Abstract Measures of walkability generally do not provide a detailed quantitative assessment pedestrian infrastructure development prioritization. In this study, link-based composite measure and walking is introduced to overcome limitation. This measure, called ‘pednet score’, based on weighted network (‘pednet’) made sidewalks crosswalks whose edge weights are descriptive their popularity. Edg...

Deployment Video on Demand (VoD) over the next generation (WiMAX) has become one of the intense interest subjects in the research these days, and is expected to be the main revenue generators in the near future. In this paper, the performance of Quilty of Service of video streaming (IPTV) over fixed mobile WiMax network is investigated under different terrain environments, namely Free Space, Ou...

cityseer-api is a Python package consisting of computational tools for fine-grained street-network and land-use analysis, helpful in assessing the morphological precursors to vibrant neighbourhoods. It underpinned by network-based methods developed specifically urban analysis at pedestrian scale. computes variety node segment-based network centrality methods, accessibility mixed-use measures, s...

The safety of vulnerable road users is paramount importance as transport moves towards fully automated driving. richness real-world data required for testing autonomous vehicles limited and furthermore, available do not present a fair representation different scenarios rare events. Before deploying publicly, their abilities must reach threshold, least with regards to users, such pedestrians. In...

Fusion of laser and vision in object detection has been accomplished by two main approaches: (1) independent integration of sensor-driven features or sensor-driven classifiers, or (2) a region of interest (ROI) is found by laser segmentation and an image classifier is used to name the projected ROI. Here, we propose a novel fusion approach based on semantic information, and embodied on many lev...

We present new achievements on the use of deep convolutional neural networks (CNN) in the problem of pedestrian detection (PD). In this paper, we aim to address the following questions: (i) Given non-deep state-of-the-art pedestrian detectors (e.g. ACF, LDCF), is it possible to improve their top performances ?; (ii) is it possible to apply a pre-trained deep model to these detectors to boost th...

Landmarks provide the most predominant navigation cue for pedestrian navigation. Very few navigation data models in the geographical information science and transportation communities support modeling of landmarks and use of landmark-based route instructions for pedestrian navigation services. This article proposes a landmark-based pedestrian navigation data model to fill this gap. This data mo...

In this paper we evaluate the effectiveness of using a Region-based Convolutional Neural Network approach to the problem of pedestrian detection. Our dataset is composed of manually annotated video sequences from the ETH vision lab. Using selective search as our proposal method, we evaluate the performance of several neural network architectures as well as a baseline logistic regression unit. W...