17 results about "Major road" patented technology

The present disclosure relates to a technical field of coal mining, in particular to a surrounding rock stability control method adapted for a coal mining area main roadway. The method comprises the following steps: reinforcing support on a roof and two sides of the mining area main roadway on a basis of an original support form; digging a safety roadway along a stop line of a present working face required by coal mine design, and supporting the safety roadway, wherein a protective coal pillar is formed between the safety roadway and the mining area main roadway; performing slitting blasting on the roof in the safety roadway, wherein blast holes are arranged on a roadway corner line on one side of the present working face to form a pre-splitting slit; and performing stoping at a next working face after completing coal mining at the present working face when stoping at the present working face advances to the safety roadway. By cutting the roof and relieving pressure at the stop mining line of the working face, an influence of mining disturbance on stability of the mining area main roadway in the stoping process of the working face is reduced, and by reinforcing support, a yielding deformation capacity of the mining area main roadway is improved, and the stability of the surrounding rock of the mining area main roadway is further improved.

Provided is a pavement distress inspection data analysis system based on Internet of Things and artificial intelligence. The pavement distress inspection data analysis system based on Internet of Things and artificial intelligence comprises: a central server, an inspection planning module, and a distress recognition module. By retrieving a set of distress types from the central server, a plurality of inspection paths including a main road are automatically generated; a comprehensive analysis of traffic flow, pavement distress, etc. on the paths is conducted to obtain priority indexes, efficiency analysis is performed on inspection devices so as to obtain inspection values, and accordingly, allocation of path inspection tasks is performed, thereby forming a dynamic path inspection plan. By performing distress recognition on collected pavement images, distress types and distress levels can be accurately extracted from the pavement images, thereby providing a quantitative distress assessment; and then deduplication-based recognition is performed on pavement images in which pavement distress is present, such that the similarity between a target image and comparison images can be accurately determined, thereby avoiding repeated inspection and improving the efficiency and accuracy of distress inspection.

The utility model discloses a mounting structure capable of stably mounting a monitoring radar, which comprises a speed measuring support and the monitoring radar, the monitoring radar is arranged at the top of the speed measuring support, and the speed measuring support is fixed on the ground. Through cooperative use of a limiting device, a limiting block, a spring, a moving hole and a limiting groove, the problems that an existing vehicle speed radar detector is equipment for monitoring and recording the vehicle running speed through the radar technology, usually works based on the Doppler effect principle, is often installed at key positions such as main roads or entrances and exits and the like, and is inconvenient to use are solved. A monitoring radar is installed in a bolt or metal hoop mode, the bolt is exposed outdoors for a long time and is prone to rusting and aging to cause unstable installation, and the metal hoop is prone to breakage due to temperature change or material aging to cause falling of the monitoring radar after being used for a long time. However, a vehicle speed radar detector used for vehicle speed monitoring in the prior art is not provided with a component for more stable installation.

The invention relates to an abnormal road scene image recognition and early warning system, and belongs to the technical field of computer vision and intelligent traffic. The system adopts a distributed architecture with edge computing and cloud collaboration, introduces a differential geometry theory to construct a road scene representation framework, collects data through a camera sensing unit, and sends the data to a cloud server; the edge computing unit executes preprocessing, and the cloud processing unit completes anomaly detection and early warning. The core innovation of the system is that the manifold learning representation module maps high-dimensional features to a Riemannian manifold space; the Riemannian geometric anomaly measurement module defines a multi-dimensional anomaly index; the multi-scale adaptive analysis module realizes comprehensive detection from macroscopic to microscopic; the abnormal scene library is automatically updated; the multi-vehicle cooperation module supports information sharing and joint decision making, the system achieves the effects that the anomaly detection precision is improved by 25-35%, the environmental adaptability is enhanced by 50-70%, the response time is controlled within 250 ms, major road anomalies can be pre-warned 5-30 seconds in advance, the traffic accident risk is reduced by 30-40% potentially, and the traffic efficiency is optimized.

The invention discloses a local shape-based road network matching method in a freehand sketch, which comprises the following steps of: 1, calculating centrality and intermediate characteristics of each road in the freehand sketch in a road network, and extracting main roads in the area from the road network; 2, calculating the shape similarity between the main road extracted from the freehand sketch and the road in the actual map by using the shape distance factor; and 3, quantifying morphological characteristics of the road. Within a preset threshold range, calculating the similarity between the road in the freehand sketch and the road in the actual map on key point features; 4, quantifying the direction change of the road, and calculating the similarity of the road in the freehand sketch and the road in the measurement map in the advancing direction; and 5, calculating the comprehensive similarity between the roads in the freehand sketch and the roads in the actual map by using a weighted average method. And generating a sorting list of the road matching sets in the actual map based on the calculated sum of the comprehensive similarities.

To provide a traffic information providing device and traffic information providing method that accurately predict the risk of traffic jams occurring on main roads based on changes in the ratio of the number of vehicles traveling on main roads and non-main roads in a target area over a predetermined period, using location information collected from multiple vehicles. [Solution] The traffic information providing device includes a driving information acquisition unit that acquires driving information from vehicles, a map information acquisition unit that stores map information, a calendar information acquisition unit that stores calendar-related information, a weather information acquisition unit that acquires weather information, and an evaluation unit that calculates the ratio of vehicles traveling on each road during the forecast period in a predetermined area, compares this with the ratio of vehicles traveling on each road between the forecast period and past periods, and determines that if the weather information during the forecast period is worse than in past periods, and the ratio of vehicles traveling on roads with lower road levels is higher than that of roads with higher road levels, then there is a high risk of traffic jams occurring on roads with high road levels within the predetermined area.

The present invention relates to the technical field of road disease identification, and specifically to a road disease inspection data analysis system based on the Internet of Things and artificial intelligence; the system comprises: a central server, an inspection planning module and a disease identification module; by calling various types of disease sets in the central server, a plurality of inspection paths including main roads are automatically generated, the vehicle flow, road diseases and the like of each path are comprehensively analyzed to obtain a priority index, and the efficiency of inspection equipment is analyzed to obtain an inspection value, and path inspection tasks are allocated accordingly, thereby forming a dynamic planning of path inspection; by performing disease identification on collected road images, the disease type and disease degree in the road image can be accurately extracted, and a quantitative disease evaluation can be provided; then, de-duplication identification is performed on road images with road diseases, and the similarity between a target image and a comparison image can be accurately judged, repeated detection is avoided, and the efficiency and accuracy of disease detection are improved.

The invention relates to the technical field of urban inland inundation early warning, and provides an urban inland inundation waterlogging evaluation method and device, electronic equipment and a storage medium, and the method comprises the steps: obtaining low-resolution DEM data and geographic vector data of a target urban region; the geographic vector data comprises road vector data and river vector data; performing resampling on the low-resolution DEM data to obtain high-resolution DEM data; performing correction processing on the road vector data based on the high-resolution DEM data so as to perform elevation sampling on a starting point and an end point of a main road and perform elevation sampling on a starting point and an end point of a non-main road to obtain road elevation data; performing elevation correction on the river vector data to obtain river elevation data; performing flooding depth calculation according to the road elevation data and the river elevation data; and performing flooding risk assessment based on the calculated flooding depth. According to the method, the accuracy of calculating the waterlogging depth of the urban inland inundation can be improved, so that the accuracy of risk early warning evaluation is improved.

The invention is suitable for the technical field of traffic emergency management, and provides a major road traffic accident emergency decision and response method and system. According to the method, data preprocessing of timestamp synchronization and coordinate conversion is carried out by carrying out multi-source data acquisition and fusing geographical environment data, so that composite scene data is generated; performing accident risk prediction and deduction analysis according to the composite scene data to obtain a prediction evaluation result, and planning an optimal rescue path based on a digital elevation model; dynamic resource scheduling is carried out, and an optimized emergency scheme is generated based on a prediction evaluation result; intelligent warning control and monitoring transmission control are carried out on the intelligent robot and the unmanned aerial vehicle, operation parameters are adjusted in real time in combination with a digital elevation model, and traffic guidance is carried out. Risk prediction and early warning of traffic accidents, quick response when the accidents occur, scientific decision making and efficient rescue can be achieved, traffic is quickly dredged after the accidents, and casualties, property losses and traffic jam influences caused by the accidents are reduced to the maximum extent.

The present application discloses a road planning method for an agricultural-photovoltaic complementary photovoltaic power station, which belongs to the technical field of road planning. The method comprises the following steps: dividing the field into different functional areas; pre-arranging the main road trunk lines in each functional area; for the crop planting areas or photovoltaic module areas on both sides of the trunk road, supplementing with a number of branch roads, ensuring the convenience of operations within each area, avoiding shading of the planted plants or damage to the photovoltaic modules; optimizing the roadbed, pavement, width and curve radius parameters of the main road and branch roads so that they can simultaneously meet the size and load requirements of agricultural machinery and photovoltaic equipment transportation; at the intersection of the main road and branch roads, adopting a layered three-dimensional design to achieve barrier-free passage of agricultural machinery or photovoltaic transport vehicles; conducting simulation analysis on the planned roads, and making targeted optimization adjustments for possible problems.

This traffic signal control system comprises: a first acquisition unit that acquires specific vehicle information indicating the traffic state of a specific vehicle traveling on a major road toward an intersection where the major road and a minor road intersect; and a control device. The control device comprises a processing unit that executes a selection process for selecting, on the basis of the specific vehicle information, a control process to be executed by the control device from among a first control process for controlling a signal light installed at the intersection and a second control process for controlling the signal light such that the priority degree for prioritizing passage of vehicles on the major road over passage of vehicles on the minor road is higher than that in the first control process.

The invention discloses an electric vehicle charging demand prediction method, system and device based on dynamic traffic information, and a medium. The method comprises the following steps: obtaining road information of a target area, extracting main roads to construct a road topological structure chart, and establishing a road network coefficient model; calculating the type proportion value of each unit area according to the interest point data, and determining the type with the maximum type proportion value as the functional area type of the corresponding road network node; using the road network coefficient model to calculate a driving path of the electric vehicle from a travel starting point to a travel ending point; calculating the charging demand quantity of the electric vehicle at each path of network node; and mapping the charging demand to a corresponding power grid node to obtain an electric vehicle charging demand prediction result of each power grid node. According to the method, the road topological structure diagram is constructed by acquiring actual road information, the road section impedance value and the node impedance value are calculated based on the road section saturation, and the road network coefficient model capable of reflecting traffic jam and signal lamp delay is established.

The invention discloses an image-based community road damage monitoring and maintenance method, equipment and a medium. The method comprises the following steps: step 1, installing a camera and intelligent visual analysis equipment; step 2, through unmanned aerial vehicle aerial photography or manual marking, obtaining road range edge spaces based on five types of main roads, group roads, house small roads, garden roads and squares; meanwhile, materials of roads in the community are marked; 3, acquiring picture information of a specified road section through a camera, and marking a corresponding picture based on the data in the step 2; and step 4, processing and analyzing the data and pictures in the step 2 and the step 3 through an intelligent algorithm, and identifying the road damage degree. According to the method, road damage types, sizes and evaluation marks are structured, so that damage degree classification can be better carried out by using a classification algorithm, and a basis is determined for a maintenance scheme.

The invention discloses a vehicle operation route planning method, device and equipment and a storage medium, and the method comprises the steps: collecting the index data related to the operation risk of an automatic driving vehicle on each road, and the index data comprises the road configuration data, the road surface condition data, the surrounding environment data and the traffic operation condition data; calculating a risk index score of each road section on each road by using the index data, and calculating a comprehensive risk index score of each road through the risk index scores; and according to the comprehensive risk index score, planning an optimal operation route of the autonomous vehicle. The method can identify the major hidden risk of the road, reduces the operation risk of the automatic driving vehicle, and effectively avoids the harm to the public safety.

The specification provides a coal rock pore network calibration method, device and equipment. The method comprises: obtaining an initial fracture system of a target coal rock, an initial matrix pore of the target coal rock, a preset main road equivalent rule and a preset secondary road equivalent rule; according to the preset main road equivalent rule, the initial fracture system is equivalent to a main road, and according to the preset secondary road equivalent rule, the initial matrix pore is equivalent to a secondary road; extracting micron-scale characteristic parameters in the main road and nanometer-scale characteristic parameters in the secondary road; according to the micron-scale characteristic parameters and the nanometer-scale characteristic parameters, a target coal rock pore network is generated; and the target coal rock pore network is calibrated as a whole to obtain a calibration result. Based on the above method, effective calibration of the target coal rock pore network can be realized.

The present invention discloses a method and device for optimizing a traffic microcirculation network in urban renewal. Based on the structural characteristics of at least one urban traffic road network, at least one first element is determined, and the first element reflects the first roads in the urban traffic road network that are not interrupted. Based on at least one first element and preset conditions, through topological depth calculation, the number of branch roads connected to each of the first roads is obtained. Based on at least one first element and the calculation results, a connectivity algorithm analysis model is established. Based on the connectivity algorithm analysis model, the urban traffic road network to be optimized is optimized to obtain an urban traffic target microcirculation network. By using the connectivity algorithm analysis model to optimize the urban traffic road network to be optimized, the connectivity of the main roads is improved by driving with branch roads, and the internal vitality of the road network is fully stimulated. Therefore, by implementing the present invention, the vitality and attractiveness of the road network are improved, and the problems of traffic microcirculation blockage and serious internal closure of the road network in the city are solved.

Some embodiments provide a navigation application with a novel declutter navigation mode. In some embodiments, the navigation application has a declutter control that when selected, directs the navigation application to simplify a navigation presentation by removing or de-emphasizing non-essential items that are displayed in the navigation presentation. In some embodiments, the declutter control is a mode-selecting control that allows the navigation presentation to toggle between normal first navigation presentation and a simplified second navigation presentation, which below is also referred to as a decluttered navigation presentation. During normal mode operation, the navigation presentation of some embodiments provides (1) a representation of the navigated route, (2) representations of the roads along the navigated route, (3) representation of major and minor roads that intersect or are near the navigated route, and (4) representations of buildings and other objects in the navigated scene. However, in the declutter mode, the navigation presentation of some embodiments provides a representation of the navigated route, while providing a de-emphasized presentation of the roads that intersect the navigated route or are near the navigated route. In some embodiments, the presentation shows the major roads that are not on the route with more emphasis than minor roads not on the route. Also, in some embodiments, the presentation fades out the minor roads not on the route more quickly than fading out the major roads not on the route.