Intersection Algorithm Research Articles

Trajectories and Platoon-forming Algorithm for Intersections with Heterogeneous Autonomous Traffic

The anticipated launch of fully autonomous vehicles presents an opportunity to develop and implement novel traffic management systems. Intersections are one of the bottlenecks for urban traffic, and thus offer tremendous potential for efficiency improvements. Platoon-forming algorithms, in which vehicles are grouped together with short inter-vehicular distances just before arriving at an intersection, seem particularly promising in this aspect. In this work, we present an intersection access control system based on platoon-forming for heterogeneous autonomous traffic. The heterogeneity of traffic arises from vehicles with different acceleration capabilities and safety constraints. We focus on obtaining computationally fast and interpretable closed-form expressions for safe and efficient vehicle trajectories enabling platoon formation, and show that these trajectories are solutions to certain optimisation problems. Additionally, we conduct a numerical study to obtain approximations for intersection capacity as a result of such platoon formation.

Capacity Optimization of Pumped–Hydro–Wind–Photovoltaic Hybrid System Based on Normal Boundary Intersection Method

Introducing pumped storage to retrofit existing cascade hydropower plants into hybrid pumped storage hydropower plants (HPSPs) could increase the regulating capacity of hydropower. From this perspective, a capacity configuration optimization method for a multi-energy complementary power generation system comprising hydro, wind, and photovoltaic power is developed. Firstly, to address the uncertainty of wind and photovoltaic power outputs, the K-means clustering algorithm is applied to deal with historical data on load and photovoltaic, wind, and water inflow within a specific region over the past year. This process helps reduce the number of scenarios, resulting in 12 representative scenarios and their corresponding probabilities. Secondly, with the aim of enhancing outbound transmission channel utilization and decreasing the peak–valley difference for the receiving-end power grid’s load curve, a multi-objective optimization model based on the normal boundary intersection (NBI) algorithm is developed for the capacity optimization of the multi-energy complementary power generation system. The result shows that retrofitting cascade hydropower plants with pumped storage units to construct HPSPs enhances their ability to accommodate wind and photovoltaic power. The optimal capacity of wind and photovoltaic power is increased, the utilization rate of the system’s transmission channel is improved, and the peak-to-valley difference for the residual load of the receiving-end power grid is reduced.

Serial and parallel organ-at-risk-specific noncoplanar arc optimization for small versus large target volumes in liver SBRT.

Noncoplanar arc optimization has been shown to reduce OAR doses in SRS/SRT and has the potential to reduce doses to OARs in SBRT. Extracranial targets have additional considerations, including large OARs and, in the case of the liver, volume constraints on the healthy liver. Considering pathlengths through OARs that encompass target volumes may lead to specific dose reductions as in the encompassing healthy liver tissue. These optimizations must also leverage delivery efficiency and trajectory sampling to ensure ease of clinical translation. The purpose of this research is to generate optimized static-couch arcs that separately consider serial and parallel OARs and arc delivery efficiency, with a trajectory sampling metric, towards the aim of reducing dose to OARs and the surrounding healthy liver tissue. Separate BEV cost maps were created for parallel, and serial OARs by means of a fast ray-triangle intersection algorithm. An additional BEV cost map was created for the liver which, by definition, encompasses the liver tumors. The individual costs of these maps were summed and combined with the sampling metric for 100 000 random combinations of arc trajectories. A search algorithm was applied to find an arc trajectory solution that satisfied BEV cost and sampling optimization, while also ensuring an efficient delivery was possible with a low number of arcs. This method of arc selection was evaluated for 16 liver SBRT patients characterized by small and large target volumes. Comparisons were made with a clinical arc template of coplanar arcs. Dosimetric plan quality was evaluated using published guidelines and metrics from RTOG1112. Four of five plan quality metrics for the liver were significantly reduced when planned with optimized noncoplanar arcs. Median (range) reductions of the volumes receiving 10, 18, and 21Gy were found of 140.4 (295.8) cc (p=0.001), 28.2 (230.6) cc (p=0.002) and 18.5 (155.5) cc (p=0.04). A significant increase in median (range) dose to the right kidney of 0.2±0.9Gy (p=0.03) was also found using optimized noncoplanar arcs, which was below the tolerance of 10Gy for all cases. The average number of arcs chosen was 4±1. Optimizing serial and parallel OARs separately during static couch noncoplanar arc selection significantly reduced the dose to the liver during SBRT using a moderate number of arcs.

A new fully projective O(lg N) line convex polygon intersection algorithm

A new fully projective O(lg N) line convex polygon intersection algorithm

TES and SLC40A1 as Potential Biomarkers for Predicting Survival in T-Cell Acute Lymphoblastic Leukemia.

Identifying patients with high-risk T-cell acute lymphoblastic leukemia (T-ALL) is crucial for personalized therapy; however, the lack of robust biomarkers hinders prognosis assessment. To address this issue, our study aimed to screen and validate genes whose expression may serve as predictive indicators of outcomes in T-ALL patients while also investigating the underlying molecular mechanisms. Differentially expressed genes (DEGs) between T-ALL patients and healthy controls were identified by integrating data from three independent public datasets. Functional annotation of these DEGs and protein-protein interactions were also conducted. Further, we enrolled a prospective cohort of T-ALL patients (n = 20) at our center, conducting RNA-seq analysis on their bone marrow samples. Survival-based univariate Cox analysis was employed to identify gene expressions related to survival, and an intersection algorithm was sequentially applied. Furthermore, we validated the identified genes using cases from the Therapeutically Applicable Research to Generate Effective Treatments database, plotting Kaplan-Meier curves for secondary validation. Through the integration of survival-related genes with DEGs identified in T-ALL, our analysis revealed six T-ALL-specific genes, the expression levels of which were linked to prognostic value. Notably, the independent prognostic value of SLC40A1 and TES expression levels was confirmed in both an external cohort and a prospective cohort at our center. In summary, our preliminary study indicates that the expression levels of TES and SLC40A1 genes show promise as potential indicators for predicting survival outcomes in T-ALL patients.

Simulating Thin Shells by Bicubic Hermite Elements

In this study, we present the bicubic Hermite element method (BHEM), a new computational framework devised for the elastodynamic simulation of thin-shell structures. The BHEM is constructed based on quadrilateral Hermite patches, which serve as a unified representation for shell geometry, simulation, collision avoidance, as well as rendering. Compared with the commonly utilized linear FEM, the BHEM offers higher-order solution spaces, enabling the capture of more intricate and smoother geometries while employing significantly fewer finite elements. In comparison to other high-order methods, the BHEM achieves conforming C1 continuity for Kirchhoff–Love (KL) shells with minimal complexity. Furthermore, by leveraging the subdivision and convex hull properties of Hermite patches, we develop an efficient algorithm for ray-patch intersections, facilitating collision handling in simulations and ray tracing in rendering. This eliminates the need for laborious remodeling of the pre-existing surface as the conventional approaches do. We substantiate our claims with comprehensive experiments, which demonstrate the high accuracy and versatility of the proposed method.

A platoon formation algorithm for intersections with blue phase control in mixed traffic

Increasing attention is being paid to intersection signal control with cooperative platoons. Assuming platoons being formed, such platoons cannot only improve the intersection capacity but also minimize the number of control units, especially when dedicated connected and automated vehicle (CAV) lanes are considered. However, the platoon formation process is often neglected, especially for lane-changing and overtaking maneuvers in mixed traffic. This may jeopardize the potential of signal control with platoons. This article proposes a platoon formation algorithm that computes the optimal lane, platoon sequence, and speed profiles of CAVs under the requirement of the central traffic controller. The algorithm is designed for mixed traffic conditions and hence the performance of human-driven vehicles is also considered. A mixed integer linear program model is formulated to minimize the deviation from the desired platoon configuration and the disturbance to overall traffic under any arbitrary initial condition. Numerical experiments are designed to test the effectiveness and the computational performance of the proposed algorithm. Results show that CAVs with signal control can form platoons with rational motion. Besides, the platoon penetration significantly affects platooning feasibility, while the platoon length does not. This suggests that CAVs can form long platoons at intersections to improve traffic throughput.

An efficient unstructured quadrilateral-dominated surface mesh generation method for arbitrary geometry with tiny features or crack defects in DiBFM

An efficient unstructured quadrilateral-dominated surface mesh generation algorithm is presented to generate high-quality surface elements for arbitrary geometry with tiny features or crack defects. For complex entities with proximity features, a novel type of meshing template has been proposed to solve the problem of entity boundary fitting of the outside-in grid-based method. The algorithm also works for regions with proximity features, as well as for arbitrary geometry with one or multiple cracks. The procedure incorporates aspects of well-known meshing techniques, but includes some original and efficient processes. The refinement field is constructed according to mesh size, boundary curvature, surface curvature and other geometry features. In order to effectively generate the core mesh, a fast intersection algorithm between topological elements and the solid boundary is established, which improves the efficiency of intersection calculation. The geometry-based techniques are employed for boundary matching of the core mesh. The method has been successfully employed in conjunction with the dual interpolation boundary face method (DiBFM). Several realistic geometries with cracks or proximity features are applied to demonstrate the accuracy and validity of the proposed approach.

Efficient List Intersection Algorithm for Short Documents by Document Reordering

List intersection plays a pivotal role in various domains such as search engines, database systems, and social networks. Efficient indexes and query strategies can significantly enhance the efficiency of list intersection. Existing inverted index-based algorithms fail to utilize the length information of documents and require excessive list intersections, resulting in lower efficiency. To address this issue, in this paper, we propose the LDRpV (Length-based Document Reordering plus Verification) algorithm. LDRpV filters out documents that are unlikely to satisfy the intersection results by reordering documents based on their length, thereby reducing the number of candidates. Additionally, to minimize the number of list intersection operations, an intersection and verification strategy is designed, where only the first m lists are intersected, and the resulting candidate set is directly verified. This approach effectively improves the efficiency of list intersection. Experimental results on four real datasets demonstrate that LDRpV can achieve a maximum efficiency improvement of 46.69% compared to the most competitive counterparts.

A novel algorithm for ship characteristic points extraction based on density clustering

With the widespread application of ship Automatic Identification System (AIS) in maritime operations, a large number of ship trajectories become available. This study aims to improve the safety of ships navigating through densely trafficked areas and address the challenge of sufficient data exploration while fully describing the traffic conditions in these waters. To achieve this objective, traffic flow information is extracted from AIS data collected in Zhoushan waters. A combination of multi-algorithms is employed to extract the traffic flow frame, specifically, the Douglas-Peucker compression algorithm and trajectory intersection algorithm are utilised to identify the characteristic points of ship trajectories. Subsequently, a density clustering algorithm is applied to extract the three types of characteristic points: compressed trajectory points, intersection points, and ship position points, facilitating data mining efforts. The resulting initial traffic flow characteristic points are then subject to weighted fusion, followed by image superposition processing to create an overlapping map of the ship trajectories. This process culminates in the generation of a traffic flow frame for the region. The framework integrates various track characteristic points, offering insights into the distribution of essential routes in the vicinity waters, thereby providing a comprehensive depiction of ship traffic flow patterns. The proposed framework can be applied to the route planning and serve as a reference to the maritime authorities when selecting recommended shipping lanes.

LPP-BPSI: A location privacy-preserving scheme using blockchain and Private Set Intersection in spatial crowdsourcing

Leakage of location information can lead to malicious attacks on workers in spatial crowdsourcing (SC) and loss of security. In response, a location privacy preserving scheme based on blockchain and Private Set Intersection were proposed, which reduced the computational overhead of workers by using a cloud service provider for outsourcing secure computation while ensuring their location privacy. First, three smart contracts based on blockchain were designed that could eliminate the control of traditional spatial crowdsourcing servers on the task allocation process. Second, differential privacy of the location method was proposed to construct the privacy location, and the cloud service provider used the privacy location to perform the location matching calculation. Third, an improved variant of the Private Set Intersection algorithm was constructed for the case of matching multiple workers for a single task in spatial crowdsourcing, which could efficiently perform location matching while protecting location privacy. To further reduce the computational overhead, Bloom filters were utilized to filter out a large number of free workers with zero location relevance before location matching. The experimental results showed that the scheme was robust and practical in the case of a large number of workers and concurrent task requests.

Fruit grading system by reconstructed 3D hyperspectral full-surface images

Conducting hyperspectral imaging of fruit' entire surfaces while simultaneously evaluating their physical properties, such as volume and mass, can provide a richer dataset for comprehensive fruit classification. For this purpose, a fruit grading system using 3D hyperspectral full-surface images is developed, which is based on multi-view imaging of mirrors in the hardware structure design and relies on the virtual volume intersection (VI) algorithm and texture technology in software design. During the design process, a mathematical model for the mirror layout and system geometry parameters is established to determine the system's layout for scanning the entire surface of the sample. In practical applications, a prototype with 28 channels ranging from 400 to 1000 nm is developed for pear samples based on a sub-component control system, a spherical-cap cavity with flashing multi-color LEDs, and multiple side mirrors. The results obtained from this prototype reveal that the predicted volume (R2=96.18%) and mass (R2=98.18%) exhibit a high correlation with measured results and the hyperspectral data between bruised and normal pears is a significant difference. A dataset of pears of three qualities (large, small, and bruised) is prepared for comprehensive classification and resulting in an effective grading (95.33%), which shows that the proposed system is a potential solution for comprehensive fruit quality classification.

Data fusion method for temperature monitoring of bio-oxidation with wireless sensor networks

In the process of bio-oxidation gold extraction located in the cold and high-altitude areas, temperature monitoring in the oxidation tank is noisy and accompanied by measurement losses. A new fusion strategy is proposed for improving the temperature monitoring performance of the bio-oxidation tank. In the specific, the measurement data from the underlying sensors is preprocessed by an improved unscented Kalman filter to reduce the impact of missing data and noises on the fusion method. At the local fusion center, the data is fused by a new covariance intersection algorithm to ensure the consistency and high accuracy of the fusion results. In the global fusion center, all of the cluster head fusion results are fused by a hybrid neural network to improve the accuracy and robustness of the designed fusion algorithm. The simulation shows that the proposed fusion strategy effectively improves the temperature monitoring performance of the oxidation tank.

Distributed asynchronous measurement system fusion estimation based on inverse covariance intersection algorithm

For state estimation of multi-source asynchronous measurement systems with measurement missing phenomena, this paper proposes a distributed sequential inverse covariance intersection (DSICI) fusion algorithm based on conditional Kalman filtering method. It is mainly divided into synchronized state space module, local filtering module and fusion estimation module. The missing measurements occurring in the system are modelled and described by a set of random variables obeying a Bernoulli distribution. The synchronized state space module uses a state iteration method to synchronize the asynchronous measurement system at the moment of measurement update and it ensures the integrity of the measurement information. The local filtering module uses a conditional Kalman filtering algorithm for filter estimation. The reliability of the local filtering results is guaranteed because the local estimator designs a method to interact information with the domain sensors. The fusion estimation module designs a DSICI fusion algorithm with higher accuracy and satisfying consistency, which fuses the filtering results provided by each sensor when the relevant information between multiple sensors is unknown. Simulation examples demonstrate the excellent performance of the proposed algorithm, with a 33% improvement in accuracy over existing algorithms and an iteration time of less than 3 ms.

A hybrid finite volume - spectral element method for aeroacoustic problems

We propose a hybrid Finite Volume (FV) - Spectral Element Method (SEM) for modeling aeroacoustic phenomena based on the Lighthill's acoustic analogy. First the fluid solution is computed employing a FV method. Then, the sound source term is projected onto the acoustic grid and the inhomogeneous Lighthill's wave equation is solved employing the SEM. The novel projection method computes offline the intersections between the acoustic and the fluid grids in order to preserve the accuracy. The proposed intersection algorithm is shown to be robust, scalable and able to efficiently compute the geometric intersection of arbitrary polyhedral elements. We then analyze the properties of the projection error, showing that if the fluid grid is fine enough we are able to exploit the accuracy of the acoustic solver and we numerically assess the obtained theoretical estimates. Finally, we address two relevant aeroacoustic benchmarks, namely the corotating vortex pair and the noise induced by a laminar flow around a squared cylinder, to demonstrate in practice the effectiveness of the projection method when dealing with high order solvers. The flow computations are performed with OpenFOAM [50], an open-source finite volume library, while the inhomogeneous Lighthill's wave equation is solved with SPEED [34], an open-source spectral element library.

Open-ICL: Open-Set Modulation Classification via Incremental Contrastive Learning.

Open-set modulation classification (OMC) of signals is a challenging task for handling "unknown" modulation types that are not included in the training dataset. This article proposes an incremental contrastive learning method for OMC, called Open-ICL, to accurately identify unknown modulation types of signals. First, a dual-path 1-D network (DONet) with a classification path (CLP) and a contrast path (COP) is designed to learn discriminative signal features cooperatively. In the COP, the deep features of the input signal are compared with the semantic feature centers (SFCs) of known classes calculated from the network, to infer its signal novelty. An unknown signal bank (USB) is defined to store unknown signals, and a novel moving intersection algorithm (MIA) is proposed to dynamically select reliable unknown signals for the USB. The "unknown" instances, together with SFCs, are continuously optimized and updated, facilitating the process of incremental learning. Furthermore, a dynamic adaptive threshold (DAT) strategy is proposed to enable Open-ICL to adaptively learn changing signal distributions. Extensive experiments are performed on two benchmark datasets, and the results demonstrate the effectiveness of Open-ICL for OMC.

Topology Guaranteed B-Spline Surface/Surface Intersection

The surface/surface intersection technique serves as one of the most fundamental functions in modern Computer Aided Design (CAD) systems. Despite the long research history and successful applications of surface intersection algorithms in various CAD industrial software, challenges still exist in balancing computational efficiency, accuracy, as well as topology correctness. Specifically, most practical intersection algorithms fail to guarantee the correct topology of the intersection curve(s) when two surfaces are in near-critical positions, which brings instability to CAD systems. Even in one of the most successfully used commercial geometry engines ACIS, such complicated intersection topology can still be a tough nut to crack. In this paper, we present a practical topology guaranteed algorithm for computing the intersection loci of two B-spline surfaces. Our algorithm well treats all types of common and complicated intersection topology with practical efficiency, including those intersections with multiple branches or cross singularities, contacts in several isolated singular points or highorder contacts along a curve, as well as intersections along boundary curves. We present representative examples of these hard topology situations that challenge not only the open-source geometry engine OCCT but also the commercial engine ACIS. We compare our algorithm in both efficiency and topology correctness on plenty of common and complicated models with the open-source intersection package in SISL, OCCT, and the commercial engine ACIS.

Research on the path extraction method of shoe upper grinding based on 3D vision

Shoe upper grinding is a crucial step in the shoe manufacturing process, impacting both the bonding quality between the sole and the upper and the overall appearance of the shoe. Presently, many shoe companies rely on manual or semi-automated grinding methods for shoe uppers, resulting in low production efficiency and subpar grinding quality. This study proposes a 3D vision-based shoe upper grinding path extraction method for guiding a robotic arm to polish the shoe upper and address this issue. Initially, the RGB-D camera was used to obtain the point cloud data of the shoe surface, which was then preprocessed using point cloud filtering, smoothing and registration methods. Second, by combining RGB images with 3D point clouds, we propose a point-cloud region of interest (ROI) extraction method based on RGB information to obtain the feature point cloud of the shoe upper grinding line. Finally, we slice the feature point cloud of the shoe upper grinding line, extract the grinding points using an intersection algorithm, and fit them with a non-uniform rational B-spline curve (NURBS) to obtain the shoe’s upper grinding path. The research demonstrates that this method can effectively extract the shoe upper grinding trajectory curve, significantly reduce the time required to obtain the shoe upper grinding trajectory, and achieve good accuracy, with promising application prospects.

Robust numerical integration of embedded solids described in boundary representation

Embedded and immersed methods have become essential tools in computational mechanics, as they allow discretizing arbitrarily complex geometries without the need for boundary-fitted meshes. One of their main challenges is the accurate numerical integration of cut elements. Among the various integration schemes developed for this purpose, moment fitting has proven to be a powerful technique that provides highly efficient and accurate integration rules.This publication presents a framework for the robust and efficient numerical integration of embedded solids described by oriented boundary meshes using moment fitting. The developments include an intersection algorithm that aims to drastically accelerate the computation of the necessary moments while achieving high accuracy. A closed surface parameterization of each cut domain is computed to facilitate the direct application of the divergence theorem. The algorithm is subject to a single quality criterion that guarantees the accurate evaluation of boundary integrals. At the same time, it allows to disregard classical mesh criteria, such as high aspect ratios, strongly varying angles, etc., resulting in extremely fast runtimes. In addition, an existing robust flood fill-based element classification scheme is further developed to initiate filling from arbitrary seed elements and to enable parallel execution, increasing its flexibility and efficiency.The successful application of all proposed algorithms to 4948 valid and flawed STLs from the Thingi10K database (Zhou and Jacobson, 2016) demonstrates their extraordinary robustness. In all cases, the wall-clock time scales at most linearly with the number of elements in the background mesh. We show that higher-order quadrature rules on the boundary elements enable efficient computation of the moments via the divergence theorem with near-machine precision. Finally, the presented methodologies are used to perform direct FE analyses on clean and flawed B-Rep models. All proposed algorithms are publicly available in the open-source C++ framework QuESo – Quadrature for Embedded Solids (https://github.com/manuelmessmer/QuESo), where the moment fitting equations are assembled and solved.

A stable conservative Lagrange-Galerkin scheme to pure convection equations with mesh intersection

We present an algorithm to solve pure-convection problems with a conservative Lagrange-Galerkin formulation in the framework of the finite element method. The weak formulation involves integrals of the product of basis functions associated to the finite element spaces of two different meshes: the original mesh and another one obtained by moving the original mesh along the characteristic curves of the convection operator. In order to compute these integrals up to machine precision, we perform a mesh intersection algorithm which is easily implemented by means of standard finite element operations. Specifically, we consider the intersection of meshes composed by triangles (in 2-dimensions) and tetrahedra (in 3-dimensions) with straight sides. We illustrate the good features of the method in terms of stability, accuracy and mass conservations in different pure-convection tests with velocity fields which are not necessarily divergence-free.