282 results about "Trunk line" patented technology

The invention relates to an arterial traffic coordination control real-time optimization method. The method comprises the following steps: S1, collecting traffic data and converting the traffic data into input data suitable for a graph neural network; s2, constructing a graph data structure, setting intersections as nodes, setting road sections as edges, and adjusting the weight of the weighted adjacent matrix at a fixed frequency according to the traffic data of the road and the historical traffic flow; s3, taking the graph data structure in the S2 as input, constructing a graph neural network model, and capturing spatial-temporal characteristics among nodes; and S4, formulating or adjusting an objective function according to the spatial-temporal characteristics, the actual traffic demands and the constraint conditions, solving the objective function by a genetic algorithm, carrying out continuous iteration on crossover and variation, and evaluating individuals according to the objective function and the constraint conditions in each iteration to obtain an optimal signal timing scheme. According to the method, spatial-temporal characteristics are effectively captured by adopting a graph neural network technology, signal timing optimization is carried out in combination with a genetic algorithm and reinforcement learning, and a signal timing scheme can be dynamically adjusted according to real-time traffic demands.

The invention discloses a power transmission line fault positioning method and system based on ground potential end transient information perception, and relates to the technical field of line fault positioning, and the method comprises the steps: obtaining a voltage traveling wave signal and a current abrupt change rate signal detected by a trunk line and branch node sensor array in a power transmission line; processing the voltage traveling wave signal and the current abrupt change rate signal to obtain traveling wave components and polarity-amplitude calibration results of different modes; according to traveling wave components and polarity-amplitude calibration results of different modes, in combination with topological parameters of the power transmission line and spatial distribution of a ground potential end sensor, adjusting edge weights or connection relationships in the graph structure to obtain a composite feature matrix and an edge weight matrix of each node; and inputting the composite feature matrix and the edge weight matrix of each node into a graph neural network positioning model, and outputting a power transmission line fault positioning result. According to the invention, through ground potential end information fusion and the dynamic graph neural network, accurate fault positioning under a complex power transmission topology is realized.

The invention provides a traffic signal lamp intelligent regulation and control system based on big data, and relates to the technical field of traffic signal lamp regulation and control systems, and the system comprises a multi-channel data collection module which is responsible for collecting traffic data of a plurality of channels, guaranteeing the comprehensiveness and accuracy of the data, and transmitting the traffic data to a cloud server; a geomagnetic sensor, a radar sensor and a camera device on a road are used for collecting the flow, speed and occupancy information of vehicles in real time, the change of the traffic flow can be sensed timely and accurately through multi-source data collection and real-time analysis, and a signal lamp timing scheme is adjusted rapidly according to the change condition, so that the traffic light timing efficiency is improved. Regulation and control of signal lamps are more in line with actual traffic demands, vehicle waiting time is effectively reduced, road passing efficiency is improved, and through green wave band control and trunk line coordination control means, overall traffic operation efficiency of a region is improved, road network traffic flow is balanced, congestion diffusion of local road sections is avoided, and overall operation stability of urban traffic is improved.

The invention discloses a dust suppression method and system for railway track dry bulk cargo loading. The method comprises the steps that if it is detected that loading operation is started on an iron road trunk line, an area to be subjected to dust suppression is determined based on loading operation field data; acquiring environment information corresponding to the region to be subjected to dust suppression, wherein the environment information comprises wind direction information; determining a to-be-loaded article based on the loading field operation data, and determining the moisture content corresponding to the to-be-loaded article; and a control strategy corresponding to the spraying system is determined based on the wind direction information, the water content and the area corresponding to the area to be subjected to dust suppression, and operation parameters corresponding to the spraying system are adjusted based on the control strategy so as to perform dust suppression treatment on the loading operation process. According to the invention, accurate treatment of railway track loading flying dust pollution is realized, limitation of traditional fixed dust suppression is broken through, and pollution prevention and control efficiency and resource utilization efficiency are remarkably improved.

The invention relates to the technical field of logistics management, and discloses an operation and control analysis method, device and equipment based on logistics transportation, and a medium, and the method comprises the steps: carrying out the preprocessing of to-be-controlled waybill data, removing invalid data, and screening an effective delivery record as a judgment basis; establishing a multi-layer affiliation relationship according to the judgment basis and marking label information; inputting the waybill data, the corresponding multi-layer affiliation relationship and the label information into an abnormal path identification model, and outputting an abnormal type corresponding to the waybill data, wherein the abnormal type at least comprises trunk line empty running, advanced departure and non-network area recovery type anomalies; and generating an abnormal path trend according to the waybill data and the corresponding abnormal type, and generating delivery optimization information according to the abnormal path trend, the delivery vehicle corresponding to the waybill data and the main delivery area so as to perform delivery optimization on the waybill data within the set time and distance range. The method is suitable for intelligent management of logistics enterprises on delivery path optimization, transport capacity scheduling and operation efficiency improvement.

The invention relates to a vision-semantic collaborative perception method and system for an automatic driving vehicle. Comprising a visual-semantic feature coding module and a visual-semantic feature fusion module. The visual-semantic feature encoding module comprises a text semantic encoder and a visual space-time encoder; a visual space-time encoder extracts single-frame semantic and structural features based on a 2D visual encoding model, and a 3D visual encoding model is adopted for modeling to form 3D frame-level fusion visual perception features; and the visual-semantic feature fusion module comprises a time converter, a cross converter and a context enrichment converter, and is used for adaptively adjusting a fusion weight based on a dynamic weight fusion strategy to generate required visual-semantic feature fusion information. According to the invention, the multi-modal weight is automatically adjusted, the environment perception error and decision delay are reduced, the adaptability and response precision of the automatic driving vehicle to the trunk line logistics complex traffic scene are improved, and the safe and stable operation of the intelligent driving system in the complex road environment is ensured.

The invention relates to the technical field of communication, in particular to a dynamic service scheduling method for a 5G new call based on intelligent semantics, which realizes efficient scheduling of 5G call services through three core steps of multi-operator fusion access, dynamic routing distribution and intelligent voice interaction. According to the method, a unified SIP trunk line integration platform is constructed, and network resources of three major operators are integrated; respectively designing routing strategies for low-concurrency and high-concurrency scenes from the dimensions of network quality, cost rate, compliance, link load and the like, and dynamically optimizing path selection through a weight algorithm; and intelligent analysis and interaction of voice semantics are realized by combining ASR, TTS and NLP engines. According to the method, the problems of cross-operator routing optimization, high-concurrency processing and compliance management are solved, and the method is suitable for scenes with high requirements on stability and compliance, such as finance and government affairs.

The invention discloses an urban trunk network-oriented reconfigurable quantum communication route synchronization system, which relates to the technical field of quantum communication and comprises a quantum channel state sensing module, a clock offset prediction and registration module, a reconfigurable route planning engine, an entangled state registration and regulation module, a synchronization instruction scheduling module and an optimization module. According to the system, de-coherence time, entanglement fidelity and synchronous offset risk of a quantum link are sensed in real time, a quantum link feasibility scoring graph is generated in combination with a graph neural network, and an optimal entanglement forwarding path is output according to the quantum link feasibility scoring graph; meanwhile, the width and rhythm of a transmission window are dynamically adjusted based on task priorities and network loads, and cross-node high-precision synchronization and resource coordination are achieved; a routing and synchronization strategy can be continuously optimized by introducing a communication performance evaluation model and a feedback learning mechanism; according to the invention, the stability of the quantum communication system in a complex urban network environment is significantly improved.

A method may include, at a control system, receiving a trip request specifying an origin boarding zone and a destination boarding zone, determining a path for the trip request, the path extending from the origin boarding zone and along at least a portion of a trunk lane of a roadway system, assigning the trip request to a vehicle, determining, based at least in part on a location of a parking spot where the vehicle is parked at the origin boarding zone, an estimated transit duration of the vehicle from the parking spot to an entrance to the trunk lane, selecting, based at least in part on the estimated transit duration, a moving position-target from a set of candidate moving position-targets, and causing the vehicle to travel from the parking spot to the trunk lane and travel along the portion of the trunk lane by following the selected moving position-target.

The invention provides a trunk line green wave control method for dynamically adjusting green light duration based on real-time sensing data, and relates to the technical field of green wave control, and the method comprises the steps: obtaining a fusion feature set at each intersection of a trunk line; determining an initial green wave period, an initial phase difference and an initial green light duration; a continuous passing zone is formed; dynamic compensation is carried out on the steering phase green light duration, and linkage correction is carried out on the steering phase green light duration and a straight-going phase adjustment result; the pedestrian phase is incorporated into the phase structure of the current period in an insertion mode, and timing calibration with the next period is executed; performing micro-amplitude correction on the phase difference of the adjacent intersections to obtain a phase difference reference distribution scheme; periodically evaluating the control effect to obtain a green wave period reference value; and performing adaptive updating on the green wave period reference value and the phase difference reference distribution scheme. According to the invention, the technical problem of low trunk line green wave control efficiency in the prior art can be solved, and the technical effect of improving the trunk line green wave control efficiency is achieved.

The invention discloses a multi-dimensional monitoring and identification method for an inspection robot of rail transit, and the method comprises the steps: obtaining rail data in real time through arranging a laser radar and a visual inertia fused synchronous positioning module on the inspection robot, and constructing an inspection backbone network; segmenting a rail transit trunk line in real time by adopting a self-adaptive module in the inspection trunk network, and obtaining coordinates and data features between rail data sampling points; building a track monitoring framework based on the three-dimensional point cloud, monitoring the track state in real time according to the data characteristics by adopting an edge detection method, and obtaining track state monitoring data; traversal detection is performed on the track state monitoring data by adopting a neural network, a panoramic image data set of a traffic track is acquired in real time, and the traffic track is automatically monitored and identified, so that the inspection efficiency is remarkably improved, the labor cost is reduced, safe and stable operation of track traffic is ensured, the robustness and adaptability of the system are enhanced, and the system reliability is improved. And effective monitoring and management of the track state are also realized.

The invention belongs to the technical field of emergency material multimodal transport scheduling, and particularly relates to an emergency material multimodal transport scheduling optimization method considering risk sensitivity, which comprises the following steps of: A, constructing an emergency material multimodal transport network in which a trunk line and a tail end are coordinated, mapping trunk line transport and tail end transport into a multimodal transport network diagram, determining nodes, feasible line sets and parameters thereof; b, establishing an emergency material multimodal transport scheduling optimization model considering risk sensitivity, and establishing a risk-sensitive scheduling optimization model based on an emergency material multimodal transport network and the obtained parameters; and C, generating a model solving result and a scheduling scheme, converting the scheduling optimization model into a solvable form, generating an executable scheduling scheme, verifying the result, and forming a complete technical closed loop. The method has the advantages that the adaptive capacity and robustness of the emergency logistics system under extreme situations such as path blocking are remarkably improved, and the method is suitable for popularization and application. And important decision support is provided for scientifically coping with disaster rescue.

The utility model discloses an intelligent sentry early warning system, and relates to the technical field of road safety early warning. The warning module is fixedly connected to one side of the support; the bottom end of the first speed measurement monitoring device is fixedly connected with a rotating shaft, the rotating shaft is rotatably connected with the support, the bottom end of the rotating shaft is slidably connected with a first end-toothed disc in the axial direction of the rotating shaft, and a positioning shaft is arranged in the support; the top end of the positioning shaft is fixedly connected with a second end-toothed disc meshed with the first end-toothed disc, and the outer side of the rotating shaft is sleeved with a spring used for driving the first end-toothed disc to reset. The intelligent sentry early warning system can detect whether vehicles come from a trunk line and a branch line or not and remind the vehicles on the branch line that the vehicles come from the trunk line and slow speed reduction is slow through the warning module, so that traffic accidents are reduced; meanwhile, the angle is convenient to adjust.

The invention discloses a trunk line adaptive coordination control method based on a dynamic green light starting time interval. The trunk line adaptive coordination control method comprises the following steps: collecting traffic information; determining influence factors of the green light starting time interval; establishing a green light starting time interval adaptive optimization model; determining a trunk line adaptive coordination timing optimization scheme based on the dynamic green light starting time interval; and outputting a trunk line adaptive coordination timing optimization scheme based on the dynamic green light starting time interval. The green light starting time interval of the adjacent intersection is dynamically optimized according to the dynamically obtained number of queuing vehicles at each intersection, and the green light starting time interval is applied to trunk line coordination control scheme optimization, so that the method has the characteristics of high universality and wide coverage; the dynamic green light starting time interval optimization model established by the invention accords with the change of traffic flow of each intersection of an actual trunk line, the calculation precision is high, and the workload is small; the method can provide an accurate trunk line adaptive coordination control scheme, and is high in scientificity, high in calculation precision and good in reliability.

The invention relates to the field of intelligent traffic and vehicle-road cooperation, in particular to a traffic operation double-control intelligent system. Comprising a multi-mode roadside sensing module used for obtaining traffic operation state data and environment state data of a road section; the double-control cooperation unit is used for jointly generating variable speed limit setting and signal control adjustment quantity based on the traffic operation state data and the environment state data; the signal control module is used for carrying out on-line adjustment on intersection phase timing or trunk line phase difference according to the signal control adjustment amount; the road information broadcasting module is used for broadcasting road information to the vehicle; the consistency verification module is used for carrying out consistency comparison on the road information, the actual signal lamp state and the phase remaining time; and the safety domain management module is used for applying double-hysteresis safety domain constraint to the variable speed limit setting and the signal control adjustment amount. According to the invention, the cooperation of two links is realized, the vibration suppression steady state is consistent with the release, and the driving behavior is stably and verifiably guided.

According to the method for evaluating the urban trunk traffic signal control effect based on the single-vehicle theory provided by the invention, the obtained gate data is used for deducing to obtain a time theoretical value sequence for all vehicles on a certain lane to arrive at a downstream intersection within a certain time period needing phase positioning; and further obtaining a green light phase arrival proportion and an upstream intersection signal control phase evaluation index. According to the evaluation method provided by the invention, the Platon Ratio index calculation model which is more suitable for the actual situation and is based on the bicycle identification data is provided; the theoretical arrival time of the vehicle arriving at the parking line at the intersection is deduced by using the vehicle matching characteristics of the single vehicle identification data, and the new model has practical guiding significance; the TAD trunk line coordination evaluation index based on the single vehicle identification data is provided, the PCD index for evaluating the trunk line coordination control effect provided in the prior art and a calculation method are improved, the limitation of the PCD index in domestic application is improved, and the method has more practical guiding significance in China.

The invention discloses a full-link coverage logistics optimization method, which comprises a goods picking step and a goods allocation step, and the goods picking step comprises a goods taking mode judgment step which comprises a whole vehicle transportation mode and a circulating goods taking mode; and when the goods taking mode is a circulating goods taking mode, determining a goods taking transportation path and a loading scheme, determining the loading scheme comprises determining a loading sequence and determining a loading position, and the goods taking transportation path comprises paths between suppliers and between the suppliers and goods picking bins. According to the full-link coverage logistics optimization method, multi-customer, multi-cargo-warehouse and multi-supplier order demands are considered, joint optimization is carried out on an existing path planning system in three links of front-end cargo picking, trunk transportation and turnover appliance management, the efficiency and cost control capability of automobile logistics are comprehensively improved, transportation resources are reasonably scheduled, and the transportation efficiency is improved. And the logistics cost is reduced.

The invention discloses a method and a system for optimizing a cargo flow transportation strategy. The method comprises the following steps of: establishing a full-flow simulation calculation super network model of containers from highway collection and distribution, railway collection and distribution, inland river port transfer and trunk line central bond port transportation to destination ports on the basis of three-dimensional traffic network transportation mode conditions; by calculating the transportation cost, the transportation time, the transfer cost and the transportation reliability of each transportation link in the super network model, establishing a generalized cost function for the cost, the time and the transportation volume of container freight; and according to the generalized cost function, container network traffic distribution is carried out, the path with the lowest generalized cost of all paths between the container starting point and the container ending point is calculated, and a cargo flow transportation strategy is formulated. According to the scheme, the total transportation volume and the transportation cost of the scheme under the conditions of large-scale networking and optimal transportation cost of a current situation and a planned port can be evaluated, and the transportation scheme is optimized and evaluated, so that the transportation economic benefit is improved.

The invention relates to the technical field of urban pipeline natural gas transmission and distribution, and particularly provides an urban gas pressure regulation control method and system, and the method comprises the steps: obtaining the current transmission and distribution data of a gas transmission and distribution trunk line at regular time based on a plurality of data collection terminals; the plurality of data acquisition terminals are additionally arranged outside a gas transmission and distribution main line; processing the current transmission and distribution data, and determining the preloading pressure of a pressure regulating device corresponding to the gas transmission and distribution main line; the preloading pressure is a difference value between a preset pressure value of the pressure regulating device and a current spring pressure value; and the pressure regulating device is controlled to perform composite pressure increasing or reducing treatment based on the preloading pressure. According to the invention, based on the current transmission and distribution data acquired by the plurality of data acquisition terminals installed outside the gas transmission and distribution trunk line, the preloading pressure of the pressure regulating device corresponding to the gas transmission and distribution trunk line is analyzed and generated, and the preloading pressure is loaded into the pressure regulating spring cavity of the pressure regulating device to complete increase and decrease pressure regulation. And the stability and the reliability of the pressure regulating system in the gas consumption peak period and the low peak period are improved.

The invention relates to the field of urban traffic management and signal control, and discloses an urban mesoscopic credit control unit division method based on breadth search, which comprises the following steps: collecting traffic data in a road network, calculating an optimal signal timing scheme, and finely adjusting a signal period according to a downstream overflow risk; by calculating the coordination benefit of each steering, effective coordination steering is screened out, and a signal coordination trunk line is generated; generating a credit control unit by using a breadth search algorithm (BFS), and reasonably dividing the credit control unit into a single-point credit control unit, a trunk line credit control unit and a regional credit control unit; finally, by calculating the coordination direction and the phase difference, signal coordination and green wave passing are ensured, and a signal control scheme of a road network is optimized. According to the method, the traffic capacity of urban traffic can be improved, traffic congestion is reduced, and the overall traffic fluency is improved.

The invention relates to a phase difference dynamic transition control method and a phase difference dynamic transition control system based on a holographic sensing technology, and aims to optimize trunk traffic signal coordination control and improve traffic flow efficiency. The method comprises the following steps: collecting traffic index data (such as flow, queuing length and the like) of lane levels of all intersections of a trunk line in real time through holographic sensing equipment; obtaining a new scheme and an old scheme of trunk line coordination, and calculating a phase difference offset; according to the phase difference offset, determining the number of cycles required by transition and the duration of each cycle, and generating a transition scheme; dynamically adjusting the phase duration and the signal control instruction of each intersection based on the real-time traffic data; and issuing the control instruction to the annunciator for execution. The method is suitable for urban trunk traffic signal control, and has high practicability and popularization value.

The invention provides an inventory allocation method and device, electronic equipment, a storage medium and a program product, and the method comprises the steps: predicting the number of sold pieces of each target SKU in each warehouse in a future preset time period, and obtaining the predicted number of sold pieces of the target SKU; solving an allocation plan of the target SKU; solving a train number allocation scheme of the allocation plan by taking the target local satisfaction rate meeting the dispatching-in warehouse as a constraint and taking the minimization of the total cost as a target; wherein the total cost is equal to the sum of the main line allocation cost, the upper and lower frame damage cost and the tail-stroke saving cost; the tail-stroke saving cost is used for representing a difference value between the local delivery freight and the cross-regional delivery freight of the target SKU; and carrying out inventory allocation based on the train number allocation scheme. According to the scheme, the complex inventory allocation decision problem is divided into three stages, the whole allocation process is gradually optimized, it is ensured that the decision of each stage is based on the optimal result of the previous stage, and the inventory allocation effect of the inventory allocation method is improved.

The technical scheme of the invention discloses a traffic flow prediction method based on a dynamic space-time diagram convolutional network. The invention provides a traffic flow prediction method fused with a dynamic space-time diagram convolutional network, which captures road network change in real time through a dynamic adjacency matrix, designs a multi-scale time attention mechanism to fuse local convolutional features and global time sequence dependence, develops an intelligent mixed precision training system to realize computing resource optimization, and improves the traffic flow prediction efficiency. And the training efficiency is improved while the prediction error is reduced. Meanwhile, traffic flow data time features and multi-section spatial features are comprehensively considered, and prediction is carried out based on a single step length and multiple step lengths. The method realizes high-precision prediction of the short-time traffic flow, and is suitable for precise flow prediction of a main line and an arterial highway of a highway network.

This invention discloses a method and system for dust suppression during the loading of dry bulk cargo on railway lines. The method includes: if loading operations are detected to have commenced on the main railway line, determining the area to be suppressed based on on-site loading data; acquiring environmental information corresponding to the area to be suppressed, including wind direction information; determining the items to be loaded based on the on-site loading data, and determining the corresponding moisture content of the items; determining a control strategy for a spray system based on the wind direction information, moisture content, and the area to be suppressed, and adjusting the operating parameters of the spray system based on the control strategy to suppress dust during the loading process. This invention achieves precise control of dust pollution during railway loading, overcoming the limitations of traditional fixed dust suppression methods, and significantly improving pollution prevention efficiency and resource utilization effectiveness.

The invention discloses a cross-domain collaborative order dispatching method and system based on dynamic decomposition of a service chain, and relates to the technical field of voltage control, and the method comprises the following four steps: 1, collecting order basic information, synchronously calling demand quantification, resource quantification, basic attributes and time-space cost parameters, and carrying out real-time scheduling; the method comprises the following steps: screening order basic suitability according to a threshold value, and then judging a three-dimensional label; 2, judging whether to start service chain decomposition or not according to requirements and resource parameters, matching three schemes if the service chain decomposition is needed, and marking a single transport capacity mode if the service chain decomposition is not needed; 3, differentially matching the transport capacity, selecting the optimal transport capacity according to a comprehensive score in a single transport capacity mode, and matching the corresponding transport capacity for pickup, trunk line and tail end tasks according to a scheme if decomposition is needed; and 4, sending an execution instruction to the transport capacity, monitoring performance parameters in stages, generating three strategies of maintenance, local adjustment and scheme reconstruction according to deviation, storing the adjusted parameters into a database, and supporting efficient order dispatching and quality control.

The invention discloses a traffic signal management and control method and device based on AI edge calculation, and relates to the technical field related to communication, and the method comprises the steps: dividing an intersection passing right into space-time resource slots through real-time interaction between a roadside edge node and a vehicle-mounted terminal; when multiple vehicles request the same slot position, detecting occupation conflicts of the same space-time resource slots, and starting block chain auction fair distribution; and adjacent edge nodes share the result and generate a digitally signed signal control instruction through distributed machine learning collaborative optimization so as to realize signal lamp switching management and control. The technical problems that in traffic signal control, fixed timing is not matched with actual traffic flow changes, trunk line green wave coordination is difficult to adapt to dynamic traffic flow changes, cloud control network delay and fluctuation are caused, and traffic signal disorder is easily caused by vehicle priority passing are solved. The technical effects of improving the traffic efficiency and the real-time reliability of traffic signal management and control when the priority vehicle and the common vehicle are mixed, enhancing the cooperative control capability of the adjacent intersections and reducing the cloud control pressure are achieved.

The application discloses a trunk green wave parking intersection recommendation method, which overcomes the problem that the existing technology cannot recommend parking intersections for a trunk line that cannot realize bidirectional green waves, and comprises the following steps: calculating the distance between two adjacent intersections on the trunk line to obtain an intersection pair recommendation sequence Z; calculating the average lane number difference between the coordinated direction and the non-coordinated direction of each intersection to obtain an average lane number intersection recommendation sequence A; calculating the average lane flow difference between the coordinated direction and the non-coordinated direction of each intersection to obtain a lane average flow intersection recommendation sequence B; calculating the flow similarity between intersections to obtain an intersection flow trend intersection recommendation sequence; obtaining a final output list from the obtained intersection recommendation sequence, and outputting corresponding recommendation reason labels. The trunk green wave parking intersection recommendation method can recommend a downlink direction parking intersection recommendation list and a recommendation reason for a trunk line that cannot realize bidirectional green waves, and improves the intelligent level of traffic control.

The present disclosure provides a traffic guidance method, apparatus, electronic device and storage medium, relating to the field of artificial intelligence, and particularly to fields such as intelligent transportation and vehicle-road collaboration. The specific implementation solution is as follows: obtain the historical traffic flow information of the congested arterial road; determine the set of traffic flow merging nodes upstream of the congested arterial road according to the historical traffic flow information; plan at least one detour route based on the set of traffic flow merging nodes; generate guidance indication information based on the at least one detour route, so as to conduct traffic guidance through the guidance indication information. By adopting the present disclosure, the congestion relief effect for the congested arterial road can be improved, thereby effectively solving the congestion problem of the congested arterial road.

A wire harness includes a trunk line extending from an upstream side to a downstream side, a plurality of branching units respectively provided at each of a plurality of branching points on the trunk line, and a plurality of branch lines branching out from the plurality of branching units, wherein the trunk line includes a trunk conductor, wherein the branch line includes a branch conductor, and wherein the branching unit includes a conductor connection portion that electrically connects the trunk conductor on the upstream side to the trunk conductor on the downstream side and to the branch conductor, and a cover portion including an insulating material that covers the conductor connection portion and surroundings thereof.

A trunk bus connector for electrically coupling one or more branch cables to a trunk line may comprise a junction area where one or more stripped portions of the branch cable(s) can be secured against a stripped portion of the trunk line. The trunk bus connector may comprise an overmold substantially encapsulating the junction area and comprising a trunk line pathway to enable the trunk line to pass through the junction area. The overmold may comprise one or more branch entry pathways to enable the branch cable(s) access into the junction area. Each branch entry pathway may be angled with respect to the trunk line pathway such that the branch cable(s) enter into the junction area such that an angle at which each branch cable approaches the trunk line is between approximately 30 and 50 degrees.