132results about How to "Improve traffic capacity" patented technology

The invention discloses a multi-intersection signal cooperative control method based on deep reinforcement learning, and the method comprises the steps: firstly constructing a comprehensive reward function which comprises waiting time, queuing length and the influence of adjacent intersections, and constructing a mathematical model of a multi-intersection signal control system based on the reward function, so as to achieve the maximization of a comprehensive reward; and secondly, designing a deep Q network cooperative control algorithm for explicit strategy adjustment, and optimizing and adjusting adjustable strategy function parameters by introducing an explicit strategy adjustment function and utilizing a stochastic gradient descent method. And finally, dynamically adjusting the signal control strategy of each intersection in the road network in a complex and changeable traffic environment by designing a parameter sharing mechanism, thereby realizing collaborative optimization control of multiple intersections. According to the invention, the cooperative control efficiency of a multi-intersection signal system is obviously improved, traffic delay is reduced, and the traffic capacity of a road network is improved.

The invention discloses an urban traffic optimization and planning system based on reinforcement learning, and relates to the technical field of computer information, and the system comprises a traffic data acquisition unit, a reinforcement learning processing unit and a traffic planning unit. The traffic data acquisition unit is used for regarding target urban traffic as a network and regarding each intersection as a node, and constructing a nonlinear traffic flow dynamic model to update a multi-dimensional tensor at each time step; the reinforcement learning processing unit is used for taking a signal timing matrix of a signal lamp of a road section between every two nodes of target urban traffic as a state space and calculating a corresponding action space when a target reward function is a maximum value; and the traffic planning unit is used for finishing the traffic planning of the target city according to the action space of each road section. According to the method, the global optimization capability, the multi-objective optimization capability, the adaptive learning capability, the data processing capability, the safety and the interpretability of traffic signal control are remarkably improved.

The invention discloses a dynamic expansion management and control method for highway accident congestion based on an ETC portal, and relates to the technical field of traffic management and control, and the method comprises the steps: obtaining accident information; calculating the queuing length of the accident scene; the congestion duration is predicted, wherein the congestion duration is composed of rescue time, obstacle clearing time and congestion dissipation time; dilatation management and control are carried out in different areas, a control area and a buffer area are sequentially divided from the accident occurrence place along the rear, and dynamic dilatation management and control are carried out according to the actual traffic capacity of the accident road section. The method has remarkable advantages in the aspects of quick response, resource adjustment, timely rescue, accurate prediction, plan making and the like, decision scientificity is improved, effectiveness of active traffic management is improved, management strategies of active traffic management are refined, scientificity and rationality of dynamic management and control measures are improved, and the method is suitable for popularization and application. The method is of great significance in improving the emergency processing capacity of the expressway and guaranteeing traffic safety and smoothness.

The invention discloses a road right sharing configuration method and a traffic control system, and relates to the technical field of special vehicle road right sharing, and the method comprises the steps: obtaining the real-time position and speed information of a common vehicle and a special vehicle at an intersection; determining the traffic flow condition of the current intersection by using a traffic flow prediction model; according to the real-time position and speed of the special vehicle and the traffic flow condition of the current intersection, the period and phase duration of the signal lamp are dynamically adjusted through a bidirectional dynamic green wave algorithm, a signal lamp control strategy is obtained, and it is ensured that the special vehicle can pass through the intersection without stopping; configuring intersection signal lamps according to the signal lamp control strategy; according to the invention, through combination of prediction of the traffic flow condition of the intersection and the real-time position of the special vehicle, the period duration and the phase duration of the signal lamp at the intersection are automatically adjusted, the influence on common vehicles at other phases is reduced as much as possible while the special vehicle is ensured to pass through the intersection without stopping, thereby realizing dynamic distribution and sharing of the road right of the special vehicle, and improving the traffic safety. And the utilization rate of special lane resources is furthest improved.

The invention discloses a traffic organization optimization method and device for road construction, and relates to the technical field of traffic organization optimization, and the method comprises the steps: carrying out the safety risk assessment and traffic flow analysis of a construction region, and obtaining construction influence data; selecting a closed mode according to the construction influence data, configuring a temporary detour route, and generating a preliminary traffic organization scheme; based on the scheme, evaluating the traffic protection capability and redistributing traffic flow, and generating a recombination scheme; performing construction restriction verification on the recombination scheme to obtain a verification scheme; and finally, executing the verification scheme to complete the traffic organization. The technical problems of traffic jam and insufficient traffic capacity caused by unreasonable traffic organization and incapability of timely evaluating and adjusting traffic flow distribution in the road construction period in the prior art are solved, and the purposes of improving the road traffic capacity and reducing the traffic load are achieved by optimizing the traffic organization in the construction period. And traffic delay and potential safety hazards caused by construction are reduced.

The invention relates to a traffic signal management technology, in particular to an intelligent traffic signal control system, which comprises a traffic data acquisition module for acquiring data of a traffic sensor in real time; the data processing module is used for analyzing the data collected by the sensor and generating an optimized signal switching strategy; the signal control module is used for controlling the state of the traffic signal lamp according to the instruction of the data processing module and automatically adjusting the signal time according to the change of the traffic flow; the cloud computing platform module is used for remotely monitoring and managing the plurality of signal control units; and the fault diagnosis and maintenance module automatically monitors the operation state of each component of the system. By acquiring the traffic flow and the pedestrian state in real time, the signal switching strategy can be intelligently analyzed and optimized, the vehicle waiting time is shortened, the traffic capacity of the intersection is improved, and the system can adjust the state of the signal lamp in time according to flow analysis and behavior pattern recognition, so that the traffic jam in the peak period is effectively relieved.

The invention discloses a traffic flow prediction and signal adjustment method based on machine learning. The method comprises the following steps: data acquisition: acquiring real-time traffic data; data processing: carrying out standardization processing on the traffic flow data and external data; machine learning model training: training the processed multi-modal data through a model; traffic flow prediction: predicting traffic flow change in a period of time in the future according to the current multi-modal data; and signal adjustment: adjusting the traffic signal of each intersection based on the predicted future traffic flow. According to the method, deep learning training is carried out on multi-modal data including traffic flow, weather, emergencies and the like, so that the model can more accurately capture the trend and rule of traffic flow change, and the prediction accuracy is remarkably improved. The system can flexibly adjust the signal period and the green light duration according to the real-time data, so that the traffic signal control has better adaptability, the instantaneous fluctuation of the traffic flow can be effectively dealt with, and the overall efficiency of the traffic system is improved.

The invention discloses a processing method for dynamically adjusting a traffic light signal scheme according to traffic flow, which comprises the following steps of: deploying sensors including a ground induction coil, a camera and a pedestrian button at each traffic intersection, and preprocessing collected traffic flow and pedestrian flow data; and predicting trends of traffic flow, non-motor vehicle flow and pedestrian flow of each intersection in a short period, modeling traffic light states of each intersection into a dynamic system, calculating an optimal traffic light adjustment strategy, and adjusting the traffic light states in real time. By dynamically adjusting the traffic light signals, the system can more effectively respond to the actual on-site conditions including the flow of pedestrians and non-motor vehicles, more reasonable signal duration distribution is achieved, waiting time is shortened, traffic efficiency is improved, meanwhile, the pedestrians and the non-motor vehicles are considered, the safety of the system can be improved through an optimized signal control strategy, and the traffic light control method is suitable for popularization and application. The signal lamp is adjusted to provide more transition time for pedestrians and non-motor vehicles, so that the accident risk is reduced.

The invention discloses a capacity expansion management and control method for predictable easily-congested road sections, and relates to the technical field of traffic management and control, historical data of each ETC portal in a near period of time on an expressway are collected, and historical traffic operation states of each road section in the monitoring range of each ETC portal are calculated; according to the historical traffic operation state of each road section, easily-congested road sections are screened, easily-congested routes are formed, and the daily average traffic volume of the easily-congested routes is calculated; and formulating a capacity expansion control strategy according to the daily average traffic volume of the easily-congested route. The method is used for solving the problems of large traffic flow and low traffic efficiency of predictable easily-congested road sections, capacity expansion can be carried out in a way of adding lanes and the like for regular and long-term easily-congested road sections so as to improve the traffic capacity, the method is a mesoscopic periodic strategy, conventional microcosmic management and control are improved to mesoscopic management and control, and the traffic efficiency is improved. Optimized configuration and efficient utilization of traffic resources can be realized, and the operation efficiency and the service level of the whole traffic system can be improved.

The invention discloses an expressway traffic flow control method, device and system, and the method comprises the steps: extracting a preset key feature from obtained historical road traffic data, and constructing a feature vector; sending the feature vector to a pre-trained traffic state prediction model, and predicting a current traffic state; the hyper-parameters of the traffic state prediction model are obtained through PSO algorithm optimization; sending the predicted current traffic state to a pre-trained control strategy model to obtain an optimal control strategy; the control strategy model is established and obtained by taking maximization of traffic flow efficiency, minimization of congestion degree and minimization of accident risk as targets. According to the method, the generalization ability and the prediction precision of the model can be improved, so that a solid technical support is provided for active control of the highway traffic flow.

The invention relates to the field of preparation of asphalt mixtures for road engineering, and discloses a water-damage-resistant high-performance asphalt mixture doped with fibers and a preparation method of the water-damage-resistant high-performance asphalt mixture. The asphalt mixture provided by the invention is a water-damage-resistant fiber-doped high-performance asphalt mixture, and the asphalt consumption and the void ratio of the asphalt mixture are in the optimal proportion; particularly, the asphalt mixture interacts with aggregate with set gradation, and basalt and polyacrylonitrile fiber are mixed for use, so that the bonding effect between the aggregate and asphalt is better, the overall compactness and water stability of the asphalt mixture are further improved, and meanwhile, other comprehensive pavement performance of the asphalt mixture is also improved; and the asphalt pavement has high-temperature stability, low-temperature bending resistance, durability and anti-skid safety, so that the traffic capacity and the service life of the asphalt pavement are enhanced, and the asphalt pavement can have good pavement performance in different water environments.

The invention provides a vehicle-mounted detecting and guiding system during advancing, and belongs to the field of vehicle control. The problem that the vehicle auxiliary driving efficiency is low is solved. Specifically, the data acquisition module acquires driving data; the positioning correction module is used for carrying out primary analysis on the driving data and correcting the position of the vehicle; the driving assistance module carries out primary adjustment on the vehicle speed; analyzing the power oil consumption change of the vehicle according to the driving data, obtaining the remaining driving time of the vehicle to the destination, and carrying out secondary adjustment on the driving speed of the vehicle; the continuous adjustment module continuously obtains driving data and destination information of the vehicle and adjusts the positioning and driving speed of the vehicle; according to the invention, the positioning and speed of the vehicle are adjusted by acquiring, analyzing and processing related data of vehicle driving, so that the vehicle is stable in driving.

The invention provides a highland cooperative automatic control method and system, and the method comprises the following steps: controlling an unmanned plane to fly to a highway section for image collection in response to a received congestion checking signal; performing image recognition on the high-speed acquired image, and determining a high-speed area and a ramp area in the high-speed acquired image; dividing the expressway area to obtain a first road section area and a second road section area which respectively indicate a road section before a ramp and a road section after the ramp, and obtaining a first congestion coefficient and a second congestion coefficient which respectively correspond to the road section before the ramp and the road section after the ramp, determining a flow attribute corresponding to the ramp section based on the first congestion coefficient and the second congestion coefficient; and in response to the traffic attribute being a congestion attribute, obtaining a vehicle lamp control device closest to the ramp road section, and controlling the vehicle lamp control device to execute a lamp control operation corresponding to vehicle passing. The traffic management efficiency is at least improved.

The present invention discloses a method for controlling and evaluating the interweaving area of ​​an urban expressway for reducing the gaming time, including using a drone to collect traffic data of the interweaving area of ​​the expressway, obtaining geometric design parameters of the interweaving area of ​​the expressway; obtaining vehicle gaming information of the interweaving area of ​​the expressway; calculating the initial capacity of the interweaving area of ​​the expressway; calculating the traffic volume of the gaming section, and performing a significance test on the traffic volume; formulating a control strategy for the interweaving area of ​​the expressway according to the geometric design parameters of the interweaving area of ​​the expressway and the significance test results of the traffic volume; simulating the control strategy, and based on the initial capacity of the interweaving area of ​​the expressway, calculating the increased capacity of the entire interweaving area of ​​the expressway due to the reduction of the vehicle gaming time. The vehicle grouping rules formulated by the present invention can realize dynamic strategy management of vehicle gaming under different circumstances, thereby reducing the vehicle gaming time and improving the road capacity.

The invention belongs to the technical field of steering pull rod design, and particularly relates to a steering pull rod mechanism design method based on analytic geometry and a steering pull rod mechanism. The steering pull rod mechanism is simplified into a plane connecting rod mechanism, and four key hinge points are marked; establishing a coordinate system by taking P1 as an original point; the length, the initial angle and the P4 coordinate of the front steering swing arm are obtained; calculating two coordinates of a P2 point when the front steering swing arm rotates to a limit position; generating P2 ''and P2'' ''points by rotating P2 'P4 and P2'' P4 line segments; and connecting the line segments and constructing perpendicular bisectors, and determining the position of a P3 point by solving the intersection point of the perpendicular bisectors. According to the method, the steering pull rod mechanism is designed through analytic geometry and coordinate transformation, the accuracy of hinge point positioning is improved, and structural deviation caused by empirical estimation is reduced; the design complexity is reduced through standardization steps, the development period is shortened, the motion coordination of the steering system is optimized, and the method is suitable for the field of automobile chassis and the like needing high-precision motion control.

The invention discloses a toll station ramp control method and device based on artificial intelligence, and a medium, and the method comprises the steps: collecting a video stream and sensor data of a to-be-controlled road segment, and carrying out the pre-processing of the video stream to determine a key frame image; analyzing the key frame image in combination with sensor data, determining traffic data and traffic influence factor values corresponding to the to-be-controlled road section, and inputting the traffic data and the traffic influence factor values into a trained traffic flow prediction model to output a pre-estimated traffic condition corresponding to a preset time period; generating a recommended planning path corresponding to the driving vehicle based on the vehicle driving demand and the estimated traffic condition which are acquired in real time, and optimizing the estimated traffic condition based on the confirmation condition of the driving vehicle on the corresponding recommended planning path; and determining a congestion level corresponding to the optimized pre-estimated traffic condition, and determining a ramp management and control strategy corresponding to the congestion level based on a preset ramp management and control library so as to perform ramp management and control on the toll station according to the ramp management and control strategy.

The invention discloses a short-distance intersection overflow control method considering dissipative overflow, and belongs to the technical field of traffic control. Microwave radar detection equipment is additionally arranged at an intersection to construct a short-distance intersection traffic data acquisition system; calculating signal timing schemes, green time ratios, traffic capacities and phase differences of upstream and downstream intersections according to the collected traffic data; calculating the maximum number of vehicles entering the overflow control direction of the downstream intersection from the upstream intersection according to the number of vehicles passing when the green light in the linkage overflow control direction of the upstream intersection and the downstream intersection is released and the maximum number of vehicles capable of being accommodated in the short-distance road section; whether the last vehicle entering the overflow control direction of the downstream intersection from the upstream intersection can enter the short-distance road section or not is judged, and the green light time and the full red time in the direction in which the upstream intersection enters the overflow control road section of the downstream intersection are dynamically controlled on the premise that traffic overflow can be dissipated; the traffic capacity between short-distance intersections is comprehensively improved while queuing vehicles at the intersections are prevented from overflowing.

The invention discloses a method and a system for optimizing an evacuation path of people in a building based on shortest global evacuation time, and relates to the field of optimization of the evacuation path of people in the building. The problems that in the prior art, a path optimization method cannot truly and accurately reflect the influence of crowd crowd on the evacuation process, and the actual condition of crowd evacuation in the crowd state cannot be reasonably considered in the path optimization process are solved. The method comprises the following steps: generating a corresponding evacuation road network model according to an architectural plan of a to-be-analyzed case; determining an evacuation personnel distribution scheme; determining a shortest-path evacuation path scheme, calculating an evacuation simulation result of the scheme, and obtaining global evacuation time and the number of the finally evacuated group; determining an optimizable evacuation group set according to a bidirectional transfer strategy; setting an initial optimization scheme; and iteratively optimizing the evacuation paths of the groups in the first optimization adjustment area and the second optimization adjustment area. And outputting a final optimized evacuation path scheme and a corresponding evacuation process simulation calculation result.

The invention relates to the technical field of electric power inspection, and particularly discloses an electric power tunnel inspection robot capable of adapting to a narrow space, which comprises a base, a rotating table mechanism arranged at the top of the base, a multi-degree-of-freedom manipulator mechanism arranged at the top of the rotating table mechanism, and a steering walking mechanism arranged on the base. According to the technical scheme, the multi-degree-of-freedom mechanical arm mechanism is arranged and used for freely adjusting the shooting position of the camera shooting mechanism, so that the multi-layer cable video inspection robot is suitable for video inspection work of tunnel multi-layer cables, and the steering walking mechanism controls separation and attachment of a friction wheel and a flywheel disc through an electric push rod; the same-speed or differential-speed operation of the crawler belts on the two sides of the steering walking mechanism can be achieved only through one motor, steering and turning-around operation of the device on a narrow tunnel is facilitated, and the traffic capacity of the device in a narrow space is improved.

The embodiment of the invention provides a vehicle lane changing control method, device and equipment, an automobile and a storage medium, and relates to the technical field of intelligent driving. The method comprises the following steps: acquiring a first space income and a second space income of a vehicle within a preset time period; the first space revenue is the revenue obtained by simulating that the vehicle runs according to a target lane changing planning track, and the target lane changing planning track is a track which is determined based on a preset dynamic planning algorithm and consumes the minimum total cost in lane changing longitudinal planning tracks at which the vehicle can change to a target position of a target lane; the second space revenue is the revenue obtained by simulating the self-vehicle to run along the target cruise planning track; determining lane changing income according to the first space income and the second space income; and controlling the own vehicle to change the lane according to the lane changing income. The method is used for achieving the effects of improving the accuracy of the lane changing decision and improving the passing efficiency of the vehicle in complex scenes such as medium and low speeds.

This invention discloses an intelligent early warning system and method for railway line patrol safety based on edge computing, involving intelligent safety early warning in the railway transportation field, enabling real-time controllable emergency measures to minimize the negative impact of incidents. The edge computing-based intelligent early warning system for railway line patrol safety includes: a cloud platform for an intelligent patrol system along the railway line, network infrastructure units for the intelligent patrol system along the railway line, on-site edge intelligent early warning devices and traffic control units, and IoT video sensing infrastructure units. This invention aims to deploy edge computers to continuously analyze 24-hour video streams from surveillance cameras at key locations along the railway line, process data in real-time, reduce latency, promptly identify abnormal events, take temporary emergency measures as quickly as possible, and rapidly report abnormal events, effectively shortening response time, significantly improving the efficiency of handling abnormal events in railway transportation, enhancing the accuracy of emergency measures, and ensuring railway line safety.

The invention discloses a main line intersection CAV special lane setting method and a self-adaptive control system in a mixed driving environment. The method comprises the following steps: collecting information in real time; according to the current CAV permeability, the traffic capacity in the trunk line direction in three different states is calculated, the maximum net income of the traffic capacity is calculated, and then lane function switching judgment conditions are set in a mode of comparing the maximum net income of the traffic capacity; the lane function switching judgment condition is used for judging whether to open or close a CAV special lane, and determining that the CAV special lane is set as a CAV full-steering special lane or a CAV straight special lane; and iteratively optimizing the generated signal control scheme by adopting a PS-PPO-based multi-agent deep reinforcement learning algorithm, and generating an optimal signal control scheme in real time. According to the invention, the hybrid lane and CAV lane functions are dynamically adjusted according to the change of the CAV permeability, the cooperative optimization of the lane functions and the signal control scheme is realized, and the traffic efficiency of the trunk line intersection is improved to the greatest extent.

The utility model discloses a kind of end small wheel supporting type mechanical arm and tracked driving platform, belong to mechanical arm technical field.The mechanical arm includes: mechanical arm base, joint arm and small wheel auxiliary support module;The joint arm is sequentially connected by rotating joint, first pitch joint, intermediate section, second pitch joint and end section;The rotating joint is arranged in the upper end surface of the mechanical arm base, relative the mechanical arm base rotates;The end section is equipped with at least one mechanical installation interface, one of which is used to install small wheel auxiliary support module to make the small wheel auxiliary support module move with joint arm;The small wheel auxiliary support module includes: support rod, small wheel and wheel shaft;One end of the support rod is machined with outwardly extending mounting base for connecting the joint arm, the other end is provided with recess;The small wheel is installed in the recess;The wheel shaft is sequentially fixed after passing through recess side, small wheel inner ring and recess other side.

The present invention relates to a control method and system for a tracked vehicle based on semantic information series connection. The method comprises fusing laser radar point cloud information and image semantic information, and determining a three-dimensional semantic grid map according to the fused information, a global topological reference path, and geometric passability parameters of the tracked vehicle; a motion planning module splices and transitions motion primitives according to the three-dimensional semantic grid map, the global topological reference path, and the extended cost of motion primitives in the motion primitive cluster; a motion control module uses a trajectory with behavioral semantic information to update the weight coefficient of the control objective function in real time, and controls the tracked vehicle based on a model predictive control algorithm according to the updated control objective function and the trajectory with behavioral semantic information under the mechanical constraints of the actuator, the kinematic constraints of the platform, and the dynamic constraints of the platform. The present invention can improve the passability of ground unmanned mobile platforms in off-road environments.

The utility model discloses a drainage pipeline large-volume garbage intercepting device for municipal engineering, which belongs to the technical field of pipeline pollution discharge and comprises a garbage collecting frame, a driving shaft is rotatably connected between the inner walls of the garbage collecting frame, and the outer wall of the driving shaft is in threaded connection with an unloading scraping strip; a discharging groove is integrally formed in one side of the top of the garbage collecting frame, an insection scraper is correspondingly arranged over the discharging groove, and a filter screen is installed on one side of the insection scraper. The filter screen is arranged at the water inlet of the pipeline, and the outer wall of the filter screen is scraped and washed by the insection scraper which moves up and down, so that any type of garbage can be washed off under the action of pressure or decomposed into garbage which is of a small part structure and cannot continue to circulate; and the garbage is collected into the garbage collecting frame by the discharging scraping strip which is rotationally scraped and washed at the bottom and the discharging groove of the fixed structure, so that the filtering and water passing effects of the filter screen are prevented from being interfered, and the passing capacity of the pipeline is further greatly improved.

The invention belongs to the field of traffic management, and particularly relates to a ramp interlacing area pavement marking adjusting method based on flow monitoring, and a corresponding device and system thereof. The design thought of the method is to pre-determine the solid line length of a middle lane and an outer lane of a main road when the optimal traffic efficiency can be achieved in a traffic scene corresponding to typical main road traffic flow and ramp traffic flow. The method comprises the steps that firstly, road traffic flow is detected in real time, the current state is matched with a typical scene, then the adjusted marking length is determined according to a matching result, a standardized value of the marking length in a road is obtained through a preset conversion function, and finally the road marking is adjusted according to the standardized value. The invention further provides related equipment for implementing the strategy. Speed reduction caused by unreasonable lane changing of vehicles in a ramp area can be weakened, the congestion degree of a main road is reduced, and the traffic capacity of the main road is improved; therefore, the device has high practical value.

The invention provides an expressway variable speed limit active control method and system, and the method comprises the steps: building a mixed traffic flow scene considering the individuation of a driver, and setting scene parameters; acquiring traffic state data of the confluence road scene in real time; training an intelligent agent by using the obtained traffic state data as a state quantity to obtain a speed limit control optimization model; different training scenes are generated by Poisson distribution in the training process; an optimal speed limit value and a proper speed limit control position are selected in each control period T, a mobile bottleneck is generated by using a mobile bottleneck variable speed limit MVSL constructed based on an intelligent network connection vehicle, and the traffic condition is optimized from the two aspects of safety and traffic efficiency by actively constructing the mobile bottleneck.

This application discloses a control method, apparatus, and self-moving device for a mobile device. The self-moving device includes a main body with a height-adjustable ranging component mounted on its top. The main body also includes a spatial information sensor. The control method for the self-moving device includes: acquiring real-time location information of the self-moving device; and controlling the lifting state of the ranging component based on historical map information and the real-time location information. The historical map information includes the location information and height information of the low-lying space. By intelligently controlling the lifting state of the ranging component using historical map information and real-time location information, the self-moving device can adapt to environments at different heights without relying on additional distance sensors, preventing the self-moving device from bumping into the ranging component when passing through low-lying spaces.

The invention discloses a cross intersection induction type all-red time calculation method. The method comprises the steps that S1, intersection linear parameters are acquired through a video detector; s2, speed information of pedestrians, non-motor vehicles and motor vehicles crossing the street is obtained through a video detector, and a speed threshold value is calculated according to the distribution frequency; s3, calculating the full-red basic duration of clearing the pedestrians, the non-motor vehicles and the motor vehicles crossing the street; s4, the crowding condition is judged, and the all-red time of pedestrians, non-motor vehicles and motor vehicles crossing the street is calculated; and S5, obtaining the final all-red time. According to the cross intersection induction type all-red time calculation method, the congestion conditions of pedestrians, non-motor vehicles and motor vehicles crossing the street are detected in real time, and the dynamic change of the traffic flow is taken into influence factors for calculation, so that the change of the induction type all-red time is realized, the accuracy of the calculated all-red time is improved, the control delay of the intersection can be reduced, and the control accuracy of the intersection is improved. The traffic flow is optimized; and the traffic jam is reduced.

The utility model discloses a material handling tractor suitable for narrow space, which comprises a bearing platform, a cavity is arranged in the bearing platform, a rotating device is arranged on one side in the cavity, two studs are arranged on the rotating device, a pushing mechanism is screwed on the studs in a threaded manner, and the pushing mechanism is arranged on the bearing platform. One end of the pushing mechanism penetrates through the side wall of the bearing table and extends to one side of the bearing table, a supporting plate is connected to one end of the pushing mechanism, folding frames are rotationally connected to the two sides of the supporting plate, one end of the folding frame on the same side is rotationally connected to one side of the bearing table, and a bearing plate is inserted into the upper end of the supporting plate. According to the utility model, adjustment can be carried out according to spaces of different specifications, the traffic capacity and adaptability of equipment in different environments are enhanced, the trouble that carrying tools are frequently replaced due to space limitation is avoided, flexible adjustment of the bearing capacity can be realized according to actual material carrying requirements, and the practicability and flexibility of the equipment are improved.