or equivalent levels of education, and transport statistics. The results of the investigation are discussed in reference to the four key tasks of adolescence (Carr-Greg & Shale 2002)', in order to establish the degree to which morphology and access levels of suburbs impact on adolescent development.

Comparative evaluation of pedestrian detection methods for mobile bus surveillance

We present a comparative evaluation of the state-of-art algorithms for detecting pedestrians in low frame rate and low resolution footage acquired by mobile sensors. Four approaches are compared: a) The Histogram of Oriented Gradient (HoG) approach [1]; b) A new histogram feature that is formed by the weighted sum of both the gradient magnitude and the filter responses from a set of elongated Gaussian filters [2] corresponding to the quantised orientation, called Histogram of Oriented Gradient Banks (HoGB) approach; c) The codebook based HoG feature with branch-and-bound (efficient subwindow search) algorithm [3] and; d) The codebook based HoGB approach. Results show that the HoG based detector achieves the highest performance in terms of the true positive detection, the HoGB approach has the lowest false positives whilst maintaining a comparable true positive rate to the HoG, and the codebook approaches allow computationally efficient detection.

Pedestrian detection for mobile bus surveillance

In this paper, we present a system for pedestrian detection involving scenes captured by mobile bus surveillance cameras in busy city streets. Our approach integrates scene localization, foreground and background separation, and pedestrian detection modules into a unified detection framework. The scene localization module performs a two stage clustering of the video data. In the first stage, SIFT Homography is applied to cluster frames in terms of their structural similarities and second stage further clusters these aligned frames in terms of lighting. This produces clusters of images which are differential in viewpoint and lighting. A kernel density estimation (KDE) method for colour and gradient foreground-background separation are then used to construct background model for each image cluster which is subsequently used to detect all foreground pixels. Finally, using a hierarchical template matching approach, pedestrians can be identified. We have tested our system on a set of real bus video datasets and the experimental results verify that our system works well in practice.

Fuzzy simulation of pedestrian walking path considering local environmental stimuli

Pedestrian steering activity is a perception-based decision making process that involves interaction with the surrounding environment and insight into environmental stimuli. There are many stimuli within the environment that influence pedestrian wayfinding behaviour during walking activities. However, compelling factors such as individual physical and psychological characteristics and trip intention cause the behaviour become a very fuzzy concept. In this paper pedestrian steering behaviour is modelled using a fuzzy logic approach. The objective of this research is to simulate pedestrian walking paths in indoor public environments during normal and non-panic situations. The proposed algorithm introduces a fuzzy logic framework to predict the impact of perceived attractive and repulsive stimuli, within the pedestrian's field of view, on movement direction. Environmental stimuli are quantified using the social force method. The algorithm is implemented in a simulated area of an office corridor consist of a printer and exit door. Stochastic simulation using the proposed fuzzy algorithm generated realistic walking trajectories, contour map of dynamic change of environmental effects in each step of movement and high flow areas in the corridor.

Pedestrian steering behaviour modelling within the built environment

Prediction of pedestrians’ steering behaviours within the built environments under normal and non-panic situations is useful for a wide range of applications, which include social science, psychology, architecture, and computer graphics. The main focus is on prediction of the pedestrian walking paths and the influences from the surrounding environment from the engineering point of view.

The association between attributions of responsibility for motor vehicle accidents and patient satisfaction: a study within a no-fault injury compensation system

This study set out to test the relationship between attributions of responsibility for motor vehicle accidents and satisfaction with personal injury compensation systems.

A genetic fuzzy system to model pedestrian walking path in a built environment

A study on the pedestrian's steering behaviour through a built environment in normal circumstances is presented in this paper. The study focuses on the relationship between the environment and the pedestrian's walking trajectory. Owing to the ambiguity and vagueness of the relationship between the pedestrians and the surrounding environment, a genetic fuzzy system is proposed for modelling and simulation of the pedestrian's walking trajectory confronting the environmental stimuli. We apply the genetic algorithm to search for the optimum membership function parameters of the fuzzy model. The proposed system receives the pedestrian's perceived stimuli from the environment as the inputs, and provides the angular change of direction in each step as the output. The environmental stimuli are quantified using the Helbing social force model. Attractive and repulsive forces within the environment represent various environmental stimuli that influence the pedestrian's walking trajectory at each point of the space. To evaluate the effectiveness of the proposed model, three experiments are conducted. The first experimental results are validated against real walking trajectories of participants within a corridor. The second and third experimental results are validated against simulated walking trajectories collected from the AnyLogic® software. Analysis and statistical measurement of the results indicate that the genetic fuzzy system with optimised membership functions produces more accurate and stable prediction of heterogeneous pedestrians' walking trajectories than those from the original fuzzy model. © 2014 Elsevier B.V. All rights reserved.

Attributions of responsibility for motor vehicle accidents and post-injury outcomes.

 This thesis explored the relationship between attributions of responsibility for motor vehicle accidents and post-injury outcomes among a large sample of TAC clients. Results demonstrated that, despite similar levels of physical injury, people who attribute responsibility for accidents to other persons or circumstances experience poorer physical and mental health recovery in comparison to those who attribute responsibility to themselves.

Urban growth and pedestrian thermal comfort

Melbourne is the second largest city in Australia, and its population is anticipated to reach 6.5 million by 2050. In October 2013, Plan Melbourne was released by Victorian government, aiming to intensify several districts to protect the suburbs from urban sprawl. The City of Melbourne’s draft municipal strategic statement identified City North as a great urban renewal area which can accommodate a significant part of the growth. Given the previous heat-related incidence in Melbourne in 2009, the potential threat to human health and pedestrian comfort will be exacerbated, if planning professionals exclude climatic conscious urban design in their practices. Therefore, this study aims to investigate the effect of the future structural plans on the microclimate and pedestrian thermal comfort in City North through numerical simulations. A three dimensional numerical modelling system, ENVI-met was used for the simulation. Field measurements were conducted across the study area to validate the simulated outputs. A clear reduction was reported in the average daytime mean radiant temperature, surface temperature and PMV values after implementing “Plan Melbourne” strategies. The outcomes of this study will assist urban planners in developing the policies which can effectively decrease the vulnerability to the heat stress at pedestrian level.

Review on the impact of urban geometry and pedestrian level greening on outdoor thermal comfort

The number of hot days is increasing in many parts of the world because of the heat island phenomenon and global climate change. High air temperature greatly affects human thermal comfort and public health, particularly in urban areas. Therefore, the challenging task of, urban designers and urban planners in accommodating the increasing population is to make cities with the least level of vulnerability to future climate change. Interest in transferring urban climatic knowledge into urban planning practices, and developing mitigation strategies to adapt to climate change, has been increased in recent years. The use of vegetation and appropriate urban geometry are shown very promising in mitigating the adverse effects of heat island and providing a better pedestrian thermal comfort. This article reviews studies on pedestrian level urban greening and geometry in improving thermal comfort in cities. Such strategies can be applied at the preliminary stages of urban planning and thus directly affect the microclimate. The analyzed data include simulation and field measurement studies. The discussion of this research clearly reflects how urban design guidelines can be applied to enhance outdoor thermal comfort and minimize the heat island effect. This study is helpful in controlling the consequences of city design from the early design stage.

Big data analytics and visualization with spatio-temporal correlations for traffic accidents

Big data analytics for traffic accidents is a hot topic and has significant values for a smart and safe traffic in the city. Based on the massive traffic accident data from October 2014 to March 2015 in Xiamen, China, we propose a novel accident occurrences analytics method in both spatial and temporal dimensions to predict when and where an accident with a specific crash type will occur consequentially by whom. Firstly, we analyze and visualize accident occurrences in both temporal and spatial view. Second, we illustrate spatio-temporal visualization results through two case studies in multiple road segments, and the impact of weather on crash types. These findings of accident occurrences analysis and visualization would not only help traffic police department implement instant personnel assignments among simultaneous accidents, but also inform individual drivers about accident-prone sections and the time span which requires their most attention.