Traffic Markings Research Articles

Research on Traffic Marking Segmentation Detection Algorithm Based on Feature Fusion

Identifying road markings is a very important part of the vehicle environment sensing system and plays a crucial role in a vehicle’s correct understanding of a current traffic situation. However, road traffic markings are interfered with by a variety of factors, such as being obscured and the viewpoint of the vehicle sensors, resulting in large errors in the existing detection methods. In order to make the target detection task applicable to irregular objects or to detection tasks with higher accuracy requirements while reducing the waste of computational resources, this paper improves the accuracy of traffic marking segmentation detection by designing a multi-type traffic marking segmentation detection model based on image segmentation algorithms and designing a segmentation guidance matrix module based on a rank guidance matrix computation method. By constructing a comprehensive traffic marking detection model, a unified road traffic marking detection is achieved. Finally, the new traffic marking datasets ApolloScape-Precise and ApolloScape-Large are constructed based on the existing ApolloScape dataset, and experimental validation is carried out on these two datasets. The results show that the index MIoU (Mean Intersection over Union) of traffic marking segmentation detection reaches 61.44% and 70.15%, thus achieving a more perfect road traffic marking detection and right-of-way information perception and proving the effectiveness of the integrated traffic marking detection method designed in this paper.

Three-Dimensional Reconstruction of Zebra Crossings in Vehicle-Mounted LiDAR Point Clouds

In the production of high-definition maps, it is necessary to achieve the three-dimensional instantiation of road furniture that is difficult to depict on traditional maps. The development of mobile laser measurement technology provides a new means for acquiring road furniture data. To address the issue of traffic marking extraction accuracy in practical production, which is affected by degradation, occlusion, and non-standard variations, this paper proposes a 3D reconstruction method based on energy functions and template matching, using zebra crossings in vehicle-mounted LiDAR point clouds as an example. First, regions of interest (RoIs) containing zebra crossings are obtained through manual selection. Candidate point sets are then obtained at fixed distances, and their neighborhood intensity features are calculated to determine the number of zebra stripes using non-maximum suppression. Next, the slice intensity feature of each zebra stripe is calculated, followed by outlier filtering to determine the optimized length. Finally, a matching template is selected, and an energy function composed of the average intensity of the point cloud within the template, the intensity information entropy, and the intensity gradient at the template boundary is constructed. The 3D reconstruction result is obtained by solving the energy function, performing mode statistics, and normalization. This method enables the complete 3D reconstruction of zebra stripes within the RoI, maintaining an average planar corner accuracy within 0.05 m and an elevation accuracy within 0.02 m. The matching and reconstruction time does not exceed 1 s, and it has been applied in practical production.

Lane Attribute Classification Based on Fine-Grained Description.

As an indispensable part of the vehicle environment perception task, road traffic marking detection plays a vital role in correctly understanding the current traffic situation. However, the existing traffic marking detection algorithms still have some limitations. Taking lane detection as an example, the current detection methods mainly focus on the location information detection of lane lines, and they only judge the overall attribute of each detected lane line instance, thus lacking more fine-grained dynamic detection of lane line attributes. In order to meet the needs of intelligent vehicles for the dynamic attribute detection of lane lines and more perfect road environment information in urban road environment, this paper constructs a fine-grained attribute detection method for lane lines, which uses pixel-level attribute sequence points to describe the complete attribute distribution of lane lines and then matches the detection results of the lane lines. Realizing the attribute judgment of different segment positions of lane instances is called the fine-grained attribute detection of lane lines (Lane-FGA). In addition, in view of the lack of annotation information in the current open-source lane data set, this paper constructs a lane data set with both lane instance information and fine-grained attribute information by combining manual annotation and intelligent annotation. At the same time, a cyclic iterative attribute inference algorithm is designed to solve the difficult problem of lane attribute labeling in areas without visual cues such as occlusion and damage. In the end, the average accuracy of the proposed algorithm reaches 97% on various types of lane attribute detection.

Study on Factors Affecting Rapid Detection of Retroreflection in Road Markings Based on One-Way ANOVA Analysis

In the dynamic and rapid detection of retroreflection coefficient in road traffic markings, different factors may affect the detection results. This study investigates the significance of different levels of environmental light intensity and vehicle speed on the detection results of retroreflection coefficient in road markings using one-way ANOVA analysis. The results show that within a 95% confidence interval, there is no statistically significant difference in the detection results of retroreflection coefficient under different levels of environmental light intensity and vehicle speed. The variance effect size calculation indicates that for the detection of retroreflection coefficient in road markings, vehicle speed control is more important than light intensity. To obtain more reliable detection results, it is recommended to maintain a stable and uniform speed of no more than 80 km/h during the detection process.

Research on the Anti-Fouling Properties of Double-Coated Road Markings

The article analyses the influencing factors of the anti-fouling properties of road traffic markings and researches a double-coated, anti-fouling road marking with good heat stability and high coating density. The anti-fouling performance of the road marking during its use period was experimentally analysed using SPSS software. The results indicate that the anti-fouling performance of the double-coated road marking is significantly better than that of thermoplastic markings and two-component markings, and it has a promising prospect for widespread application.

Traffic Marking Extraction Algorithm Based on Image and Point Cloud Data

Traffic Marking Extraction Algorithm Based on Image and Point Cloud Data

Modeling the lane-changing behavior of non-motorized vehicles on road segments via social force model

Using traffic marking to separate non-motorized lane from the adjacent motorized lane is a common traffic design method for urban road segments. With the increase in non-motorized vehicle flow, illegal lane-changing occurs frequently, which leads to more serious conflict among road users. The study of the behavior characteristics of non-motorized illegal lane-changing on road segments, and establishing a microscopic simulation model can be used as a theoretical support and analysis tool for the design of non-motorized lane. This paper takes non-motorized vehicles as the research object to study lane-changing behavior characteristics. Then, the K-means clustering algorithm is used to classify riding styles into three types: risker, opportunist, and prudent. The micro-behavioral characteristics of riders with different riding styles are analyzed. Next, a three-layer model framework composed of perceptual, decision-making, and social force model is established. The logit model is used in the decision-making model to predict the probability of non-motorized vehicles crossing the line. Different riding styles are considered in the social force, and a virtual boundary force is introduced to describe lane-changing behavior. Subsequently, parameters are calibrated and the model is validated in various ways. Finally, the proposed model is used to conduct simulation experiments to explore the renovation scheme of the non-motorized lane. The results show that the proposed model can reproduce the traffic operation in the real scenario.

An efficient hexadecimal network flow watermark method for tracking attack traffic

Network flow watermark technology is a traffic marking technique that embeds watermark information into the characteristics of network flows to mark and trace attack flows generated by network attackers. However, with the development of network attack techniques, the time and number of packets required for network attacks have decreased. Existing network flow watermark technologies fail to balance watermark robustness and efficiency, resulting in poor practicality. To address this issue, this paper proposes an efficient hexadecimal network flow watermark method. The method introduces an efficient interval watermark algorithm and utilizes an interval synchronization algorithm to self-learn watermark parameters, thereby improving the encoding efficiency of the watermark. The design of watermark start and end markers ensures the practicality of network watermarks, enabling traceability and source attribution of attack flows in real network environments. The proposed method is experimentally tested using real network traffic, and the results demonstrate that even in the presence of a network jitter, the watermark detection success rate of this scheme remains above 95%. Compared to other network flow watermark schemes, the hexadecimal network flow watermark proposed in this paper achieves a 50% improvement in encoding and decoding efficiency while ensuring robustness. It also exhibits excellent resistance to network jitter, packet loss, and false packet insertion.

The influence of vehicle rolling on the retroreflective coefficient of hot melt markings

In the service life of traffic markings, the visibility of the markings can be significantly impacted due to continuous rolling by vehicles. This study aims to investigate the change of retroreflective coefficient of traffic markings at different positions on the road after being rolled by vehicles. A two-month follow-up study was conducted on a specific section of the road, focusing on the sideline and middle line of the lane. The retroreflective coefficient instrument was utilized to collect data on the retroreflective coefficient of the markings. Results revealed that the middle line, due to more frequent vehicle rolling, exhibited a larger range in its retroreflective coefficient as compared to the sideline of the lane. The change in reflection ability of hot melt markings, when rolled by the vehicle, depends on the mosaic condition of the glass beads within the coating. It was observed that the rolling of the vehicle had a direct impact on the retroreflective coefficient of the hot melt marking line. Furthermore, it was found that with increased rolling of the marking line, the greater the impact on its reflection capacity and the thickness also demonstrated a significant decrease.

Driver-Specific Risk Recognition in Interactive Driving Scenarios Using Graph Representation

This paper presents a driver-specific risk recognition framework for autonomous vehicles that can extract inter-vehicle interactions. This extraction is carried out for urban driving scenarios in a driver-cognitive manner to improve the recognition accuracy of risky scenes. First, clustering analysis is applied to the operation data of drivers for learning the subjective assessment of risky scenes of different drivers and generating the corresponding risk label for each scene. Second, the graph representation model (GRM) is adopted to unify and construct the features of dynamic vehicles, inter-vehicle interactions, and static traffic markings in real driving scenes into graphs. The driver-specific risk label provides ground truth to capture the risk evaluation criteria of different drivers. In addition, the graph model represents multiple features of the driving scenes. Therefore, the proposed framework can learn the risk-evaluating pattern of driving scenes of different drivers and establish driver-specific risk identifiers. Last, the performance of the proposed framework is evaluated via experiments conducted using real-world urban driving datasets collected by multiple drivers. The results show that the risks and their levels in real driving environments can be accurately recognized by the proposed framework.

LiDAR Perception and Evaluation Method for Road Traffic Marking Retroreflection

To solve the problem of low efficiency in retroreflection maintenance of road traffic markings, in this study a vehicle-mounted LiDAR-based perception and evaluation method of retroreflection of markings is proposed. First, this method establishes a calibration prediction model for LiDAR based on a regression decision tree. Then, a marking maintenance evaluation model is constructed in combination with the decision threshold proposed by China’s national standard, and the accuracy of the maintenance evaluation model is analyzed using F1-score, recall, and precision. In this study, four marking lines were used as the calibration data source, and a dataset of an independent 1,300 m road section was used to verify the established models. The results show that the coefficient of the retroreflected luminance ( RL) and the reflection intensity of the markings are positively correlated. During the construction of the calibration prediction model, the multiple linear regression functions, the second-order polynomial functions, and the decision tree are compared, and the result indicates that decision tree has the best fit to the data with the coefficient of determination for the established calibration prediction model better than 0.95. The agreement between the maintenance decision obtained from the maintenance evaluation model and the traditional method is more than 85%. The time cost is reduced by at least 90%. The proposed calibration prediction model can accurately predict the RL, and can quickly collect the RL values of the in-service road traffic markings. The proposed maintenance evaluation model is highly efficient and can replace the traditional evaluation method for markings.

Road Traffic Marking Extraction Algorithm Based on Fusion of Single Frame Image and Sparse Point Cloud

Road Traffic Marking Extraction Algorithm Based on Fusion of Single Frame Image and Sparse Point Cloud

Influence of construction technology on the retroreflective performance of two-component traffic marking

The construction technology of traffic marking has a significant influence on its retroreflective performance. To study the effect of different construction processes on the service performance of traffic markings, two-component spraying paint and two different glass beads were chosen to produce traffic markings that were prepared by single-layer or double-layer spraying, as well as once and twice surface spraying of glass beads. The effects of glass bead coating, spraying times of glass beads and paints on the surface morphology and retroreflective performance of traffic markings were investigated, as well as the variation of the retroreflective coefficient (RC) at the early and middle stages. The results indicated that double-layer spraying was more effective than single spraying. The coated glass beads would decrease the initial RC of the markings, but improved their long-term service performance. The TP-21C has the finest overall retroreflective performance and the lower construction complexity.

Evaluation Test of NO Degradation by Nano-TiO2 Coatings on Road Pavements under Natural Light

Reducing or degrading nitrogen oxides (NOx) emitted by automobile exhausts has diversified ways. This paper presents a solution to degrade NO by Nano-sized titanium dioxide (Nano-TiO2) mixed with coating materials for traffic marking on road pavements. The effect on degradation was evaluated by adopting a simple laboratory test with statistical analysis. During the test, five different contents of Nano-TiO2, 2%, 3%, 4%, 5%, and 6%, mix with a coating material for pavement marking, followed by an interpretation of the micro mechanism of degradation effect. The results show that the pavement marking coatings mixed with Nano-TiO2 has a good performance on NO degradation. The effect of degradation is increased with increasing the content of Nano-TiO2 particles, however. At the same time, a peak value with about 70% of the maximum removing rate existed when applying 4% Nano-TiO2 due to the agglomeration phenomenon for nanoparticles close to each other for adding more Nano-TiO2. The methods to reduce agglomeration are also suggested, and a routine field test for all potential traffic coating materials is recommended in this study.

The effect of acrylic silane crosslinker on room‐temperature cured acrylate binder for road markings

AbstractAn acrylic binder with excellent physical properties is prepared using copolymer of methyl methacrylate (MMA) and butyl acrylate monomer (BAM), 2‐hydroxyethyl methacrylate (2‐HEMA), 3‐(trimethoxysilyl)propyl methacrylate (TMSPMA), and additives. The obtained acrylic resins are subjected to a redox initiator system (ROIS) for room temperature curing. The effects of the TMSPMA concentration and [acryl‐copolymer]/[2‐HEMA] ratio on backbone content are studied in terms of traffic marking paint. The mechanical and morphological properties are thoroughly evaluated using universal testing machine (UTM), UV spectrum, and SEM. With increasing TMSPMA content, the adhesive strength and transmittance of the cured resins increase up to a limiting value of TMSPMA content because of the optimizing crosslink network in backbone structure. The introduction of TMSPMA may be effectively attributed to strong adhesive and high transparency of an acrylic resin series. Consequently, acrylic resins with optimal TMSPMA content can be mostly utilized as a high‐performance binder in the traffic marking paint field.

Combination Layout of Traffic Signs and Markings of Expressway Tunnel Entrance Sections: A Driving Simulator Study

To determine a better combination of signs and markings on expressway tunnel entrance sections, three types of typical signs and markings were compared and tested according to five indicators: speed, lane lateral offset, lane change behavior, fixation behavior, and operating load, using a driving simulator. The results identified that the obvious no overtaking and speed limit signs, combined with a layer of thin red pavement, had the most influence on drivers’ speed, and they led to the highest fixation frequency of static facilities, the longest average distance from the completion point of the lane change to the entrance, and the longest average lane change distance, which could help drivers to pass through tunnel entrance sections more smoothly. The location of the static facilities should be between 3 s before the tunnel entrance and 3 s after entering the tunnel, as this is the area where a driver’s relative viewpoint changes. The improper combination of warning signs and deceleration measures will affect a driver’s judgment, causing negative effects, such as premature lane changes and an increased operating load. The research results can provide a design basis and reference for the combination setting of safety signs and markings on tunnel entrance sections.

Simulation analysis of reflective performance of marking glass beads

Road traffic markings are made of glass beads embedded in paint. To analyze the effects of glass-bead radius, embedment depth, correlated color temperature of light sources, and incident angle on the reflective performance of glass beads, a numerical model is established using the geometric optics method, effective light conditions are analyzed, calculation methods for optical power devised, and non-standard planes of incident light calculated. Calculations were also carried out. Results show that the retroreflective properties of glass beads are positively correlated with the correlated color temperature of the light source and radius of the beads. The glass-bead radii, embedment depths, and incident angles have little effect on their reflective performance. Moreover, the correlated color temperature of the light source is an important factor affecting the accuracy of measuring glass-bead reflective performance. When using retro reflectometers, standard retro reflectance-measuring devices for retro reflectance measurement, and other equipment to evaluate the reflective performance of road traffic markings, the correlated color temperature of the light source of the equipment should be as close as possible to 2856 K.

Cognitive bias analysis of young novice drivers' observation abilities-A questionnaire-based study.

Observation ability, which is the basis of following decision-making and vehicle manipulation behaviour, is of great importance while driving. However, the subject self-cognition and objective assessment of driving ability are usually different, especially for the young novice drivers. In this paper, drivers’ observation abilities for both static traffic signs and markings and dynamic surrounding vehicles were investigated based on questionnaire data. Effects of gender and driving characteristics (driving year, driving frequency, driving time) on drivers’ observation abilities were verified by ANOVA analysis and structural equation model (SEM) from two aspects: drivers’ self-assessment scores (self-assessment) and mutual assessment scores (evaluated by others). Significant difference could be found between all the factors and drivers’ self-assessment scores, while only driving year had a significant effect on drivers’ mutual assessment scores. Besides, cognitive bias was found between all the driving year groups. It seemed that drivers with driving experience less than one year were always overconfident with their driving abilities. And drivers with driving experience more than three years usually gave the most conservative assessment scores for themselves and others. With more exposures to various traffic conditions, experienced drivers are more aware of their limitations on observing surrounding information, while young novice drivers still not realized their limitations on observing traffic signs and other vehicles in a right way.

Analysis Of Inclusion Of Foreign Diplomatic Representatives In The Pakistan Exit Control List To Protection Of Diplomatic Immune Rights

A diplomatic representative is a person who carries the task of officially connecting the tongues of two countries, namely between the sending country and the receiving country. As a representation of a country, diplomatic representatives are given the privilege of immunity to be able to perform the duties and missions charged to it. Such privilege arrangements are legally regulated under the Vienna Convention of 1961 and supported by other sources of international law including international customary law. However, there are some obstacles in its application such as in the case of Colonel Hall in Islamabad, Pakistan. The accident caused by Colonel Hall's negligence in violation of traffic markings has left the victim dead and seriously injured. However, due to legal immunity, the authorities have not yet completed an investigation into the case. The Pakistani government then listed Colonel Hall's name on the Blacklist and recommended putting his name on the Exit Control List. How the incident is reviewed from the perspective of international law will be discussed by the author in this paper.

Rapid Crack Detection Method of High-grade Cement Concrete Pavement

A new fast automatic repaired crack detection method of high-grade cement concrete pavement was realized through inhibition of groove, image enhancement, crack extraction and crack stitching in the low-resolution images using wavelet decomposition on the basis of in-depth feature analysis of repaired cracks. In addition, the modified crack identification algorithms were discussed in detail with joints, strip stains and traffic markings. It has significantly improved the processing speed by reducing image resolution and the applying one-dimensional convolution template instead of two-dimension. Large sample tests showed that recognition rate close to 94%.