相关论文: Vision-based Pedestrian Alert Safety System (PASS)…

The mortality rate for pedestrians using wheelchairs was 36% higher than the overall population pedestrian mortality rate. However, there is no data to clarify the pedestrians' categories in both fatal and nonfatal accidents, since police…

Visually impaired people face significant challenges in their day-to-day commutes in the urban cities of Bangladesh due to the vast number of obstructions on every path. With many injuries taking place through road accidents on a daily…

For automated vehicles (AVs) to reliably navigate through crosswalks, they need to understand pedestrians crossing behaviors. Simple and reliable pedestrian behavior models aid in real-time AV control by allowing the AVs to predict future…

Collisions between vehicles and pedestrians usually result in the fatality to the vulnerable road users (VRUs). Thus, new technologies are needed to be developed for protecting the VRUs. Based on the high density of pedestrians and limited…

Intersections are hazardous places. Threats arise from interactions among pedestrians, bicycles and vehicles, more complicated vehicle trajectories in the absence of lane markings, phases that prevent determining who has the right of way,…

Pedestrian fatalities continue to rise in the United States, driven by factors such as human distraction, increased vehicle size, and complex traffic environments. Advanced Driver Assistance Systems (ADAS) offer a promising avenue for…

The recent surge in interest in autonomous driving stems from its rapidly developing capacity to enhance safety, efficiency, and convenience. A pivotal aspect of autonomous driving technology is its perceptual systems, where core algorithms…

Predicting pedestrian crossing intention is an indispensable aspect of deploying advanced driving systems (ADS) or advanced driver-assistance systems (ADAS) to real life. State-of-the-art methods in predicting pedestrian crossing intention…

We propose a safe DRL approach for autonomous vehicle (AV) navigation through crowds of pedestrians while making a left turn at an unsignalized intersection. Our method uses two long-short term memory (LSTM) models that are trained to…

Today's major concern in traffic management systems includes time-efficient emergency transports. The awareness of environment and vehicle information is necessary for the emergency vehicles as well as the surrounding commercial vehicles…

While the development of Vehicle-to-Vehicle (V2V) safety applications based on Dedicated Short-Range Communications (DSRC) has been extensively undergoing standardization for more than a decade, such applications are extremely missing for…

Event cameras like Dynamic Vision Sensors (DVS) report micro-timed brightness changes instead of full frames, offering low latency, high dynamic range, and motion robustness. DVS-PedX (Dynamic Vision Sensor Pedestrian eXploration) is a…

Detecting pedestrians accurately in urban scenes is significant for realistic applications like autonomous driving or video surveillance. However, confusing human-like objects often lead to wrong detections, and small scale or heavily…

Distracted pedestrians, like distracted drivers, are an increasingly dangerous threat and precursors to pedestrian accidents in urban communities, often resulting in grave injuries and fatalities. Mitigating such hazards to pedestrian…

Road safety is the main motivation for Cooperative Intelligent Transport Systems (C-ITS) in general, and vehicular communications (V2X) technology in particular. The V2X-based Vulnerable Road User (VRU) protection is an approach that relies…

Multispectral pedestrian detection has attracted increasing attention from the research community due to its crucial competence for many around-the-clock applications (e.g., video surveillance and autonomous driving), especially under…

In this paper, we propose a deep learning based assistive system to improve the environment perception experience of visually impaired (VI). The system is composed of a wearable terminal equipped with an RGBD camera and an earphone, a…

Understanding and predicting pedestrian crossing behavior is essential for enhancing automated driving and improving driving safety. Predicting gap selection behavior and the use of zebra crossing enables driving systems to proactively…

This paper presents a novel end-to-end system for pedestrian detection using Dynamic Vision Sensors (DVSs). We target applications where multiple sensors transmit data to a local processing unit, which executes a detection algorithm. Our…

In this paper, we address an issue that the visually impaired commonly face while crossing intersections and propose a solution that takes form as a mobile application. The application utilizes a deep learning convolutional neural network…