To reduce the false detection rate of vehicle targets caused by occlusion, an improved method in different traffic scenarios based on YOLO v5 network is proposed. The proposed uses Flip-Mosaic algorithm to enhance network’s perception small targets. A multi-type target dataset collected was set up. model trained dataset. experimental results showed that data enhancement can improve accuracy and rate.

This study proposes an explainable extreme gradient boosting (XGBoost) model for predicting the international roughness index (IRI) and identifying key influencing factors. A comprehensive dataset integrating multiple data sources, such as structure, climate traffic load, is constructed. voting-based feature selection strategy adopted to identify factors, which are used inputs prediction model. Multiple machine learning (ML) models trained predict IRI with constructed dataset, XGBoost...

The existing connected-vehicle deployments obtain the real-time status of connected vehicles, but without knowing unconnected traffic. It is urgent to find an approach collecting high-resolution road users. This paper introduces a new-generation light detection and ranging (LiDAR) enhanced infrastructures that actively sense surrounding traffic participants with roadside LiDAR sensors broadcast messages through DSRC units. data processing procedure, including background filtering, object...

The application of infrared camera-related technology is a trending research topic. By reviewing the development thermal imagers, this paper introduces several main processing technologies expounds image nonuniformity correction, noise removal, and pseudo color enhancement briefly analyzes some algorithms used in processing. blind element detection compensation, temperature measurement, target detection, tracking imager are described. analyzing tracking, advantages disadvantages these put...

How to collect the real-time information of unconnected vehicles has been a challenge for connected vehicle technologies. The LiDAR sensors deployed along roadside and at intersections provide solution fill data gap during transition from traditional traffic full traffic. can record movement all road users with relative long detection range. lane serves as fundamental but important step processing. location (which is occupied) be used changing detection, departure warning wrong-way alerts....

The high-resolution traffic data (HRTD) of all roadway users is important to connected-vehicle systems, safety analysis, performance evaluation and fuel efficiency study. roadside LiDAR (light detection ranging) sensors can provide HRTD by collecting real-time 3D point clouds surrounding objects, which significant applications with mixed flow - connected unconnected road users. background filtering a necessary step improve the accuracy extraction from raw data. At same time, lane space...

This research presented a new approach for vehicle classification using roadside LiDAR sensor. Six features (one feature, object height profile, contains 10 sub-features) extracted from the trajectories were applied to distinguish different classes of vehicles. The aims assign objects into ten types defined by FHWA. A database containing 1,056 manually marked samples and their corresponding pictures was provided analysis. Those collected at scenarios (roads intersections, speed limits, day...

Connected-vehicle system is an important component of smart cities. The complete benefits connected-vehicle technologies need the real-time information all vehicles and other road users. However, existing deployments obtain status connected vehicles, but without knowing unconnected traffic since there are still many pedestrians on roads. Therefore, it urgent to find approach collect high-resolution When difficult for pedestrians, bicyclists broadcast their in near future, enhancing...

High-resolution vehicle data including location, speed, and direction is significant for new transportation systems, such as connected-vehicle applications, micro-level traffic performance evaluation, adaptive control. This research developed a processing procedure detection tracking of multi-lane multi-vehicle trajectories with roadside light ranging (LiDAR) sensor. Different from existing methods onboard sensing this was specifically to extract high-resolution LiDAR sensors. includes...

Cameras allow for highly accurate identification of targets. However, it is difficult to obtain spatial position and velocity information about a target by relying solely on images. The millimeter-wave radar (MMW radar) sensor itself easily acquires the but cannot identify shape target. MMW camera, as two sensors with complementary strengths, have been heavily researched in intelligent transportation. This article examines reviews domestic international research techniques definition,...

Trajectory tracking and crossing intention prediction of pedestrians at intersections are important to intersection safety. Recently, on‐board video sensors have been developed for detection pedestrians. However, both the range operating environment video‐based systems seem be constrained by advancement image‐processing technologies. Additionally, cannot alarm take evasive actions when risk, a feature which is critical saving lives. This paper summarises authors' practice on using roadside...

The previous studies showed that rainy and snowy weather can reduce the quality of LiDAR data. In weather, laser beams were often blocked by raindrops or snowflakes, which was called occlusion. vehicle detection with occlusion is a challenge. When traditional density-based spatial clustering applications noise (DBSCAN) used for clustering, data processing false rate conventional DBSCAN under high. This paper aims to present characteristics roadside in days improve accuracy during challenging...

Roadside light detection and ranging (LiDAR) is an emerging traffic data collection device has recently been deployed in different transportation areas. The current processing algorithms for roadside LiDAR are usually developed assuming normal weather conditions. Adverse conditions, such as windy snowy could be challenges processing. This paper examines the performance of state-of-the-art under adverse then composed improved background filtering object clustering method order to process...

Road defects are important factors affecting traffic safety. In order to improve the identification efficiency of road diseases and pertinence maintenance management, intelligent detection technologies have been developed. The problems high cost low artificial inspection solved efficiently, quality construction is improved availably. This not only guarantee highway but also people’s lives study focuses on disease summarizes commonly used equipment in technology diseases, which include...