In this paper, a fuzzy logic control system was constructed for controlling the green time length for a real single intersection with multiple lanes, turns, and two pedestrian crossings. Control of pedestrian crossingd was achieved by assigning pedestrian crossingd into related light phases, which were controlled by a fuzzy logic controller. An evolutionary algorithm was employed to generate th...

We present a planning framework for producing socially competent robot behaviors in pedestrian environments. The framework is designed according to conclusions of recent psychology studies on action interpretation and sociology studies on human pedestrian behavior. The core of the approach is a novel topological representation of the pedestrian scene, based on braid groups. Thanks to this repre...

The complexity of vehicle-pedestrian collisions necessitates extensive validation of pedestrian computational models. While body components can be individually simulated, overall validation of human pedestrian models requires full-scale testing with post mortem human surrogates (PMHS). This paper presents the development of a full-scale pedestrian impact test plan and experimental design, and s...

We present a novel pedestrian representation based on a new model of pedestrian motion coupled with a geometric optimization method. The model of pedestrian motion seeks to capture the underlying physiological and psychological factors which give rise to the fundamental diagram — the phenomenon that pedestrian speed reduces as density increases. The optimization method computes collision-free v...

Pedestrian detection is a hot topic in computer vision and pattern recognition. Existing pedestrian detection methods face new challenges in the background of big data, e.g., heavy burdens on computing and memory. To solve these problems, in this paper, we propose a pedestrian detection framework based on incremental learning. Compared with existing pedestrian detection frameworks, it costs muc...

Pedestrian behavioral modeling is a topic that is receiving more and more attention in different areas of application such as panic analysis, building evacuation and surveillance systems. We propose a model based on discrete choice theory for pedestrian dynamic behavior. Our model is based on a local discretization of the space around each pedestrian, as opposed to other models which are contin...

We present a new method for obstacle and pedestrian detection with lower computation complexity and higher detection performance on a small target. By calculating stereo disparity according to the road parameters, our system efficiently detects objects above the ground. Experiments on over 10,000 images captured in urban areas demonstrate our method’s effectiveness. We also propose a multi-scal...

We present a novel framework for socially competent pedestrian navigation based on understanding pedestrians’ intentions and planning intent-expressive robot motion. We model pedestrians’ intentions as combinations of intended topological routes and intended destinations. The core of this approach is a novel topological representation of a pedestrian scene, based on braid groups. This represent...

Learning to recognize pedestrian attributes at far distance is a novel research topic in video surveillance scenarios where face and body close-shots are hardly available; instead, only far-view video frames of pedestrian are given. In this study, we present an alternative approach that exploits the context of neighboring pedestrian images for improved attribute inference compared to the conven...

We have introduced excluded volume effect, which is an important factor to model a realistic pedestrian queue, into queueing theory. The probability distributions of pedestrian number and pedestrian waiting time in a queue have been calculated exactly. Due to time needed to close up the queue, the mean number of pedestrians increases as pedestrian arrival probability (λ) and leaving probability...