228 results about "Trunk road" patented technology

The invention relates to the technical field of new energy, and particularly discloses a new energy heavy truck energy-saving path planning method and electronic device.The new energy heavy truck energy-saving path planning method comprises the steps that a layered road network based on an energy consumption model is constructed, and the layered road network divides a road into multiple levels through a comprehensive weight formula, wherein the high-level road network comprises low-energy-consumption main roads, and the low-level road network comprises all road types; and on the basis of vehicle real-time state parameters and destination information, a two-way A algorithm is adopted to carry out path search in the layered road network, the two-way A algorithm is synchronously expanded from a starting point and an ending point, and the search direction is optimized on the basis of a dynamic heuristic function. According to the new energy heavy truck energy-saving path planning method provided by the embodiment of the invention, three major pain points of high energy consumption, difficult energy complementation and poor real-time performance in new energy heavy truck path planning are optimized and solved through modules of layered road network construction, dynamic weight adjustment, bidirectional A * algorithm optimization and the like, and the energy complementation bottleneck problem of the new energy heavy truck is solved.

The invention provides a multi-path main road signal cooperative control method considering speed fluctuation, and the method comprises the steps: firstly collecting traffic data, including road network geometric data, traffic flow data and signal control data, and determining a plurality of main paths according to the traffic flow data; then, based on the running speed of each vehicle on each main path, the vehicle running average speed and the speed fluctuation quantity on each main path are calculated; and finally, constructing a signal control optimization model: constructing a target function by taking weighted green wave bandwidth maximization of all paths as a target, adding a loop integer constraint, an interference constraint, a speed fluctuation space-time constraint, a highest speed fluctuation constraint and a lowest speed fluctuation constraint, solving the signal control optimization model, and obtaining an optimized signal period and green wave bandwidth. And outputting the optimized signal timing strategy. The signal timing generated by the method has a good prospect in the aspect of reducing travel delay and parking times, and a better multi-path collaborative effect can be realized.

The invention relates to the technical field of unmanned aerial vehicle intelligent maintenance and cleaning, in particular to an unmanned aerial vehicle-based main road camera non-closure autonomous cleaning system and method, and the system executes the following steps: an unmanned aerial vehicle hovers at the outer side of a camera, collects millimeter wave-polarization-acoustic signals to generate stain spectrum fingerprints, and obtains cleaning parameters through optimization; and the model prediction controller sequentially executes plasma, acoustic cavitation and ion air curtain dry cleaning under energy constraint, self-adjusting parameter iteration is carried out when residues exceed a threshold value, and return flight and battery replacement are carried out after the standard is reached. And the cleaning progress, the residual index and the energy consumption are packaged and chained, the cloud self-learning model updates online and outputs a next order of instruction, and non-stop, low-consumption and efficient autonomous cleaning is realized.

The invention relates to the technical field of natural gas pressure regulating station automatic site selection, and provides a natural gas pressure regulating station automatic site selection method, system, equipment and medium, and the method comprises the steps: precisely extracting a water system contour boundary through employing an edge detection algorithm, generating a water system distribution diagram, and building a terrain constraint condition through combining with a gradient grading mask; the gradient attenuation range of the water system safety buffer area is dynamically adjusted based on the river channel bending curvature characteristic and the branch intersection density, and water body protection and land use requirements are effectively balanced; recognizing boundaries of a building area and a forest protection area through color and shape features of the remote sensing image, and performing superposition to generate a composite security constraint layer; and screening low-gradient contiguous effective candidate blocks after excluding the protected area, simulating a feasible path through a depth-first search algorithm, and selecting an area which is high in connectivity with a main road and small in topographic relief as a final site. The ecological environment damage risk is reduced, the engineering implementation feasibility is ensured, and the optimal balance of ecological protection, safety protection and construction cost is achieved.

The invention is suitable for the technical field of intelligent driving regulation, and provides an intelligent traffic flow line optimized driving behavior regulation method and system, and the method comprises the steps: continuously collecting the behavior characteristic data of the following distance, lane changing frequency, accelerator stability and the like of a driver, and generating aggressive or prudent driving style DNA tags; in combination with vehicle navigation destinations and routes, a temporary motorcade containing one aggressive leader vehicle and two cautious following vehicles is established in the vehicles sharing the main road path; sending a team establishment application through the Internet of Vehicles, establishing a temporary collaborative team after confirmation of all the members, and planning an exclusive collaborative route; the leader vehicle broadcasts control instructions such as lane changing and speed changing, a vehicle team is regarded as a whole to calculate a cooperative safety space, instruction transmission intervals are dynamically set, and a unified driving strategy is generated. According to the invention, vehicle complementation and cooperation are realized, the traffic flow line is optimized, the driving behavior is adjusted, and the traffic efficiency and safety are improved.

The invention discloses an atmospheric environment monitoring and early warning method and device, and relates to the technical field of atmospheric environment monitoring and early warning, and the method specifically comprises the following steps: obtaining the traffic environment state information on a main road in real time, and evaluating the urgency degree of adjusting the data collection time interval of sensor equipment on the main road; based on evaluation and analysis results, an early warning and acquisition interval adjustment mechanism is constructed and applied, and corresponding early warning and acquisition interval adjustment measures are taken for different urgency conditions; and response feedback information of the sensor equipment on the main road is obtained in real time and analyzed after being obtained, and whether the adjustment degree of the mechanism on the data acquisition time interval of the sensor equipment on the main road meets the preset response requirement or not is evaluated. According to the invention, the problem of monitoring lag of rapid accumulation of pollutants in the traffic peak period is solved, and the technical effects of dynamically adjusting the acquisition interval and accurately triggering pollution early warning are realized.

The invention discloses a path planning method, a vehicle and electronic equipment. The method comprises the following steps: acquiring entrance and exit information of a working area and spatial orientation information of a plurality of working positions; generating a plurality of candidate paths based on the entrance and exit information and the spatial orientation information; determining a first type of trunk road based on a first type of candidate lanes in the plurality of candidate paths, and determining a second type of trunk road based on a second type of candidate lanes in the plurality of candidate paths; combining at least part of the first type of candidate lanes in each candidate path into a first type of main road, combining at least part of the second type of candidate lanes in each candidate path into a second type of main road, and generating a target path; and sending the target path to the target vehicle. According to the invention, the technical problem of poor path planning effect in related technologies is solved.

The invention relates to the technical field of traffic signal control, and discloses an arterial road variable bandwidth green wave coordination method and system for multiple critical paths, and the method comprises the following steps: obtaining real-time arterial road structure data, intersection signal timing parameters and critical path information; inputting the collected data into a pre-constructed trunk road green wave optimization model, solving the trunk road green wave optimization model, outputting optimized signal control parameters, and coordinating green waves according to the optimized signal control parameters; the trunk road green wave optimization model comprises an objective function and constraint conditions; and obtaining a target function of the trunk road green wave optimization model by taking the weighted sum of the green wave bandwidth of the maximized key path as a target. The method can be applied to an urban trunk road scene, green wave bands are provided for multiple key paths, the green wave bands can be flexibly changed in different road sections, and the traffic flow passing efficiency of the urban trunk road is improved.

The invention provides a hierarchical autonomous behavior decision and joint control method for expressway and ramp scenes, and belongs to the technical field of auxiliary driving. Comprising the steps of S1, a training stage; s1.1, collecting expert data and training an IL decision maker; s1.2, an RL control module is trained; s1.3, performing combined overall verification and fine adjustment; s2, an execution stage; s2.1, environment perception and state construction are carried out; s2.2, performing upper layer imitation learning decision making; s2.3, calling a lower layer reinforcement learning control module; s2.4, a lower layer MPC control module is called; and S2.5, vehicle execution and environment updating are carried out. According to the invention, control mode switching is more adaptive and learnable, and dependence on artificial experience is reduced; strategy flexibility and control feasibility or safety are considered; complex tasks such as highway main road lane changing, ramp confluence and ramp diversion can be processed under the same framework; according to the method, smooth and comfortable control behaviors can be generated on the premise of ensuring the safety margin.

Provided herein is technology relating to roadway design and traffic control systems and methods for connected and automated vehicle and highway (CAVH) systems, and particularly, but not exclusively, to systems and methods for controlling switching of vehicles between automated mode and human-driven mode, systems and methods for vehicle merging, diverging, and overtaking on automated lanes of multiple lane highways, systems and methods for emergency management and roadside assistance on automated lanes, and / or systems and methods for managing automated vehicle lanes on urban major and minor expressways.

The invention discloses a vehicle cooperative control method and system in a ramp confluence area scene in mixed traffic, and relates to the technical field of intelligent traffic. Comprising the following steps: constructing traffic scenes of a single-lane main road and a single-lane ramp, and designing a state space, an action space and a reward function corresponding to each agent; designing a double-delay depth deterministic strategy gradient ITD3 model, and controlling the CAV to perform two-dimensional continuous transverse driving and longitudinal driving; fusing a two-dimensional collision avoidance strategy for each agent, and constructing a KBS-ITD3 model by fusing a double-delay depth deterministic strategy gradient ITD3 model; a network model corresponding to the KBS-ITD3 model is established for training, and the trained KBS-ITD3 model is used for controlling vehicles in a ramp confluence area scene. The safety in the confluence process is greatly improved while the efficiency is guaranteed.

The invention provides a mobile charging system, and belongs to the technical field of new energy automobile charging, and the mobile charging system comprises a mobile charging pile which is provided with a first docking port and a second docking port; the aerial track comprises a plurality of main roads and a plurality of branch main roads, and the branch main roads lead to all the parking spaces; the charging position butt joint part is arranged at the tail end position of the branch trunk road, and the charging position butt joint part is provided with a first interface connected with a charging gun, a second interface connected with a power supply and a supporting part used for placing the mobile charging pile; and the mobile charging robot walks on the aerial track and is used for carrying the mobile charging pile to the supporting component and completing the butt joint of the first butt joint port and the first interface and the butt joint of the second butt joint port and the second interface. The utilization rate and the turnover rate of the charging pile can be improved.

The invention provides a path planning method, device and equipment and a readable storage medium, and the method is applied to a mobile device, and comprises the steps: obtaining a target map, dividing the target map into a plurality of sub-regions, and enabling the plurality of sub-regions to comprise a starting point region and an ending point region; determining an access point in the starting point area, and determining an outgoing point in the ending point area; a hybrid obstacle avoidance algorithm is utilized to determine an access path between the starting point and the access point and determine an outgoing path between the outgoing point and the terminal point, and the hybrid obstacle avoidance algorithm is a path planning algorithm combining a heuristic search algorithm and vehicle dynamics constraints; determining a main road path between the access point and the outgoing point by using a shortest path search algorithm; and determining a target path of the movable device based on the access path, the main road path and the access-out path. The driving requirements of the movable device can be met while the driving path is optimized.

The invention relates to a main road night construction management decision-making method, and relates to the technical field of road construction management, and the method comprises the following steps: S1, data collection and analysis: collecting construction area environment data, and using a data analysis tool to evaluate potential influences; s2, risk assessment: performing construction risk assessment based on the collected data; s3, decision model construction: establishing a multi-objective optimization model, taking construction time, cost, safety and environmental influence as decision variables, and generating an optimal construction time window and a resource allocation scheme; s4, real-time monitoring and adjustment, wherein real-time monitoring is carried out in the construction process, and the construction plan is adjusted according to real-time data; and S5, evaluation and feedback: the construction process is evaluated, scientific decision making, comprehensive risk evaluation and rapid response to emergencies can be realized through real-time monitoring, data analysis and construction management, and a construction scheme is continuously optimized through a closed-loop feedback system, so that the construction safety and efficiency are improved, and sustainable development is realized.

A road junction merging structure and a merging control system. The structure comprises a trunk road (1), an entrance ramp (2), and an exit ramp (3); the trunk road (1) is provided with a plurality of lanes, an exit taper (11) and an entrance taper (12) are sequentially formed on the outermost lane of the trunk road (1) in a driving direction, and a buffer zone (13) is arranged in the zone between the exit taper (11) and the entrance taper (12) of the outermost lane of the trunk road (1), so that the outermost lane between the exit taper (11) and the entrance taper (12) of the trunk road (1) is a non-accessible buffer lane; the exit taper (11) is connected to the exit ramp (3), and the entrance taper (12) is connected to the entrance ramp (2); a merging segment is arranged ahead of the entrance taper (12); a merging segment is arranged behind the exit taper (11). The system comprises the structure, an electronic lane change line, a lane change line regulation and control structure, a monitoring device, and a controller.

The invention provides a dynamic decision-making method and system for store site selection based on geographic information, and relates to the technical field of geographic information system.The method comprises the steps that traffic data of main roads and subway lines of a target city and geographic image information of peripheral business districts of a to-be-analyzed area in the target city are obtained; processing the geographic image information to obtain a physical boundary range and business state distribution information of a peripheral business district, and calculating traffic reachability parameters in combination with traffic data; determining a preliminary candidate area in the physical boundary range, and obtaining a cooperative potential parameter according to the traffic reachability parameter; selecting a candidate store area position from the preliminary candidate area based on the traffic reachability parameter and the cooperative potential parameter; according to surrounding dynamic factors, the candidate store area positions are evaluated to determine the final store site selection, so that the accurate, intelligent and dynamic decision-making of the store site selection is realized, and the scientificity and the commercial success rate of the site selection are improved.

Disclosed in the present invention is a path planning method for an unmanned forklift. The method comprises: step 1, drawing a feasible area for an unmanned forklift on a constructed grid map, moving the unmanned forklift to record coordinates of stations, and automatically generating a topological map consisting of nodes and edges; step 2, setting a starting point and a destination point for planning, and on the basis of cost weights of all the edges in the topological map, searching for an optimal route; and step 3, driving the unmanned forklift to move along the planned optimal route. In the path planning method for an unmanned forklift of the present invention, a topological map required for a path search is automatically generated, without the need for manual drawing, thereby increasing the efficiency; different attributes of a route are automatically set on the basis of a task type, an operation area, etc., such that the method is more applicable to unmanned forklifts; and if it is not possible to make a U-turn due to insufficient space on a main road, another feasible area can be used to complete the U-turn, thereby increasing the flexibility.

The application discloses a biomass collection, storage and transportation site optimization method, and belongs to the technical field of biomass energy utilization and space optimization. The method comprises the following steps: acquiring biomass site data and trunk road information of a preset area, constructing a biomass distribution matrix of the preset area by means of geographical coordinates and density of the biomass site, setting weights of corresponding sites based on biomass density, clustering and reducing dimensions of the distribution matrix by means of the weights, and outputting a preset number of candidate site sets of biomass collection and storage stations; generating an address combination containing a preset number of optimal biomass collection and storage stations based on the candidate site sets of the biomass collection and storage stations; generating a candidate site set containing a preset number of biomass power plants along a line by means of the trunk road information; generating an address combination containing a preset number of optimal biomass power plants based on the candidate site set of the biomass power plants; and the method can accurately and economically determine an optimal address combination of biomass collection, storage and transportation in the preset area.

The invention relates to the technical field of expressway operation management / traffic big data, and provides a freight transport transfer demand prediction method under a differentiated charging policy, and the method comprises the steps: obtaining the GPS track data of a truck, and carrying out the data preprocessing of the GPS track data, and obtaining effective GPS track data; carrying out stop point discrimination on the preprocessed effective GPS track data by adopting a judgment method of combining time sequence DBSCAN clustering with a stop interval, identifying and dividing different travel segments, and constructing a complete truck travel chain; based on a trip chain, identifying the flow of each sample road section through road section matching, and expanding the obtained flow of each sample road section to the flow of the whole sample road section through observation station data and portal frame data of parallel national and provincial trunk roads and expressways; and performing parameter calibration on the constructed travel path selection behavior model by using the flow of the whole sample road section subjected to sample expansion, and predicting the expressway freight transfer traffic demand by using the model based on the adjusted differentiated rate.

The invention discloses a travel traffic road condition evaluation planning system based on fusion processing. The travel traffic road condition evaluation planning system comprises a multi-source data acquisition engine, a data fusion preprocessing unit, a road condition state fusion evaluation unit, a short-time prediction evolution unit, an intelligent path planning unit and a coordination signal optimization unit, according to the method, historical and real-time dual-mode prediction verification channel and regional coordination signal control feedback is established, a road network state evolution trend decoupling stability quantitative model is used for driving a planning decision, road average delay in peak periods in typical urban road network tests is decreased, the traffic capacity of main roads is improved, the response time of extreme meteorological events is shortened, and the reliability of the urban road network is improved. The road condition evaluation precision is improved through heterogeneous data fusion and dynamic rule engine coupling, a multi-source data acquisition engine is coupled with environmental data in real time, and signal noise interference is inhibited through a credibility weighting mechanism in a data fusion preprocessing unit.

The invention relates to the technical field of traffic flow management and control, and discloses a road congestion analysis management and control method, which comprises the following steps: S01, acquiring historical road congestion data through an expert platform to obtain a plurality of driving roads; s02, carding the plurality of driving roads at the same time to obtain a main road in each driving road and set data about a plurality of entrance node roads along the main road; and S03, generating a corresponding data acquisition chain according to the number of the set data, and continuously acquiring the road condition data of the current driving road based on the data acquisition chain. The method comprises the following steps: acquiring historical road congestion data, carding a main road and an entrance node road of a driving road, continuously acquiring road condition data at the current moment and the next moment, predicting future driving-in expected time of a vehicle entering the main road, and determining the traffic congestion of the vehicle on the basis of main road traffic flow reasonable capacity parameters, congestion occurrence time and elimination time. And generating a waiting duration prolonging mechanism of the traffic signal lamp.

The invention provides a vehicle congestion detection method and device, equipment and a storage medium. Comprising the steps of obtaining a current frame detection frame picture based on a current frame monitoring picture; the current frame detection frame picture comprises a plurality of target detection frames; performing clustering analysis on the plurality of target detection frames by adopting a preset distance clustering strategy to obtain a preprocessing clustering result; the preset distance clustering strategy is a strategy for clustering distances between adjacent vehicles; the vehicle corresponding to the pre-processing detection frame identifier may be a congested vehicle; tracking the vehicles in the possible congestion state to obtain a next frame of detection frame picture corresponding to the vehicles in the possible congestion state, and determining a secondary clustering result of a moment corresponding to the next frame of detection frame picture based on a preset position and direction clustering strategy and a preset distance clustering strategy; the preset position and direction clustering strategy is a strategy for clustering the driving position and direction of each vehicle; and determining that the vehicles on the trunk road are in a congested state based on a secondary clustering result and a preset time length.

The invention relates to the field of asphalt mixtures, in particular to an anti-rutting asphalt mixture and a preparation method thereof, which are used for solving the problems that the existing asphalt mixture is poor in rutting resistance and low-temperature crack resistance, and the driving safety, comfort and service life of a pavement are seriously influenced. According to the preparation method, by adding the coated basalt fiber and the organic silicon grafted epoxy resin into the asphalt mixture, a highly crosslinked network structure can be formed in the asphalt mixture, and the asphalt mixture has very high mechanical strength and toughness, so that the rutting resistance of the asphalt mixture can be remarkably improved, and the low-temperature crack resistance of the asphalt mixture is synchronously and remarkably improved. Therefore, the fatigue damage of the road surface can be effectively reduced, the service life of the road can be prolonged, the driving comfort can be improved, and the use quality and safety of the road surface can be optimized on the road sections with frequent traffic, such as expressways and main roads.

The invention relates to the technical field of traffic signal control, and provides a traffic accident surrounding traffic signal response method and system, and the method comprises the steps: obtaining main road traffic flow parameters and secondary road exit vehicle existence information; judging whether the trunk road is in a trunk road congestion state or not; judging whether the secondary road is in a secondary road exit abnormal retention state or not; identifying a key exit passive blocking event; a control instruction is sent to an upstream intersection of the target intersection corresponding to the key exit passive blocking event, so that the upstream intersection of the target intersection controls a main road direction signal lamp to be red, and a traffic gap is created; turning the signal lamp in the main road direction of the target intersection into green light, and emptying vehicles in the main road area in front of the key exit of the secondary road; after it is confirmed that the vehicle is emptied, the vehicle at the key exit is released; and after the release is completed, judging that the emergency condition is relieved and recovering traffic signal control. The method has the advantage of avoiding traffic delay and potential public safety risks.

The invention discloses a green wave coordination control method and device and electronic equipment, and belongs to the technical field of traffic. The method comprises the steps that operation constraint conditions and coordination directions of all intersections on a trunk road are determined, a trunk road coordination control scheme meeting the coordination directions of all the intersections is determined under the operation constraint conditions, and the coordination control scheme at least comprises signal timing schemes of all the intersections on the trunk road; for any intersection on the trunk road, the signal timing scheme of the intersection is optimized through the optimization function; and controlling the intersection according to the optimized signal timing scheme so as to realize green wave coordination control of the trunk road. According to the invention, the control effect of green wave coordination control on the trunk road is improved.

The invention discloses a multi-type intersection mixed traffic control method based on multi-agent reinforcement learning, and the method comprises the steps: setting CAV special lanes and common lanes for different types of intersections, and configuring different signal lamp phases for all types of intersections; a double-layer control structure is constructed, an upper-layer controller selects an optimal signal phase by adopting a multi-agent reinforcement learning algorithm according to the state information of each intersection, and the signal lamp state of each intersection is dynamically adjusted; and when the CAV special phase is activated, the lower-layer controller adopts a reinforcement learning algorithm to carry out passing right distribution and cooperative control on the CAV on the CAV special lane, and carries out speed guidance and track cooperation on the CAV fleet. By constructing a double-layer control framework and fusing a collaborative decision-making mechanism of multi-agent reinforcement learning, the green wave passing time of vehicles on a main road is prolonged, and the passing efficiency is improved; the overall throughput of a road network is improved, and the bearing and dispersion capabilities of a regional traffic system are enhanced.

The present application provides a touch electrode structure and a touch display panel, wherein the touch electrode structure comprises: a plurality of first touch electrodes arranged in parallel, including a plurality of first main track electrodes connected end to end and continuously conducting along a first direction, branch electrodes connected to the first main track electrodes, the branch electrodes including a first branch portion connected to the first main track electrode, and a second branch portion cross-connected with the first branch portion; a plurality of second touch electrodes arranged in parallel, arranged around the first touch electrodes and electrically insulated from the first touch electrodes, including a plurality of second main track electrodes connected end to end and continuously conducting along a second direction; a first hollow portion is arranged in at least one branch electrode, or / and a second hollow portion is arranged in at least one second touch electrode, and the second hollow portion is arranged outside the second main track electrode. The parasitic capacitance between the touch electrode and the cathode is reduced, the scanning frequency of the touch electrode is increased, and a high reporting rate of the touch screen is achieved.

The utility model relates to the technical field of intelligent traffic, in particular to an intelligent traffic signal lamp device at a level crossing. Comprising side weighing sensing devices installed at level crossings on the two sides of a main road, a middle weighing sensing device is installed at the white straight line in the middle of the main road, button rods are arranged on one side of the side weighing sensing devices and one side of the middle weighing sensing device respectively, and control buttons are arranged on the button rods. The side weighing sensing devices, the middle weighing sensing device and the control button are respectively connected with the control device, the control device is in signal connection with traffic lights arranged at the level crossing, and the control device controls signal conversion of the traffic lights according to signals of the weighing sensors and the control button. The control device can accurately control the signal lamp, pedestrians can safely cross the road, potential safety hazards are eliminated, if the control device does not receive signals of the weighing sensor and the control button for a long time, green light passing is continuously kept on the main road, and therefore the passing efficiency of the main road is improved.

The present invention discloses an emergency traffic dispatching management method and system based on drone surveillance, which relates to the technical field of traffic management control. It includes determining the emergency traffic location within the urban arterial road area based on traffic image data, and planning the driving data of the target object within the urban arterial road area according to the emergency traffic location. By collecting the image data of the target object at different positions within the urban arterial road area by the drone and combining the time intervals between the image data at different positions, the drone can locate the position of the target object and enable the communication device of the public transportation interacting with the target object to connect to the command channel with the drone, so that the drone can send regulation commands to the public transportation communication device in stages based on the position of the target object and the position of the drones, thereby realizing a rapid response and precise dispatching to the emergency traffic situation and ensuring the efficiency of traffic dispatching.

To easily achieve toll processing such as toll collection by various toll systems according to a route even for a large-scale toll road network.SOLUTION: A toll processing system includes first and second area management devices, entrance and exit tollgate apparatuses, a plurality of route apparatuses, and a barrier apparatus. The first and second area management devices correspond to a first or second area, and manages the first or second area by dividing it into a plurality of zones. The entrance or exit tollgate apparatuses correspond to each entrance tollgate or each exit tollgate. The plurality of route apparatuses correspond to routes, respectively, and transmit passage route information indicating that a vehicle has passed a main line road connected to a predetermined main line branch. The first area management device receives the passage route information to calculate a first toll to transmit it to the corresponding exit tollgate apparatus. The barrier apparatus transmits area straddling information. The first area management device calculates a second toll on the basis of the area straddling information to transmit takeover information including the second toll to the second area management device.SELECTED DRAWING: Figure 2