# Vulnerable Road User Detection for Roadside-Assisted Safety Protection: A Comprehensive Survey
###### Abstract  
In recent years, the safety of vulnerable road users (VRUs), such as pedestrians, cyclists, and micro-mobility users, has become an increasingly significant concern in urban transportation systems worldwide. Reliable and accurate detection of VRUs is essential for effective safety protection. This survey explores the techniques and methodologies used to detect VRUs, ranging from conventional methods to state-of-the-art (SOTA) approaches, with a primary focus on infrastructure-based detection. This study synthesizes findings from recent research papers and technical reports, emphasizing sensor modalities such as cameras, LiDAR, and RADAR. Furthermore, the survey examines benchmark datasets used to train and evaluate VRU detection models. Alongside innovative detection models and sufficient datasets, key challenges and emerging trends in algorithm development and dataset collection are also discussed. This comprehensive overview aims to provide insights into current advancements and inform the development of robust and reliable roadside detection systems to enhance the safety and efficiency of VRUs in modern transportation systems. vulnerable road users (VRUs); object detection; safety; intelligent transportation system (ITS) +
Footnote †: journal: Applied sciences  
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system is a major challenge. With the advancement in computer vision technology, more advanced detection methods have been proposed continuously over the past decades, using either 2D or 3D object detection. From the perspective of traffic management departments, the increasing availability of cost-effective and highly accurate sensors in recent years presents an opportunity to enhance real-time detection and protection of vulnerable road users, in addition to their traditional use for monitoring traffic flow. Usually, roadside sensors are mounted on the poles at the intersections and middle blocks with fixed locations and angles, which is different from onboard sensors' operating conditions. With well-developed sensors and corresponding detection models, VRUs can be detected accurately, which brings the following benefits: (1) VRU safety can be assured as much as possible; (2) drivers could be aware of the situation by receiving the warning messages in advance if the vehicle/smartphone is connected to the roadside unit (RSU); and (3) the intersection could be smarter by optimizing the priority and phase duration for different road users, especially VRUs. Roadside detection systems have made significant strides in practical applications to safeguard Vulnerable Road Users (VRUs). Key examples include the Intelligent Roadside Unit (IRSU) developed by the University of Sydney and Cohda Wireless, which integrates camera and LiDAR sensors for precise VRU detection [4], and Commsignia's V2X units [5], which combine cameras, LiDAR, and RADAR to enhance traffic services and VRU protection. Ouster's BlueCity solution [6], implemented in Chattanooga, utilizes LiDAR-based traffic management to optimize signal timings and improve safety by processing real-time data [7]. These systems showcase the effectiveness of roadside detection technologies in improving VRU safety and traffic management. Additionally, the National Highway Traffic Safety Administration (NHTSA) is advancing connected vehicle systems, underscoring the continued importance of such technologies in creating safer roadways for VRUs, reducing accidents, and optimizing traffic management globally. Unlike previous surveys that focus solely on vehicle or pedestrian detection, this paper provides a comprehensive review of VRU detection models and datasets from a roadside perspective, which is an area that has not been systematically explored in detail. This survey will explicitly answer the following questions: (1) What sensors should be used for roadside VRU detection? (2) What models should be used for each type of sensor?