Crashes among young and inexperienced drives are a major safety problem in the United States, especially an area with large rural road networks, such as West Texas. Rural roads present many unique concerns that not fully explored. This study presents complete machine leaning pipeline to find patterns of crashes involved teen drivers no older than 20 on Texas, identify factors affect injury levels, build four learning predictive models crash severity. The analysis indicates causes driver...

Lane information is an essential part of high-resolution micro-traffic data (HRMTD). Most the lane detection algorithms for Light Detection and Ranging (LiDAR) are applied to high-density onboard LiDAR airborne LiDAR, which cannot be used directly process low-density roadside data. In this article, algorithm proposed, includes three steps: ground recognition, marking point extraction, pavement points clustering. Firstly, improved recognition proposed get normal (NGPs). Then, extracted from...

High-density land uses cause high-intensity traffic demand. Metro as an urban mass transit mode is considered a sustainable strategy to balance the high-density development and However, capacity of metro cannot always meet demand during rush hours. It calls for agents reinforce operation management standard improve service level. Passenger flow prediction foremost pivotal technology in improving level metro. important technological means ensuring steady transportation. This paper...

Further detection will increase traffic safety by perceiving unexpected incidents earlier, allowing more time to make decisions and implement these decisions. Therefore, this article attempts extend the range using a low-channel roadside light sensor (LiDAR) due its low price widespread employment in future. The proposed method contains two major parts: static background construction objects detection. For construction, successive point cloud frames data were used cover most LiDAR scanning...

Pavement marking retroreflectivity and diffuse illumination can degrade due to wear, cracks, aging. To enable efficient, safe, cost-effective inspections of pavement markings, ensure timely maintenance, regulate driver behavior, enhance traffic safety, a method using an onboard low-channel LiDAR for detecting classifying worn was proposed. The process begins by applying coordinate transform, ground mapping, sigmoid function filtering the collected point cloud data differentiate markings from...

Short-term traffic flow prediction is one of the most important issues in field intelligent transport system (ITS). Because uncertainty and nonlinearity, short-term a challenging task. In order to improve accuracy short-time prediction, hybrid model (SSA-KELM) proposed based on singular spectrum analysis (SSA) kernel extreme learning machine (KELM). SSA used filter out noise time series. Then, filtered data train KELM model, optimal input form determined by phase space reconstruction,...

Mixed traffic composed of human-driven vehicles (HDVs) and CAVs will exist for an extended period before connected autonomous (CAVs) are fully employed on the road. There is a consensus that dense fog can cause serious accidents reduce efficiency. In order to enhance safety, mobility, efficiency highway networks in adverse weather conditions, it necessary explore characteristics mixed traffic. Therefore, we develop novel cellular automata model considering limited visual distance exploring...

The advancement of technology and economic development has raised the standard living at same time brought a greater burden to environment. Environmental governance become common concern around world, although China’s environmental achieved some success, it is still long way from ultimate goal. This paper empirically analyzes impact publicity education on performance, using public participation as mediator. results show that: direct effect performance not significant; have significant...

A lane-level intersection map is a cornerstone in high-definition (HD) traffic network maps for autonomous driving and high-precision intelligent transportation systems applications such as management control, accident evaluation prevention. Mapping an HD time-consuming, labor-intensive, expensive with conventional methods. In this paper, we used low-channel roadside light detection range sensor (LiDAR) to automatically dynamically generate intersection, including the signal phases,...

Road defect detection is a crucial aspect of road maintenance projects, but traditional manual methods are time-consuming, labor-intensive, and lack accuracy. Leveraging deep learning frameworks for object offers promising solution to these challenges. However, the complexity backgrounds, low resolution, similarity cracks make detecting with high accuracy challenging. To address issues, novel crack algorithm, termed Defect Detection YOLOv5 (RDD-YOLOv5), was proposed. Firstly, model proposed...

A light detection and ranging (LiDAR) sensor can obtain richer more detailed traffic flow information than traditional detectors, which could be valuable data input for various novel intelligent transportation applications. However, the point cloud generated by LiDAR scanning not only includes road user points but also other surrounding object points. It is necessary to remove worthless from using a suitable background filtering algorithm accelerate micro-level extraction. This paper...

Clear and distinctive pavement markings play a critical role in providing traffic information avoiding crashes at night adverse weather conditions. Periodically inspecting marking is essential but requires vast human material resources currently. This paper attempts to use the low-channel LiDAR sensor detect evaluate stain, wear, cracks of based on research Pike Che that retroreflectivity highly correlated with laser intensity LiDAR. Thus, deployment location mobile its built-in...

Short-time traffic flow prediction is necessary for advanced management system (ATMS) and traveler information (ATIS). In order to improve the effect of short-term prediction, this paper presents a multistep method based on similarity search time series. Firstly, landmark model used represent series data. Then input data are determined through searching similar Finally, echo state networks prediction. The performance proposed measured with expressway collected from loop detectors in...

The ability to track multiple objects is crucial for roadside units provide high-precision, trajectory-based traffic data, especially connected vehicles that require complementary and long-range information improve road safety. Occlusion continuous tracking are major challenges have hindered the achievement of obtaining accurate, uninterrupted, consistent multi-object using LiDAR technology. This paper presents a lane-level full-cycle multi-vehicle (MVT) method utilizes low-channel LiDAR....

Object detection is the fundamental task of vision-based sensors in environmental perception and sensing. To leverage full potential roadside 4D MMW radars, an innovative traffic method proposed based on their distinctive data characteristics. First, velocity-based filtering region interest (ROI) extraction were employed to filter associate point by merging cloud frames enhance relationship. Then, Louvain algorithm was used divide graph into modularity converting structure amplifying...

Detection of pavement diseases is crucial for road maintenance. Traditional methods are costly, time-consuming, and less accurate. This paper introduces an enhanced disease recognition algorithm, MS-YOLOv8, which modifies the YOLOv8 model by incorporating three novel mechanisms to improve detection accuracy adaptability varied conditions. The Deformable Large Kernel Attention (DLKA) mechanism adjusts convolution kernels dynamically, adapting multi-scale targets. Separable (LSKA) enhances...

Short-term traffic flow prediction is an important part of intelligent transportation systems research and applications. For further improving the accuracy short-time prediction, a novel hybrid model (multivariate phase space reconstruction–combined kernel function-least squares support vector machine) based on multivariate reconstruction combined machine proposed. The C-C method used to determine optimal time delay embedding dimension variables’ (flow, speed, occupancy) series for...

Straw burning can cause serious environmental pollution, whereas returning straw to the fields, as a green production method, improve rural environment and strengthen sustainable development of agriculture. According statistics, China produced 797 million tons in 2020, but current return technology still needs be improved; ability farmers choose correct amount returned field their awareness protection need strengthened. is openly burned some areas, causing pollution waste resources, which...

Lane marking is the criterion line for roadside unit to extract lane-level and high-resolution microlevel traffic data (HRMTD), which essential information in vehicle-to-infrastructure (V2I) cooperative. For lane detection complex environments, inconsistent width indistinctive laser intensity are two significant challenges LiDAR. To address these issues, we proposed an accuracy robustness method. With low-channel LiDAR, divided LiDAR scanned area into grids vehicle points filter out noise...