WO2018232897A1 - 一种在雾霾天智能行驶的方法及装置 - Google Patents
一种在雾霾天智能行驶的方法及装置 Download PDFInfo
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- WO2018232897A1 WO2018232897A1 PCT/CN2017/096970 CN2017096970W WO2018232897A1 WO 2018232897 A1 WO2018232897 A1 WO 2018232897A1 CN 2017096970 W CN2017096970 W CN 2017096970W WO 2018232897 A1 WO2018232897 A1 WO 2018232897A1
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- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/16—Anti-collision systems
- G08G1/166—Anti-collision systems for active traffic, e.g. moving vehicles, pedestrians, bikes
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- the invention relates to the technical field of safety control, in particular to a method and a device for intelligent driving in a haze day.
- the present invention provides a method and apparatus for intelligent driving in a haze day.
- the present invention provides a method of intelligent driving in a haze day, the method comprising:
- At least one of the two adjacent vehicles is alerted to adjust the current traveling speed.
- An embodiment of the present invention provides a method for intelligent driving in a haze day, each of which transmits current location information and speed information to a server through an in-vehicle terminal. After the server collects this information, it can use this information to determine which vehicles are adjacent. And easily calculate the distance between two adjacent cars, as well as the coefficient of collision risk. If the risk factor of the collision is too large, promptly remind the user to adjust the speed of the vehicle. In this way, even in the case of smoggy weather and low visibility, the driver master does not need to worry about a traffic accident, as long as the broadcast is sent according to the server. Prompt message, you can drive normally. Through the above method, it can be ensured that the vehicle can safely travel in smog weather, and the occurrence of traffic accidents is greatly avoided.
- the method further includes:
- a further advantageous effect of the above is that in order to reduce the amount of computing data of the server, it is possible to divide according to the area.
- a vehicle in the same area is responsible for calculating the risk factor of collision between two adjacent vehicles by a server.
- two adjacent vehicles one of which is located in one area and the other in the other adjacent area
- the location information of one of the vehicles is sent to another area, and then the server in the other area is responsible for calculating the risk factor of the collision between the two. And when the risk coefficient is large, promptly remind.
- the present invention provides an apparatus for intelligent driving in a haze day, the apparatus comprising:
- a receiving unit configured to receive vehicle traveling speed information and current position information of the vehicle respectively sent by the vehicle-mounted terminals of each of the plurality of vehicles;
- a processing unit configured to determine a distance between two adjacent vehicles according to current location information of the vehicle respectively sent by the vehicle-mounted terminal of each of the plurality of vehicles;
- the reminding unit is configured to remind at least one of the two adjacent vehicles to adjust the current traveling speed when the risk coefficient is greater than the preset risk threshold.
- each of the vehicles transmits the current location information and speed information to the server through the vehicle-mounted terminal.
- the processing unit can determine which vehicles are adjacent according to the information. And easily calculate the distance between two adjacent cars, as well as the coefficient of collision risk. If the risk factor of the collision is too large, promptly remind the user to adjust the speed by the reminder unit. In this case, even in the case of smoggy weather and low visibility, the driver master does not need to worry about a traffic accident, as long as the server is followed.
- the broadcast prompt message sent can be driven normally.
- the device further includes: a sending unit, configured to transmit current position information and moving speed of each of the adjacent two vehicles to the two different areas when the two adjacent vehicles are respectively located in two different areas One of the areas, so that the server in the area can calculate the risk factor of collision between two adjacent vehicles based on the current position information of each of the adjacent two vehicles and the moving speed.
- a sending unit configured to transmit current position information and moving speed of each of the adjacent two vehicles to the two different areas when the two adjacent vehicles are respectively located in two different areas One of the areas, so that the server in the area can calculate the risk factor of collision between two adjacent vehicles based on the current position information of each of the adjacent two vehicles and the moving speed.
- a further advantageous effect of the above is that in order to reduce the amount of computing data of the server, it is possible to divide according to the area.
- a vehicle in the same area is responsible for calculating the risk factor of collision between two adjacent vehicles by a server.
- two adjacent vehicles one of which is located in one area and the other in the other adjacent area
- the sending unit in the device of the smoky day intelligent driving will inform the location of one of the cars
- the message is sent to another area, and then the server in the other area is responsible for calculating the risk factor of the collision between the two. And when the risk coefficient is large, promptly remind.
- FIG. 1 is a schematic structural diagram of a system for intelligent driving in a haze day according to an embodiment of the present invention
- FIG. 2 is a schematic diagram of a signaling flow of a method for data transmission between components in a system for intelligent driving in a haze day according to an embodiment of the present invention
- FIG. 3 is a schematic flowchart of a method for intelligent driving in a haze day according to an embodiment of the present invention
- FIG. 4 is a schematic flow chart of another method for intelligent driving in a haze day according to an embodiment of the present invention.
- FIG. 5 is a schematic flowchart of another method for intelligent driving in a haze day according to an embodiment of the present invention.
- FIG. 6 is a schematic structural diagram of an apparatus for intelligently driving in a haze day according to an embodiment of the present invention
- FIG. 7 is a schematic structural diagram of an apparatus for intelligently driving in a haze day according to an embodiment of the present invention.
- FIG. 1 is a system architecture diagram of intelligent driving in a haze day according to an embodiment of the present invention.
- the system includes at least an in-vehicle terminal 10, a base station 20, and a server 30.
- the in-vehicle terminal 10 establishes a communication connection through the base station 20 and the server 30.
- the in-vehicle terminal 10 is for transmitting a data signal and receiving a control command transmitted by the server 30.
- the number of base stations 20 and the number of servers 30 are both at least one. In the same area, one or more base stations may be included. In order to reduce the amount of computing data of the server, each area may be configured with one server 30, or multiple areas may be configured with the same server 30. Or, if the area is too large, multiple servers 30 can serve the area at the same time. How to set it up, there is no limit here.
- the in-vehicle terminal 10 can establish a communication connection between the base station 20 and the server 30 by using one or more communication technologies of 3G to 5G, IPv4, IPv6, and GPRS. Alternatively, a communication connection is established between the server 30 and other communication technologies. There are no restrictions here.
- the base station 20 receives the vehicle travel speed information of each of the plurality of vehicles and the current position information of the vehicle. These parameter information are forwarded to the server 30.
- the server 30 determines the distance between the adjacent two vehicles based on the current position information of the vehicle transmitted by the in-vehicle terminal 10 of each of the plurality of vehicles.
- the base station 20 transmits prompt information to the adjacent two vehicle-mounted terminals 10 in the form of data transmission or broadcast, and reminds at least one of the two adjacent vehicles to adjust the current traveling speed.
- FIG. 2 is a schematic diagram of a signaling flow of a method for data transmission between components in a system for intelligent driving in a haze day according to an embodiment of the present invention.
- Step 1 The first in-vehicle terminal sends a first data transmission request to the base station, and the second in-vehicle terminal sends a second data transmission request to the base station, where the data transmission request includes the data size to be transmitted.
- Step 2 assign scheduling resources to the first in-vehicle terminal and the second in-vehicle terminal, respectively;
- the base station may, according to the data transmission request sent by the first in-vehicle terminal and the second in-vehicle terminal, The first in-vehicle terminal transmits a first scheduling resource for data transmission, and transmits a second scheduling resource for data transmission to the second in-vehicle terminal.
- Step 3 The first in-vehicle terminal transmits the first data to the base station on the basis of the first scheduling resource, and the second in-vehicle terminal transmits the second data to the base station on the basis of the second scheduling resource.
- the first in-vehicle terminal loads the first data into the first scheduling resource, and then sends the first data to the base station.
- the second in-vehicle terminal loads the second data onto the second scheduling resource, and then sends the second data to the base station.
- the first data includes the current traveling speed and current position information of the vehicle to which the first in-vehicle terminal belongs.
- the second data includes the current traveling speed and current position information of the vehicle to which the second in-vehicle terminal belongs.
- Step 4 After receiving the first data sent by the first in-vehicle terminal and the second data sent by the second in-vehicle terminal, the base station forwards the first data and the second data to the server.
- Step 5 After receiving the first data and the second data, the server parses the first data and the second data respectively.
- the associated vehicle traveling speed information and the current position information of the vehicle transmitted by the first vehicle-mounted terminal, and the associated vehicle traveling speed information and the current position information of the vehicle transmitted by the second vehicle-mounted terminal are read.
- Step 6 The server determines, according to the first data sent by the first in-vehicle terminal and the second data sent by the second in-vehicle terminal, a distance between the vehicle to which the first in-vehicle terminal belongs and the vehicle to which the second in-vehicle terminal belongs.
- Step 7 The server calculates the speed of the adjacent two vehicles according to the distance between the vehicle to which the first vehicle-mounted terminal belongs and the vehicle to which the second vehicle-mounted terminal belongs, the speed information of the vehicle to which the first vehicle-mounted terminal belongs, and the speed information of the vehicle to which the second vehicle-mounted terminal belongs. The risk factor for collisions between them.
- Step 8 When the server determines that the risk coefficient is greater than the preset risk threshold, reminding at least one of the two adjacent vehicles to adjust the current traveling speed.
- the adjacent two vehicles are the vehicles to which the first in-vehicle terminal belongs and the vehicle to which the second in-vehicle terminal belongs in the present embodiment.
- the current position and speed information of each vehicle and the like are acquired in real time, and the distance between adjacent vehicles is judged. Therefore, the risk coefficient of the vehicle collision is judged, and if the risk coefficient is relatively large, the speed of the adjacent two vehicles is adjusted. That is to say, even if there is too much smog between two adjacent vehicles, the presence of the other party cannot be seen, or the distance between the other party and itself cannot be distinguished, or the speed of the other party cannot be judged, etc. Will receive a reminder message sent by the server, and will not cause the vehicle to collide. Thereby reducing the occurrence of traffic accidents and avoiding unnecessary personal injury and property damage.
- an embodiment of the present invention provides a schematic flow chart of a method for intelligent driving in a haze day. Specifically, as shown in FIG. 3, the method includes:
- Step 310 Receive vehicle travel speed information and current position information of the vehicle respectively sent by the vehicle-mounted terminals of each of the plurality of vehicles.
- the in-vehicle terminal of each of the plurality of vehicles respectively transmits the traveling speed information of the vehicle and the current position information of the vehicle to the server through the base station.
- Step 320 Determine a distance between two adjacent vehicles according to the current location information of the vehicle respectively sent by the vehicle-mounted terminals of each of the plurality of vehicles.
- the statistical process may include front and rear distances and left and right distances.
- Step 330 Calculate a risk factor of collision between two adjacent vehicles according to a distance between two adjacent vehicles and information about each of the two adjacent vehicles.
- the judgment at this time may be relatively simple. As long as the distance between the two adjacent vehicles is less than or equal to the preset safety distance, the user is reminded to change the driving direction slightly, and try to ensure that the two vehicles are adjacent to each other. There is a safe distance between them.
- Step 340 when the risk coefficient is greater than the preset risk threshold, reminding at least one of the two adjacent vehicles to adjust the current traveling speed.
- the server needs to consider the current traveling speed of the two adjacent vehicles, and also considers the current traveling speed of the adjacent other vehicles. Therefore, it may be necessary to adjust only the current travel speed of one of the vehicles, or it may be that the current travel speeds of the two adjacent vehicles need to be adjusted.
- the relative driving speed of the two vehicles is at least a preset relative traveling speed.
- the invention provides a method for intelligent driving in a haze day, and the server receives the vehicle through real time.
- the reminder message sent by the server will not cause the vehicle to collide. Thereby reducing the occurrence of traffic accidents and avoiding unnecessary personal injury and property damage.
- the embodiment of the invention further provides another schematic diagram of a method for intelligent driving in a haze day, as shown in FIG. 4, the method includes:
- Step 410 Receive vehicle travel speed information and current position information of the vehicle respectively sent by the vehicle-mounted terminals of each of the plurality of vehicles.
- the in-vehicle terminal of each of the plurality of vehicles respectively transmits the traveling speed information of the vehicle and the current position information of the vehicle to the server through the base station.
- Step 420 Determine a distance between two adjacent vehicles according to the current location information of the vehicle respectively sent by the vehicle-mounted terminals of each of the plurality of vehicles.
- the statistical process may include front and rear distances and left and right distances.
- Step 430 Calculate a risk coefficient of collision between two adjacent vehicles according to a distance between two adjacent vehicles and information about each of the two adjacent vehicles.
- the judgment at this time may be relatively simple. As long as the distance between the two adjacent vehicles is less than or equal to the preset safety distance, the user is reminded to change the driving direction slightly, and try to ensure that the two vehicles are adjacent to each other. There is a safe distance between them.
- step a the inter-vehicle time interval is calculated according to the moving speed of the first vehicle and the distance between the first vehicle and the second vehicle.
- step b the relative speed is calculated according to the moving speed of the first vehicle and the moving speed of the second vehicle.
- Step c calculating the pre-collision time according to the relative speed, the distance between the first vehicle and the second vehicle.
- step d the risk coefficient of collision between two adjacent vehicles is calculated according to the time interval of the workshop and the pre-crash time.
- the inter-vehicle time interval is calculated according to the distance between the first vehicle and the second vehicle according to the moving speed of the first vehicle:
- t1 is the inter-vehicle time interval
- v1 is the moving speed of the first vehicle
- s is the distance between the first vehicle and the second vehicle.
- the pre-collision time is calculated based on the relative speed and the distance between the first vehicle and the second vehicle:
- t2 is the pre-crash time
- s the distance between the first vehicle and the second vehicle
- v is the relative speed between two adjacent vehicles.
- the risk factor of collision between two adjacent vehicles is calculated according to the shop time interval t1 and the pre-collision time t2.
- Equation 1-4 the formula for calculating the risk coefficient of collision between two adjacent vehicles according to the shop time interval t1 and the pre-collision time t2 can be expressed by Equations 1-4:
- f is the risk coefficient of collision between two adjacent vehicles; the weight coefficient corresponding to the shop time interval t1; and the weight coefficient corresponding to the pre-collision time t2.
- the inter-vehicle time interval is the time when the first vehicle reaches the current position of the second vehicle according to the moving speed of the first vehicle.
- the pre-collision time refers to the time when the first vehicle will collide with the second vehicle according to the distance between the two if the moving speeds of the first vehicle and the second vehicle do not change.
- the workshop time interval indicates the degree of influence on the pre-collision time if the moving speed of the preceding vehicle changes. That is, if the moving speed of the preceding vehicle changes, if the moving speed of the rear vehicle does not change, the relative speed will change. Correspondingly, the pre-collision time will change. The smaller the pre-collision time, the greater the likelihood of collision between two adjacent vehicles. Therefore, when calculating the risk factor of collision between two adjacent vehicles, it is necessary to consider both the shop time interval and the pre-collision time. Multiply the two by the corresponding weight coefficients and do the sum. Finally, the risk factor of collision between two adjacent vehicles is obtained.
- Step 440 When the risk coefficient is greater than the preset risk threshold, alerting at least one of the two adjacent vehicles to adjust the current traveling speed.
- the server needs to consider the current travel speed of two adjacent vehicles, while also taking into account the current travel speed of other adjacent vehicles. Therefore, it may be necessary to adjust only the current speed of one of the vehicles. It may also be that the current driving speed of two adjacent vehicles needs to be adjusted.
- the relative driving speed of the two vehicles is at least a preset relative traveling speed.
- the server receives the position information of the belonging vehicle and the vehicle traveling speed information transmitted by the vehicle-mounted terminal in real time, and determines whether the adjacent vehicles are between the two vehicles according to the two parameters. Safe driving, whether the risk factor of collision is too large, and so on. If the risk factor of the collision is too large, then at least one of the two adjacent vehicles is alerted to adjust the current speed. Therefore, even if there is too much smog between two adjacent vehicles, the presence of the other party cannot be seen, or the distance between the other party and itself cannot be distinguished, or the speed of the other party cannot be judged, etc., as it will be received. The reminder message sent by the server will not cause the vehicle to collide. Thereby reducing the occurrence of traffic accidents and avoiding unnecessary personal injury and property damage.
- the concentration of the smog can also be considered as one of the parameters when calculating the risk coefficient.
- FIG. 5 is a schematic flowchart of another method for intelligent driving in a haze day according to an embodiment of the present invention.
- the method includes:
- Step 510 Receive vehicle travel speed information and current position information of the vehicle respectively sent by the vehicle-mounted terminals of each of the plurality of vehicles.
- the in-vehicle terminal of each of the plurality of vehicles respectively transmits the traveling speed information of the vehicle and the current position information of the vehicle to the server through the base station.
- Step 520 Determine a distance between two adjacent vehicles according to the current location information of the vehicle respectively sent by the vehicle-mounted terminals of each of the plurality of vehicles.
- the statistical process may include front and rear distances and left and right distances.
- Step 530 Receive a smog concentration in the current air respectively sent by the vehicle-mounted terminals of each of the plurality of vehicles.
- the vehicle terminal of each vehicle can collect the smog in the current air and detect the smog concentration.
- the haze concentration information and the vehicle travel speed information and the current position information of the vehicle are then simultaneously transmitted to the server or separately to the server. After the server receives these three parameters, step 540 is performed.
- Step 540 comprehensively calculate a risk coefficient of collision between two adjacent vehicles according to the workshop time interval, the pre-crash time, and the smog concentration.
- the judgment at this time may be relatively simple. Some, as long as the distance between the two adjacent vehicles is less than or equal to the preset safety distance, the user is reminded to change the driving direction slightly, and try to ensure a safe distance between the two adjacent vehicles.
- steps a to c are the same as in the previous embodiment, and are not described herein again.
- the only difference is step d.
- step d the risk coefficient of collision between two adjacent vehicles is calculated according to the workshop time interval, the pre-crash time, and the haze concentration.
- the inter-vehicle time interval is calculated according to the distance between the first vehicle and the second vehicle according to the moving speed of the first vehicle:
- t1 is the inter-vehicle time interval
- v1 is the moving speed of the first vehicle
- s is the distance between the first vehicle and the second vehicle.
- the pre-collision time is calculated based on the relative speed and the distance between the first vehicle and the second vehicle:
- t2 is the pre-crash time
- s the distance between the first vehicle and the second vehicle
- v is the relative speed between two adjacent vehicles.
- Equation 2-4 The formula for calculating the risk factor of collision between two adjacent vehicles according to the shop time interval t1, the pre-collision time t2, and the haze concentration C can be expressed by Equation 2-4:
- f is a risk coefficient of collision between two adjacent vehicles; a weight coefficient corresponding to the shop time interval t1; a weight coefficient corresponding to the pre-collision time t2, which is a weight coefficient corresponding to the smog concentration C, and .
- the inter-vehicle time interval is the time when the first vehicle reaches the current position of the second vehicle according to the moving speed of the first vehicle.
- the pre-collision time refers to the time when the first vehicle will collide with the second vehicle according to the distance between the two if the moving speeds of the first vehicle and the second vehicle do not change.
- the workshop time interval indicates the degree of influence on the pre-collision time if the moving speed of the preceding vehicle changes. That is, if the moving speed of the preceding vehicle changes, if the moving speed of the rear vehicle does not change, the relative speed will change.
- the pre-collision time will be sent Health changes. The smaller the pre-collision time, the greater the likelihood of collision between two adjacent vehicles. The greater the concentration of smog, the more blurred the state of the user seeing the outside of the car. As a result, because the degree of smog is too high, even if the vehicle may be in danger of collision, the user will not be prepared.
- Step 550 When the risk coefficient is greater than the preset risk threshold, alerting at least one of the two adjacent vehicles to adjust the current traveling speed.
- the server needs to consider the current travel speed of two adjacent vehicles, while also taking into account the current travel speed of other adjacent vehicles. Therefore, it may be necessary to adjust only the current travel speed of one of the vehicles, or it may be that the current travel speeds of the two adjacent vehicles need to be adjusted.
- the relative driving speed of the two vehicles is at least a preset relative traveling speed.
- the method for intelligent driving in the haze day not only considers the speed information between adjacent vehicles, but also the position information of each of the adjacent two vehicles, and comprehensively considers Parameters such as smog concentration. Through these three parameters, the risk coefficient of the collision between two adjacent vehicles can be determined, and the accuracy can be added. Furthermore, the driving safety of the user in the smog weather is further ensured. It avoids the increase of traffic accidents caused by haze weather, reduces the risk of unnecessary vehicle collisions, and reduces personal injury and property damage.
- each of the steps may include a step A to B, as shown in FIG. 3-5. Show.
- Step A determining an area to which the current location of each of the plurality of vehicles belongs.
- step B in the same area, the risk coefficient of collision between two adjacent vehicles is calculated.
- one or more servers are placed in each area. Used to deal with the risk of collision between two adjacent vehicles in the area.
- the method further includes:
- the server in one of the areas can receive the edge area of the other area Location and speed information.
- the server of another area needs to transmit the location information and speed information of the vehicle in the edge area to the adjacent area in real time.
- the adjacent areas are used to calculate the risk factor between two adjacent vehicles belonging to different areas.
- the program is not only applicable to smog weather.
- the program can also be applied to heavy rains, such as excessive rainfall, which also causes the user to see the road outside the car in the car is blurred. Or ordinary sunny weather is also applicable.
- the traffic accident can be reduced by promptly reminding the “newbie” or less experienced users and adjusting the speed of the vehicles adjacent to them. The situation has happened. Guarantee personal safety and property damage.
- FIG. 6 is a schematic structural diagram of an apparatus for intelligently driving in a haze day according to an embodiment of the present invention. As shown in FIG. 6, the apparatus includes: a receiving unit 601, a processing unit 602, and a reminding unit 603.
- the receiving unit 601 is configured to receive vehicle traveling speed information and current position information of the vehicle respectively sent by the vehicle-mounted terminals of each of the plurality of vehicles.
- the in-vehicle terminal of each of the plurality of vehicles respectively transmits the traveling speed information of the vehicle and the current position information of the vehicle to the server through the base station.
- the receiving unit 601 in the server is used for the parameter information transmitted by the in-vehicle terminal.
- the processing unit 602 is configured to determine a distance between two adjacent vehicles according to the current location information of the vehicle respectively sent by the in-vehicle terminal of each of the plurality of vehicles. Calculating the risk factor of collision between two adjacent vehicles based on the distance between two adjacent vehicles and the speed information of each of the two adjacent vehicles
- the processing unit 602 first counts the current location information of the vehicle respectively sent by the in-vehicle terminal of each vehicle, and further confirms the distance between two adjacent vehicles.
- the statistical process may include front and rear distances and left and right distances.
- the processing unit 602 determines whether there is a risk of collision in two adjacent vehicles, it is more focused on determining the risk of collision between the two vehicles before and after.
- the judgment at this time may be relatively simple. As long as the distance between the two adjacent vehicles is less than or equal to the preset safety distance, the user is reminded to change the driving direction slightly, and try to ensure that the two vehicles are adjacent to each other. There is a safe distance between them.
- the processing unit 602 calculates a risk coefficient of a collision between two adjacent vehicles, and the specific process includes:
- Step a according to the moving speed of the first vehicle, and the distance between the first vehicle and the second vehicle, Calculate the time interval of the workshop.
- step b the relative speed is calculated according to the moving speed of the first vehicle and the moving speed of the second vehicle.
- Step c calculating the pre-collision time according to the relative speed, the distance between the first vehicle and the second vehicle.
- step d the risk coefficient of collision between two adjacent vehicles is calculated according to the time interval of the workshop and the pre-crash time.
- the inter-vehicle time interval is calculated according to the distance between the first vehicle and the second vehicle according to the moving speed of the first vehicle:
- t1 is the inter-vehicle time interval
- v1 is the moving speed of the first vehicle
- s is the distance between the first vehicle and the second vehicle.
- the pre-collision time is calculated based on the relative speed and the distance between the first vehicle and the second vehicle:
- t2 is the pre-crash time
- s the distance between the first vehicle and the second vehicle
- v is the relative speed between two adjacent vehicles.
- the risk factor of collision between two adjacent vehicles is calculated according to the shop time interval t1 and the pre-collision time t2.
- Equation 1-4 the formula for calculating the risk coefficient of collision between two adjacent vehicles according to the shop time interval t1 and the pre-collision time t2 can be expressed by Equations 1-4:
- f is the risk coefficient of collision between two adjacent vehicles; the weight coefficient corresponding to the shop time interval t1; and the weight coefficient corresponding to the pre-collision time t2.
- the inter-vehicle time interval is the time when the first vehicle reaches the current position of the second vehicle according to the moving speed of the first vehicle.
- the pre-collision time refers to the time when the first vehicle will collide with the second vehicle according to the distance between the two if the moving speeds of the first vehicle and the second vehicle do not change.
- the workshop time interval indicates the degree of influence on the pre-collision time if the moving speed of the preceding vehicle changes. That is, if the moving speed of the preceding vehicle changes, if the moving speed of the rear vehicle does not change, the relative speed will change. Correspondingly, the pre-collision time will change. The smaller the pre-collision time, the greater the likelihood of collision between two adjacent vehicles. Therefore, when calculating the risk factor of collision between two adjacent vehicles, it is necessary to consider both the shop time interval and the pre-collision time. Multiply the two by the corresponding weight coefficients and do the sum. finally Obtain the risk factor of collision between two adjacent vehicles.
- the reminding unit 603 is configured to remind at least one of the two adjacent vehicles to adjust the current traveling speed when the risk coefficient is greater than the preset risk threshold.
- the reminding unit 603 is notified.
- the reminder unit 603 reminds at least one of the two adjacent vehicles to adjust the current traveling speed.
- the processor needs to consider the current traveling speed of two adjacent vehicles, while also taking into account the current traveling speed of other adjacent vehicles. Therefore, it may be necessary to adjust only the current travel speed of one of the vehicles, or it may be that the current travel speeds of the two adjacent vehicles need to be adjusted.
- the relative driving speed of the two vehicles is at least a preset relative traveling speed.
- the receiving unit receives the position information of the belonging vehicle and the vehicle traveling speed information transmitted by the vehicle-mounted terminal in real time; and the processing unit determines whether the adjacent vehicles are between the two vehicles according to the two parameters. It is safe to drive, whether the risk factor of collision is too large, and so on. If the risk factor of the collision is too large, the reminder unit is used to remind at least one of the two adjacent vehicles to adjust the current vehicle speed. Therefore, even if there is too much smog between two adjacent vehicles, the presence of the other party cannot be seen, or the distance between the other party and itself cannot be distinguished, or the speed of the other party cannot be judged, etc., as it will be received. The reminder message sent by the server will not cause the vehicle to collide. Thereby reducing the occurrence of traffic accidents and avoiding unnecessary personal injury and property damage.
- the concentration of the smog can also be considered as one of the parameters when calculating the risk coefficient.
- the embodiment of the invention further provides a schematic structural diagram of another device for intelligent driving in a haze day. Specifically, as shown in Figure 7.
- the device comprises: a receiving unit 701, a processing unit 702, and a reminding unit 703.
- the receiving unit 701 is configured to receive vehicle traveling speed information and current position information of the vehicle respectively sent by the vehicle-mounted terminals of each of the plurality of vehicles, and a smog concentration in the current air.
- the vehicle terminal of each vehicle can collect the smog in the current air and detect the smog concentration.
- the haze concentration information and the vehicle travel speed information and the current position information of the vehicle are then simultaneously transmitted to the server.
- the receiving unit 701 in the server is configured to receive the parameter information.
- the processing unit 702 is configured to determine a distance between two adjacent vehicles according to the current location information of the vehicle that is respectively sent by the in-vehicle terminal of each of the plurality of vehicles. According to the workshop time interval, pre-collision time, and smog concentration, the risk coefficient of collision between two adjacent vehicles is comprehensively calculated.
- the processing unit 702 is configured to count the current vehicle sent by each vehicle terminal of each vehicle. Location information to confirm the distance between two adjacent vehicles.
- the statistical process may include front and rear distances and left and right distances.
- the judgment at this time may be relatively simple. As long as the distance between the two adjacent vehicles is less than or equal to the preset safety distance, the user is reminded to change the driving direction slightly, and try to ensure that the two vehicles are adjacent to each other. There is a safe distance between them.
- the specific process includes: step a, calculating the inter-vehicle time interval according to the moving speed of the first vehicle and the distance between the first vehicle and the second vehicle.
- step b the relative speed is calculated according to the moving speed of the first vehicle and the moving speed of the second vehicle.
- Step c calculating the pre-collision time according to the relative speed, the distance between the first vehicle and the second vehicle.
- step d the risk coefficient of collision between two adjacent vehicles is calculated according to the time interval of the workshop and the pre-crash time.
- the inter-vehicle time interval is calculated according to the distance between the first vehicle and the second vehicle according to the moving speed of the first vehicle:
- t1 is the inter-vehicle time interval
- v1 is the moving speed of the first vehicle
- s is the distance between the first vehicle and the second vehicle.
- the pre-collision time is calculated based on the relative speed and the distance between the first vehicle and the second vehicle:
- t2 is the pre-crash time
- s the distance between the first vehicle and the second vehicle
- v is the relative speed between two adjacent vehicles.
- Equation 4-4 The formula for calculating the risk factor of collision between two adjacent vehicles according to the shop time interval t1, the pre-collision time t2, and the haze concentration C can be expressed by Equation 4-4:
- f is the risk factor of collision between two adjacent vehicles; corresponding to the time interval t1 of the workshop
- the weight coefficient is a weight coefficient corresponding to the pre-collision time t2, and is a weight coefficient corresponding to the haze concentration C, and.
- the inter-vehicle time interval is the time when the first vehicle reaches the current position of the second vehicle according to the moving speed of the first vehicle.
- the pre-collision time refers to the time when the first vehicle will collide with the second vehicle according to the distance between the two if the moving speeds of the first vehicle and the second vehicle do not change.
- the workshop time interval indicates the degree of influence on the pre-collision time if the moving speed of the preceding vehicle changes. That is, if the moving speed of the preceding vehicle changes, if the moving speed of the rear vehicle does not change, the relative speed will change. Correspondingly, the pre-collision time will change. The smaller the pre-collision time, the greater the likelihood of collision between two adjacent vehicles. The greater the concentration of smog, the more blurred the state of the user seeing the outside of the car. As a result, because the degree of smog is too high, even if the vehicle may be in danger of collision, the user will not be prepared. Then, it is also necessary to consider the degree of burden of the haze concentration on the user's psychology.
- the reminding unit 703 is configured to remind at least one of the two adjacent vehicles to adjust the current traveling speed when the risk coefficient is greater than the preset risk threshold.
- the processing unit 702 calculates the specific risk coefficient f, it is also required to determine whether the risk coefficient f is greater than a preset risk threshold (for example, the preset risk threshold is 0.5). However, if the risk factor is greater than the preset risk threshold, the processing unit 702 needs to consider the current traveling speed of the two adjacent vehicles, while also taking into account the current traveling speed of the adjacent other vehicles. Therefore, it may be necessary to adjust only the current travel speed of one of the vehicles, or it may be that the current travel speeds of the two adjacent vehicles need to be adjusted. When adjusting, as long as the distance between two adjacent vehicles is at least one preset safe driving distance, the relative driving speed of the two vehicles is at least a preset relative traveling speed.
- a preset risk threshold for example, the preset risk threshold is 0.5.
- a device for intelligent driving in a haze day the processing unit not only considers the speed information between adjacent vehicles, but also the position information of each of the adjacent two vehicles, and further integrates Parameters such as the concentration of smog considered. Through these three parameters, the risk coefficient of the collision between two adjacent vehicles can be determined, and the accuracy can be added. Furthermore, the driving safety of the user in the smog weather is further ensured. It avoids the increase of traffic accidents caused by haze weather, reduces the risk of unnecessary vehicle collisions, and reduces personal injury and property damage.
- the processing unit may further be configured to: determine an area to which the current position of each of the plurality of vehicles belongs, and calculate the two adjacent vehicles in the same area. The risk factor for collisions between them.
- the apparatus may further include a transmitting unit that transmits the current position information and the moving speed of each of the adjacent two vehicles to two different when the two adjacent vehicles are respectively located in two different areas.
- a transmitting unit that transmits the current position information and the moving speed of each of the adjacent two vehicles to two different when the two adjacent vehicles are respectively located in two different areas.
- One of the areas in the area so that the server in the area can calculate the risk factor of collision between two adjacent vehicles based on the current position information of each of the adjacent two vehicles and the moving speed.
- the transmitting unit in the server of another area needs to transmit the position information and the speed information of the vehicle in the edge area to the adjacent area in real time.
- the processing unit in the adjacent area is facilitated to calculate the risk factor between two adjacent vehicles belonging to different areas.
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Abstract
一种在雾霾天智能行驶的方法及装置。雾霾天智能行驶的方法包括:接收多个车辆中每一个车辆的车载终端(10)分别发送的车辆行驶速度信息和车辆的当前位置信息;根据多个车辆中的每一个车辆的车载终端(10)分别发送的车辆当前位置信息,确定相邻两个车辆之间的距离;根据相邻两个车辆之间的距离,以及相邻两个车辆中每一个车辆行驶速度信息,计算相邻两个车辆之间发生碰撞的风险系数;当风险系数大于预设风险阈值时,提醒相邻两个车辆中至少一个车辆调整当前行驶速度。通过采集每个终端(10)分别发送的位置信息和速度信息,计算相邻两辆车之间的距离,以及发生碰撞风险的系数。如果发生碰撞的风险系数过大时,及时提醒用户调整车速。
Description
本发明涉及安全控制技术领域,尤其涉及一种在雾霾天智能行驶的方法及装置。
由于工业技术的迅猛发展,随之而来的,也造成了空气质量的严重降低。艳阳天气成为了“奢侈”,雾霾天气逐渐增多。雾霾,不仅仅会直接威胁人们的健康安全,还会间接导致人身安全。在雾霾天气,将会导致路面的交通状况模糊不清,虽然司机师傅通常都会将车开的很慢,但是还是免不了会发生车辆追尾的事件。甚至有一些安全意识较差的司机,或者经验不足的司机,在雾霾天气车速仍然不减,最终造成重大的交通事故,导致人身伤亡。
那么,如何保证车辆即使在雾霾天气也能够安全出行,则成为了一个亟待解决的技术问题。
发明内容
为解决上述技术问题,本发明提供了一种在雾霾天智能行驶的方法及装置。
第一方面,本发明提供了一种在雾霾天智能行驶的方法,该方法包括:
接收多个车辆中每一个车辆的车载终端分别发送的车辆行驶速度信息和车辆的当前位置信息;
根据多个车辆中的每一个车辆的车载终端分别发送的车辆当前位置信息,确定相邻两个车辆之间的距离;
根据相邻两个车辆之间的距离,以及相邻两个车辆中每一个车辆行驶速度信息,计算相邻两个车辆之间发生碰撞的风险系数;
当风险系数大于预设风险阈值时,提醒相邻两个车辆中至少一个车辆调整当前行驶速度。
本发明实施例提供的一种在雾霾天智能行驶的方法,每一个车辆均通过车载终端发送当前的位置信息和速度信息至服务器。服务器采集这些信息后,可以根据这些信息确定哪些车辆相邻。并且轻易的计算出相邻两辆车之间的距离,以及发生碰撞风险的系数。如果发生碰撞的风险系数过大时,及时提醒用户调整车速,如此一来,即使在雾霾天气,可见度很低的情况下,司机师傅也无需担心会发生交通事故,只要时刻按照服务器发送的广播提示消息,正常驾驶即可。通过上述方法,可以保证车辆在雾霾天气也能够安全行驶,大大避免了交通事故的发生。
进一步的,当相邻两辆车分别位于两个不同区域时,方法还包括:
将相邻两辆车中每一个车辆的当前位置信息以及移动速度传输至两个不同区域中的其中一个区域,以便该区域中的服务器能够根据相邻两辆车中每一个车辆的当前位置信息以及移动速度,计算相邻两辆车之间发生碰撞的风险系数。
采用上述进一步的有益效果在于,为了降低服务器的运算数据量,可以按照区域进行划分。在同一区域中的车辆由一个服务器负责计算相邻两个车辆之间发生碰撞的风险系数。但是,考虑到相邻区域的边界范围内,相邻的两辆车(其中一辆车位于一个区域,另一辆车位于相邻的另一个区域)同样会存在发生碰撞的危险,那么可以将其中一辆车的位置信息发送至另一区域,然后统一由另一个区域中的服务器负责计算二者之间发生碰撞的风险系数。并在风险系数较大时,及时提醒。
第二方面,本发明提供了一种在雾霾天智能行驶的装置,该装置包括:
接收单元,用于接收多个车辆中每一个车辆的车载终端分别发送的车辆行驶速度信息和车辆的当前位置信息;
处理单元,用于根据多个车辆中的每一个车辆的车载终端分别发送的车辆当前位置信息,确定相邻两个车辆之间的距离;
根据相邻两个车辆之间的距离,以及相邻两个车辆中每一个车辆行驶速度信息,计算相邻两个车辆之间发生碰撞的风险系数;
提醒单元,用于当风险系数大于预设风险阈值时,提醒相邻两个车辆中至少一个车辆调整当前行驶速度。
本发明实施例提供的智能确定乘客安全下车的装置,车辆中的每一个车辆均通过车载终端发送当前的位置信息和速度信息至服务器。服务器中的接收单元接收这些信息后,处理单元可以根据这些信息确定哪些车辆相邻。并且轻易的计算出相邻两辆车之间的距离,以及发生碰撞风险的系数。如果发生碰撞的风险系数过大时,及时通过提醒单元提醒用户调整车速,如此一来,即使在雾霾天气,可见度很低的情况下,司机师傅也无需担心会发生交通事故,只要时刻按照服务器发送的广播提示消息,正常驾驶即可。通过上述方法,可以保证车辆在雾霾天气也能够安全行驶,大大避免了交通事故的发生。
进一步的,装置还包括:发送单元,用于当相邻两辆车分别位于两个不同区域时,将相邻两辆车中每一个车辆的当前位置信息以及移动速度传输至两个不同区域中的其中一个区域,以便该区域中的服务器能够根据相邻两辆车中每一个车辆的当前位置信息以及移动速度,计算相邻两辆车之间发生碰撞的风险系数。
采用上述进一步的有益效果在于,为了降低服务器的运算数据量,可以按照区域进行划分。在同一区域中的车辆由一个服务器负责计算相邻两个车辆之间发生碰撞的风险系数。但是,考虑到相邻区域的边界范围内,相邻的两辆车(其中一辆车位于一个区域,另一辆车位于相邻的另一个区域)同样会存在发生碰撞的危险,那么可以利用雾霾天智能行驶的装置中的发送单元将其中一辆车的位置信
息发送至另一区域,然后统一由另一个区域中的服务器负责计算二者之间发生碰撞的风险系数。并在风险系数较大时,及时提醒。
图1为本发明实施例提供的为本发明实施例提供的一种在雾霾天智能行驶的***架构图;
图2为本发明实施例提供的在雾霾天智能行驶的***中各部件之间数据传输的方法信令流程示意图;
图3为本发明实施例提供的一种在雾霾天智能行驶的方法流程示意图;
图4为本发明实施例提供的另一种在雾霾天智能行驶的方法流程示意图;
图5为本发明实施例提供的另一种在雾霾天智能行驶的方法流程示意图;
图6为本发明实施例提供的一种在雾霾天智能行驶的装置结构示意图;
图7为本发明实施例提供的一种在雾霾天智能行驶的装置结构示意图。
以下描述中,为了说明而不是为了限定,提出了诸如特定***结构、接口、技术之类的具体细节,以便透切理解本发明。然而,本领域的技术人员应当清楚,在没有这些具体细节的其它实施例中也可以实现本发明。在其它情况中,省略对众所周知的***、电路以及方法的详细说明,以免不必要的细节妨碍本发明的描述。
图1为本发明实施例提供的一种在雾霾天智能行驶的***架构图。
具体如图1所示,该***至少包括:车载终端10,基站20和服务器30。其中,车载终端10通过基站20和服务器30建立通信连接。车载终端10用于传输数据信号,以及接收服务器30发送的控制指令。其中,基站20的个数和服务器30的个数均为至少一个。在同一个区域中,可以包括一个或者多个基站。而为了降低服务器的计算数据量,每个区域可以配置一个服务器30,或者多个区域配置同一个服务器30。又或者,如果区域太大,可以多个服务器30同时为这个区域服务。具体如何设定,这里不做任何限定。
车载终端10可以利用3G~5G,IPv4、IPv6以及GPRS中的一种或多种通信技术通过基站20和服务器30之间建立通信连接。又或者通过其他通信技术和服务器30之间建立通信连接。这里不做任何限定。
其中,基站20接收多个车辆中每一个车辆的车载终端10分别发送车辆行驶速度信息和车辆的当前位置信息。并将这些参数信息转发至服务器30中。服务器30根据多个车辆中的每一个车辆的车载终端10分别发送的车辆当前位置信息,确定相邻两个车辆之间的距离。
然后,根据相邻两个车辆之间的距离,以及相邻两个车辆中每一个车辆行驶
速度信息,计算相邻两个车辆之间发生碰撞的风险系数。
当风险系数大于预设风险阈值时,通过基站20以数据传输或者广播的形式向相邻的两个车载终端10发送提示信息,提醒相邻的两个车辆中至少一个车辆调整当前行驶速度。
具体的,如图2所示,图2为本发明实施例提供的在雾霾天智能行驶的***中各部件之间数据传输的方法信令流程示意图。
在本实施例中,为了能够让读者能够更加容易的理解本申请文件的具体实现过程。在图2中,仅以相邻的2个车载终端为例进行说明。
步骤1,第一车载终端向基站发送第一数据传输请求,第二车载终端向基站发送第二数据传输请求,其中数据传输请求中包含所要传输的数据大小。
步骤2,分别向第一车载终端和第二车载终端分配调度资源;
具体的,基站接收到第一车载终端发送的第一数据传输请求,以及第二车载终端发送的第二数据传输请求后,会根据第一车载终端和第二车载终端发送的数据传输请求,向第一车载终端发送用于数据传输的第一调度资源,以及向第二车载终端发送用于数据传输的第二调度资源。
步骤3,第一车载终端在第一调度资源的基础上,将第一数据传输至基站,以及第二车载终端在第二调度资源的基础上,将第二数据传输至基站。
具体的,第一车载终端接收到调度资源后,将第一数据加载到第一调度资源上之后,发送至基站。同样的,第二车载终端接收到第二调度资源后,将第二数据加载到第二调度资源上之后,发送至基站。其中,第一数据包括第一车载终端所属的车辆当前的行驶速度和当前位置信息等。相应的,第二数据包括第二车载终端所属的车辆当前的行驶速度和当前位置信息等。
步骤4,基站分别接收到第一车载终端发送的第一数据,以及第二车载终端发送的第二数据后,将第一数据和第二数据转发至服务器。
步骤5,服务器接收到第一数据和第二数据后,分别对第一数据和第二数据进行解析。读取第一车载终端发送的所属车辆行驶速度信息和车辆的当前位置信息,以及第二车载终端发送的所属车辆行驶速度信息和车辆的当前位置信息。
步骤6,服务器根据第一车载终端发送的第一数据和第二车载终端发送的第二数据,确定第一车载终端所属车辆和第二车载终端所属车辆之间的距离。
步骤7,服务器根据第一车载终端所属车辆和第二车载终端所属车辆之间的距离,第一车载终端所属车辆的速度信息以及第二车载终端所属车辆的速度信息,计算相邻两个车辆之间发生碰撞的风险系数。
步骤8,当服务器判断风险系数大于预设风险阈值时,提醒相邻两个车辆中至少一个车辆调整当前行驶速度。
其中,如上,这里的相邻两个车辆,也即是本实施例中的第一车载终端所属车辆和第二车载终端所属车辆。
在本实施例中,通过实时获取每一个车辆的当前位置和速度信息等,并判断相邻车辆之间的距离。从而判断车辆相撞的风险系数,如果风险系数比较大时,调整相邻两辆车的速度。也即是说,即使相邻两辆车之间由于雾霾太大而看不到对方的存在,或者分不清对方与自身之间的距离,又或者无法判断对方的行驶速度等等,由于会收到服务器发送的提醒消息,也不会造成车辆相撞。从而减少了交通事故的发生,避免了不必要的人身伤亡和财产损失的发生。
为进一步详细的说明服务器在本发明的技术方案所执行的步骤,本发明实施例提供了一种在雾霾天智能行驶的方法流程示意图。具体如图3所示,该方法包括:
步骤310,接收多个车辆中每一个车辆的车载终端分别发送的车辆行驶速度信息和车辆的当前位置信息。
具体的,如上一实施例,多个车辆中的每一个车辆的车载终端分别通过基站发送车辆的行驶速度信息和车辆的当前位置信息至服务器中。
步骤320,根据多个车辆中的每一个车辆的车载终端分别发送的车辆当前位置信息,确定相邻两个车辆之间的距离。
具体的,统计每一个车辆的车载终端分别发送的车辆当前位置信息,进而确认相邻两个车辆之间的距离。统计过程中,可以包括前后距离和左右距离。
步骤330,根据相邻两个车辆之间的距离,以及相邻两个车辆中每一个车辆行驶速度信息,计算相邻两个车辆之间发生碰撞的风险系数。
具体的,一般而言,判断相邻两辆车是否存在会发生碰撞的风险时,更侧重于判断前后两辆车之间发生碰撞的风险。
不过,也要考虑左右两辆车发生碰撞的风险。此时的判断可能更相对简单一些,只要判断左右相邻两辆车之间的距离小于或者等于预设的安全距离时,就要提醒用户稍微改变行车方向,尽量保证左右相邻两辆车之间有一个安全距离。
而如果判断前后相邻两辆车之间是否存在风险时,则需要判断相邻两辆车之间的距离之外,还包括分别确定两辆车的速度信息。最终根据二者的速度信息,以及二者之间的距离。计算相邻两辆车之间发生的碰撞的风险系数。
步骤340,当风险系数大于预设风险阈值时,提醒相邻两个车辆中至少一个车辆调整当前行驶速度。
具体的,当风险系数大于预设风险阈值(例如预设风险阈值为0.6)时,服务器需要考虑相邻两辆车的当前行驶速度,同时还要兼顾相邻的其他车辆的当前行驶速度。所以,可能需要调整的只是其中一个车辆的当前行驶速度,也可能是相邻两个车辆的当前行驶速度均需要进行调整。调整时,只要保证相邻两辆车之间的距离至少为一个预设的安全行驶距离,两辆车的相对行驶速度至少为一个预设的相对行驶速度。
本发明实施例提供的一种在雾霾天智能行驶的方法,服务器通过实时接收车
载终端发送的所属车辆的位置信息和车辆行驶速度信息,并根据这两种参数确定相邻车辆之间是否是安全行驶,发生碰撞的风险系数是否过大等等。如果发生碰撞的风险系数过大时,则提醒相邻的两辆车中至少一辆车调整当前车速。因此,即使相邻两辆车之间由于雾霾太大而看不到对方的存在,或者分不清对方与自身之间的距离,又或者无法判断对方的行驶速度等等,由于会收到服务器发送的提醒消息,也不会造成车辆相撞。从而减少了交通事故的发生,避免了不必要的人身伤亡和财产损失的发生。
本发明实施例还提供了另一种在雾霾天智能行驶的方法流程示意图,具体如图4所示,该方法包括:
步骤410,接收多个车辆中每一个车辆的车载终端分别发送的车辆行驶速度信息和车辆的当前位置信息。
具体的,如上一实施例,多个车辆中的每一个车辆的车载终端分别通过基站发送车辆的行驶速度信息和车辆的当前位置信息至服务器中。
步骤420,根据多个车辆中的每一个车辆的车载终端分别发送的车辆当前位置信息,确定相邻两个车辆之间的距离。
具体的,统计每一个车辆的车载终端分别发送的车辆当前位置信息,进而确认相邻两个车辆之间的距离。统计过程中,可以包括前后距离和左右距离。
步骤430,根据相邻两个车辆之间的距离,以及相邻两个车辆中每一个车辆行驶速度信息,计算相邻两个车辆之间发生碰撞的风险系数。
具体的,一般而言,判断相邻两辆车是否存在会发生碰撞的风险时,更侧重于判断前后两辆车之间发生碰撞的风险。
不过,也要考虑左右两辆车发生碰撞的风险。此时的判断可能更相对简单一些,只要判断左右相邻两辆车之间的距离小于或者等于预设的安全距离时,就要提醒用户稍微改变行车方向,尽量保证左右相邻两辆车之间有一个安全距离。
而如果判断前后相邻两辆车之间是否存在风险时,则需要判断相邻两辆车之间的距离之外,还包括分别确定两辆车的速度信息。最终根据二者的速度信息,以及二者之间的距离。计算相邻两辆车之间发生的碰撞的风险系数。
而计算相邻两辆车之间发生的碰撞的风险系数时,可以包括如下方法步骤。
步骤a,根据第一车辆的移动速度,以及第一车辆和第二车辆之间的距离,计算车间时距。
步骤b,根据第一车辆的移动速度和第二车辆的移动速度,计算相对速度。
步骤c,根据相对速度,第一车辆和第二车辆之间的距离,计算预碰撞时间。
步骤d,根据车间时距、预碰撞时间计算相邻两个车辆之间发生碰撞的风险系数。
具体的,根据第一车辆的移动速度,第一车辆和第二车辆之间的距离,计算车间时距:
其中,t1为车间时距;v1为第一车辆的移动速度;s为第一车辆和第二车辆之间的距离。
然后,根据第一车辆的移动速度和第二车辆的移动速度,计算相对速度:
v=v1-v2 (1-2)
其中,v为相邻两辆车之间的相对速度;v1为第一车辆的移动速度;v2为第二车辆的移动速度。
根据相对速度,以及第一车辆和第二车辆之间的距离,计算预碰撞时间:
其中,t2为预碰撞时间;s第一车辆和第二车辆之间的距离;v为相邻两辆车之间的相对速度。
最终,根据车间时距t1,预碰撞时间t2计算相邻两个车辆之间发生碰撞的风险系数。
具体的,根据车间时距t1,预碰撞时间t2计算相邻两个车辆之间发生碰撞的风险系数的公式可以由公式1-4表示:
f=αt1+βt2 (1-4)
其中,f为相邻两个车辆之间发生碰撞的风险系数;为与车间时距t1对应的权重系数;为与预碰撞时间t2对应的权重系数,且。
以上,车间时距为第一车辆按照第一车辆的移动速度,到达第二车辆当前位置时的时间。预碰撞时间指的是如果第一车辆和第二车辆的移动速度均不发生改变,按照当前二者之间的距离,第一车辆将会与第二车辆发生碰撞的时间。
需要说明的是,车间时距表示的是如果前方车辆的移动速度变化对预碰撞时间的影响程度。即,如果前方车辆的移动速度变化时,如果后方车辆的移动速度不发生改变的情况下,那么相对速度将会发生改变。对应的,预碰撞时间则会发生改变。预碰撞时间越小,那么相邻的两个车辆之间发生碰撞的可能性则会越大。因此,在计算相邻两个车辆之间发生碰撞的风险系数时,需要同时考虑车间时距和预碰撞时间这两个参数。将二者之间分别乘以相应的权重系数,并做和。最终获取相邻两个车辆之间发生碰撞的风险系数。
步骤440,当风险系数大于预设风险阈值时,提醒相邻两个车辆中至少一个车辆调整当前行驶速度。
具体的,根据步骤430计算出具体的风险系数f后,判断风险系数f是否大于预设的风险阈值(例如预设风险阈值为0.6)。而如果当风险系数大于预设风险阈值时,服务器需要考虑相邻两辆车的当前行驶速度,同时还要兼顾相邻的其他车辆的当前行驶速度。所以,可能需要调整的只是其中一个车辆的当前行驶速
度,也可能是相邻两个车辆的当前行驶速度均需要进行调整。调整时,只要保证相邻两辆车之间的距离至少为一个预设的安全行驶距离,两辆车的相对行驶速度至少为一个预设的相对行驶速度。
本发明实施例提供的一种在雾霾天智能行驶的方法,服务器通过实时接收车载终端发送的所属车辆的位置信息和车辆行驶速度信息,并根据这两种参数确定相邻车辆之间是否是安全行驶,发生碰撞的风险系数是否过大等等。如果发生碰撞的风险系数过大时,则提醒相邻的两辆车中至少一辆车调整当前车速。因此,即使相邻两辆车之间由于雾霾太大而看不到对方的存在,或者分不清对方与自身之间的距离,又或者无法判断对方的行驶速度等等,由于会收到服务器发送的提醒消息,也不会造成车辆相撞。从而减少了交通事故的发生,避免了不必要的人身伤亡和财产损失的发生。
进一步的,因为本发明实施方案侧重于考虑在雾霾天气情况的下的行车安全,因此,在计算风险系数时,还可以考虑将雾霾的浓度作为计算风险系数时其中的一个参数。
具体的,如图5所示,图5为本发明实施例提供的另一种在雾霾天智能行驶的方法流程示意图。该方法包括:
步骤510,接收多个车辆中每一个车辆的车载终端分别发送的车辆行驶速度信息和车辆的当前位置信息。
具体的,如上一实施例,多个车辆中的每一个车辆的车载终端分别通过基站发送车辆的行驶速度信息和车辆的当前位置信息至服务器中。
步骤520,根据多个车辆中的每一个车辆的车载终端分别发送的车辆当前位置信息,确定相邻两个车辆之间的距离。
具体的,统计每一个车辆的车载终端分别发送的车辆当前位置信息,进而确认相邻两个车辆之间的距离。统计过程中,可以包括前后距离和左右距离。
步骤530,接收多个车辆中每一个车辆的车载终端分别发送的当前空气中的雾霾浓度。
具体的,每一个车辆的车载终端均可以采集当前空气中的雾霾,并检测器雾霾浓度。然后将雾霾浓度信息和车辆行驶速度信息和车辆的当前位置信息同时发送至服务器中,或者分别发送至服务器中。服务器接收到这三种参数后,执行步骤540。
步骤540,根据车间时距、预碰撞时间,以及雾霾浓度,综合计算相邻两个车辆之间发生碰撞的风险系数。
具体的,一般而言,判断相邻两辆车是否存在会发生碰撞的风险时,更侧重于判断前后两辆车之间发生碰撞的风险。
不过,也要考虑左右两辆车发生碰撞的风险。此时的判断可能更相对简单一
些,只要判断左右相邻两辆车之间的距离小于或者等于预设的安全距离时,就要提醒用户稍微改变行车方向,尽量保证左右相邻两辆车之间有一个安全距离。
而如果判断前后相邻两辆车之间是否存在风险时,则需要判断相邻两辆车之间的距离之外,还包括分别确定两辆车的速度信息、当前空气中的雾霾浓度等等。最终根据相邻两辆车之间的速度信息,相邻两辆车之间的距离,以及雾霾浓度等。综合计算相邻两辆车之间发生的碰撞的风险系数。
而综合计算相邻两辆车之间发生的碰撞的风险系数时,步骤a~c与上一实施例相同,这里不再赘述。唯一不同的则是步骤d。
具体的,步骤d,根据车间时距、预碰撞时间以及雾霾浓度计算相邻两个车辆之间发生碰撞的风险系数。
具体的,根据第一车辆的移动速度,第一车辆和第二车辆之间的距离,计算车间时距:
其中,t1为车间时距;v1为第一车辆的移动速度;s为第一车辆和第二车辆之间的距离。
然后,根据第一车辆的移动速度和第二车辆的移动速度,计算相对速度:
v=v1-v2 (2-2)
其中,v为相邻两辆车之间的相对速度;v1为第一车辆的移动速度;v2为第二车辆的移动速度。
根据相对速度,以及第一车辆和第二车辆之间的距离,计算预碰撞时间:
其中,t2为预碰撞时间;s第一车辆和第二车辆之间的距离;v为相邻两辆车之间的相对速度。
根据车间时距t1,预碰撞时间t2以及雾霾浓度C计算相邻两个车辆之间发生碰撞的风险系数的公式可以由公式2-4表示:
f=αt1+βt2 (2-4)
其中,f为相邻两个车辆之间发生碰撞的风险系数;为与车间时距t1对应的权重系数;为与预碰撞时间t2对应的权重系数,为雾霾浓度C对应的权重系数,且。
以上,车间时距为第一车辆按照第一车辆的移动速度,到达第二车辆当前位置时的时间。预碰撞时间指的是如果第一车辆和第二车辆的移动速度均不发生改变,按照当前二者之间的距离,第一车辆将会与第二车辆发生碰撞的时间。
需要说明的是,车间时距表示的是如果前方车辆的移动速度变化对预碰撞时间的影响程度。即,如果前方车辆的移动速度变化时,如果后方车辆的移动速度不发生改变的情况下,那么相对速度将会发生改变。对应的,预碰撞时间则会发
生改变。预碰撞时间越小,那么相邻的两个车辆之间发生碰撞的可能性则会越大。而雾霾浓度越大,用户看见车外的状态也越模糊,如此以来,因为雾霾程度太高,即使车辆可能会发生碰撞危险,用户也不会有什么心理准备。那么,就还需要考虑雾霾浓度会对用户的心理造成的负担程度。因此,在计算相邻两个车辆之间发生碰撞的风险系数时,需要同时考虑车间时距和预碰撞时间以及雾霾浓度这三个参数。将三者之间分别乘以相应的权重系数,并做和。最终获取相邻两个车辆之间发生碰撞的风险系数。
步骤550,当风险系数大于预设风险阈值时,提醒相邻两个车辆中至少一个车辆调整当前行驶速度。
具体的,根据步骤530计算出具体的风险系数f后,判断风险系数f是否大于预设的风险阈值(例如预设风险阈值为0.5)。而如果当风险系数大于预设风险阈值时,服务器需要考虑相邻两辆车的当前行驶速度,同时还要兼顾相邻的其他车辆的当前行驶速度。所以,可能需要调整的只是其中一个车辆的当前行驶速度,也可能是相邻两个车辆的当前行驶速度均需要进行调整。调整时,只要保证相邻两辆车之间的距离至少为一个预设的安全行驶距离,两辆车的相对行驶速度至少为一个预设的相对行驶速度。
本发明实施例提供的一种在雾霾天智能行驶的方法,不仅仅考虑了相邻车辆之间的速度信息,以及相邻两辆车中每一辆车的位置信息以外,还综合考虑的雾霾浓度等参数。通过这三种参数确定相邻两个车辆碰撞的风险系数,能加精准。进而,进一步保证了用户在雾霾天气的行车安全。避免了因为雾霾天气而造成的交通事故的增多,降低了不必要的车辆碰撞的风险,以及减少了人身伤亡和财产损失。
另外,为了防止一个服务器同时处理大量数据时,所造成的服务器负担过重。处理速度延时,而造成的不必要的危险发生。上述任一个实施例中,在接收多个车辆中每一个车辆的车载终端分别发送的车辆行驶速度信息和车辆的当前位置信息之后,均可以包括一个步骤A~B,具体如图3-5所示。
步骤A,确定多个车辆中每一个车辆的当前位置所属区域。
步骤B,在同一区域中,计算相邻两个车辆之间发生碰撞的风险系数。
如上文中,在每个区域分别安放一个或者多个服务器。用于处理该区域内相邻两个车辆之间的碰撞风险系数。
优选的,如果相邻的两个车辆分属于两个不同的区域时,当相邻两辆车分别位于两个不同区域时,方法还包括:
将相邻两辆车中每一个车辆的当前位置信息以及移动速度传输至两个不同区域中的其中一个区域,以便该区域中的服务器能够根据相邻两辆车中每一个车辆的当前位置信息以及移动速度,计算相邻两辆车之间发生碰撞的风险系数。其中,为了保证其中一个区域中的服务器能够接收到另一个区域中边缘区域的车辆
的位置信息和速度信息。那么,另一个区域的服务器需要实时将边缘区域中的车辆的位置信息和速度信息发送至相邻的区域中。以便于相邻的区域来计算分属于不同区域的相邻两个车辆之间的风险系数。
而后续其他步骤则和上文中实施例的方法步骤相同,这里将不再赘述。
读者应理解,虽然本发明的上述实施例均以雾霾天气为具体的应用场景。实际上而言,该方案并非只能应用于雾霾天气。该方案还可以应用于大雨天气,例如雨量过大,同样会造成用户在车内看到车外的道路模糊不清。或者普通的艳阳天气同样适用。比如用户是“新手上路”,或者用户经验较少,那么根据本发明提供的技术方案,通过及时提醒“新手”或者经验较少的用户,以及他们相邻的车辆调整车速,同样可以减少交通事故情况的发生。保证人身安全和财产损失。
相应地,本发明实施例还提供了一种在雾霾天智能行驶的装置。图6为本发明实施例提供的一种在雾霾天智能行驶的装置结构示意图。如图6所示,该装置包括:接收单元601,处理单元602以及提醒单元603。
其中,接收单元601,用于接收多个车辆中每一个车辆的车载终端分别发送的车辆行驶速度信息和车辆的当前位置信息。
具体的,多个车辆中的每一个车辆的车载终端分别通过基站发送车辆的行驶速度信息和车辆的当前位置信息至服务器中。而服务器中的接收单元601则用于分别车载终端传输的这些参数信息。
处理单元602,用于根据多个车辆中的每一个车辆的车载终端分别发送的车辆当前位置信息,确定相邻两个车辆之间的距离。根据相邻两个车辆之间的距离,以及相邻两个车辆中每一个车辆行驶速度信息,计算相邻两个车辆之间发生碰撞的风险系数
具体的,处理单元602首先统计每一个车辆的车载终端分别发送的车辆当前位置信息,进而确认相邻两个车辆之间的距离。统计过程中,可以包括前后距离和左右距离。
一般而言,处理单元602判断相邻两辆车是否存在会发生碰撞的风险时,更侧重于判断前后两辆车之间发生碰撞的风险。
不过,也要考虑左右两辆车发生碰撞的风险。此时的判断可能更相对简单一些,只要判断左右相邻两辆车之间的距离小于或者等于预设的安全距离时,就要提醒用户稍微改变行车方向,尽量保证左右相邻两辆车之间有一个安全距离。
而如果判断前后相邻两辆车之间是否存在风险时,则需要判断相邻两辆车之间的距离之外,还包括分别确定两辆车的速度信息。最终根据二者的速度信息,以及二者之间的距离。计算相邻两辆车之间发生的碰撞的风险系数。
具体的,处理单元602计算相邻两辆车之间发生的碰撞的风险系数,具体流程包括:
步骤a,根据第一车辆的移动速度,以及第一车辆和第二车辆之间的距离,
计算车间时距。
步骤b,根据第一车辆的移动速度和第二车辆的移动速度,计算相对速度。
步骤c,根据相对速度,第一车辆和第二车辆之间的距离,计算预碰撞时间。
步骤d,根据车间时距、预碰撞时间计算相邻两个车辆之间发生碰撞的风险系数。
具体的,根据第一车辆的移动速度,第一车辆和第二车辆之间的距离,计算车间时距:
其中,t1为车间时距;v1为第一车辆的移动速度;s为第一车辆和第二车辆之间的距离。
然后,根据第一车辆的移动速度和第二车辆的移动速度,计算相对速度:
v=v1-v2 (3-2)
其中,v为相邻两辆车之间的相对速度;v1为第一车辆的移动速度;v2为第二车辆的移动速度。
根据相对速度,以及第一车辆和第二车辆之间的距离,计算预碰撞时间:
其中,t2为预碰撞时间;s第一车辆和第二车辆之间的距离;v为相邻两辆车之间的相对速度。
最终,根据车间时距t1,预碰撞时间t2计算相邻两个车辆之间发生碰撞的风险系数。
具体的,根据车间时距t1,预碰撞时间t2计算相邻两个车辆之间发生碰撞的风险系数的公式可以由公式1-4表示:
f=αt1+βt2 (3-4)
其中,f为相邻两个车辆之间发生碰撞的风险系数;为与车间时距t1对应的权重系数;为与预碰撞时间t2对应的权重系数,且。
以上,车间时距为第一车辆按照第一车辆的移动速度,到达第二车辆当前位置时的时间。预碰撞时间指的是如果第一车辆和第二车辆的移动速度均不发生改变,按照当前二者之间的距离,第一车辆将会与第二车辆发生碰撞的时间。
需要说明的是,车间时距表示的是如果前方车辆的移动速度变化对预碰撞时间的影响程度。即,如果前方车辆的移动速度变化时,如果后方车辆的移动速度不发生改变的情况下,那么相对速度将会发生改变。对应的,预碰撞时间则会发生改变。预碰撞时间越小,那么相邻的两个车辆之间发生碰撞的可能性则会越大。因此,在计算相邻两个车辆之间发生碰撞的风险系数时,需要同时考虑车间时距和预碰撞时间这两个参数。将二者之间分别乘以相应的权重系数,并做和。最终
获取相邻两个车辆之间发生碰撞的风险系数。
提醒单元603,用于当风险系数大于预设风险阈值时,提醒相邻两个车辆中至少一个车辆调整当前行驶速度。
具体的,当处理单元602确定风险系数大于预设风险阈值时,将会通知提醒单元603。以便提醒单元603提醒相邻两个车辆中至少一个车辆调整当前行驶速度。
当然,当风险系数大于预设风险阈值(例如预设风险阈值为0.5)时,处理器需要考虑相邻两辆车的当前行驶速度,同时还要兼顾相邻的其他车辆的当前行驶速度。所以,可能需要调整的只是其中一个车辆的当前行驶速度,也可能是相邻两个车辆的当前行驶速度均需要进行调整。调整时,只要保证相邻两辆车之间的距离至少为一个预设的安全行驶距离,两辆车的相对行驶速度至少为一个预设的相对行驶速度。
本发明实施例提供的一种在雾霾天智能行驶的装置,接收单元实时接收车载终端发送的所属车辆的位置信息和车辆行驶速度信息;处理单元根据这两种参数确定相邻车辆之间是否是安全行驶,发生碰撞的风险系数是否过大等等。如果发生碰撞的风险系数过大时,则通过提醒单元提醒相邻的两辆车中至少一辆车调整当前车速。因此,即使相邻两辆车之间由于雾霾太大而看不到对方的存在,或者分不清对方与自身之间的距离,又或者无法判断对方的行驶速度等等,由于会收到服务器发送的提醒消息,也不会造成车辆相撞。从而减少了交通事故的发生,避免了不必要的人身伤亡和财产损失的发生。
进一步的,因为本发明实施方案侧重于考虑在雾霾天气情况的下的行车安全,因此,在计算风险系数时,还可以考虑将雾霾的浓度作为计算风险系数时其中的一个参数。
因此,本发明实施例还提供了另一种在雾霾天智能行驶的装置结构示意图。具体如图7所示。
该装置包括:接收单元701,处理单元702,提醒单元703。
其中,接收单元701,用于接收多个车辆中每一个车辆的车载终端分别发送的车辆行驶速度信息和车辆的当前位置信息,以及当前空气中的雾霾浓度。
具体的,每一个车辆的车载终端均可以采集当前空气中的雾霾,并检测器雾霾浓度。然后将雾霾浓度信息和车辆行驶速度信息和车辆的当前位置信息同时发送至服务器中。服务器中的接收单元701则用于接收这些参数信息。
处理单元702,用于根据多个车辆中的每一个车辆的车载终端分别发送的车辆当前位置信息,确定相邻两个车辆之间的距离。根据车间时距、预碰撞时间,以及雾霾浓度,综合计算相邻两个车辆之间发生碰撞的风险系数。
具体的,处理单元702用于统计每一个车辆的车载终端分别发送的车辆当前
位置信息,进而确认相邻两个车辆之间的距离。统计过程中,可以包括前后距离和左右距离。
一般而言,判断相邻两辆车是否存在会发生碰撞的风险时,更侧重于判断前后两辆车之间发生碰撞的风险。
不过,也要考虑左右两辆车发生碰撞的风险。此时的判断可能更相对简单一些,只要判断左右相邻两辆车之间的距离小于或者等于预设的安全距离时,就要提醒用户稍微改变行车方向,尽量保证左右相邻两辆车之间有一个安全距离。
而如果判断前后相邻两辆车之间是否存在风险时,则需要判断相邻两辆车之间的距离之外,还包括分别确定两辆车的速度信息、当前空气中的雾霾浓度等等。最终根据相邻两辆车之间的速度信息,相邻两辆车之间的距离,以及雾霾浓度等。综合计算相邻两辆车之间发生的碰撞的风险系数。
具体过程包括:步骤a,根据第一车辆的移动速度,以及第一车辆和第二车辆之间的距离,计算车间时距。
步骤b,根据第一车辆的移动速度和第二车辆的移动速度,计算相对速度。
步骤c,根据相对速度,第一车辆和第二车辆之间的距离,计算预碰撞时间。
步骤d,根据车间时距、预碰撞时间计算相邻两个车辆之间发生碰撞的风险系数。
具体的,根据第一车辆的移动速度,第一车辆和第二车辆之间的距离,计算车间时距:
其中,t1为车间时距;v1为第一车辆的移动速度;s为第一车辆和第二车辆之间的距离。
然后,根据第一车辆的移动速度和第二车辆的移动速度,计算相对速度:
v=v1-v2 (4-2)
其中,v为相邻两辆车之间的相对速度;v1为第一车辆的移动速度;v2为第二车辆的移动速度。
根据相对速度,以及第一车辆和第二车辆之间的距离,计算预碰撞时间:
其中,t2为预碰撞时间;s第一车辆和第二车辆之间的距离;v为相邻两辆车之间的相对速度。
根据车间时距t1,预碰撞时间t2以及雾霾浓度C计算相邻两个车辆之间发生碰撞的风险系数的公式可以由公式4-4表示:
f=αt1+βt2 (4-4)
其中,f为相邻两个车辆之间发生碰撞的风险系数;为与车间时距t1对应的
权重系数;为与预碰撞时间t2对应的权重系数,为雾霾浓度C对应的权重系数,且。
以上,车间时距为第一车辆按照第一车辆的移动速度,到达第二车辆当前位置时的时间。预碰撞时间指的是如果第一车辆和第二车辆的移动速度均不发生改变,按照当前二者之间的距离,第一车辆将会与第二车辆发生碰撞的时间。
需要说明的是,车间时距表示的是如果前方车辆的移动速度变化对预碰撞时间的影响程度。即,如果前方车辆的移动速度变化时,如果后方车辆的移动速度不发生改变的情况下,那么相对速度将会发生改变。对应的,预碰撞时间则会发生改变。预碰撞时间越小,那么相邻的两个车辆之间发生碰撞的可能性则会越大。而雾霾浓度越大,用户看见车外的状态也越模糊,如此以来,因为雾霾程度太高,即使车辆可能会发生碰撞危险,用户也不会有什么心理准备。那么,就还需要考虑雾霾浓度会对用户的心理造成的负担程度。因此,在计算相邻两个车辆之间发生碰撞的风险系数时,需要同时考虑车间时距和预碰撞时间以及雾霾浓度这三个参数。将三者之间分别乘以相应的权重系数,并做和。最终获取相邻两个车辆之间发生碰撞的风险系数。
提醒单元703,用于当风险系数大于预设风险阈值时,提醒相邻两个车辆中至少一个车辆调整当前行驶速度。
具体的,处理单元702计算出具体的风险系数f后,还需要判断风险系数f是否大于预设的风险阈值(例如预设风险阈值为0.5)。而如果当风险系数大于预设风险阈值时,处理单元702需要考虑相邻两辆车的当前行驶速度,同时还要兼顾相邻的其他车辆的当前行驶速度。所以,可能需要调整的只是其中一个车辆的当前行驶速度,也可能是相邻两个车辆的当前行驶速度均需要进行调整。调整时,只要保证相邻两辆车之间的距离至少为一个预设的安全行驶距离,两辆车的相对行驶速度至少为一个预设的相对行驶速度。
本发明实施例提供的一种在雾霾天智能行驶的装置,处理单元不仅仅考虑了相邻车辆之间的速度信息,以及相邻两辆车中每一辆车的位置信息以外,还综合考虑的雾霾浓度等参数。通过这三种参数确定相邻两个车辆碰撞的风险系数,能加精准。进而,进一步保证了用户在雾霾天气的行车安全。避免了因为雾霾天气而造成的交通事故的增多,降低了不必要的车辆碰撞的风险,以及减少了人身伤亡和财产损失。
进一步的,为了防止一个服务器同时处理大量数据时,所造成的服务器负担过重。处理速度延时,而造成的不必要的危险发生。在上述任一种的在雾霾天智能行驶的装置中,处理单元均还可以用于:确定多个车辆中每一个车辆的当前位置所属区域,在同一区域中,计算相邻两个车辆之间发生碰撞的风险系数。
进一步的,该装置还可以包括发送单元,当相邻两辆车分别位于两个不同区域时,将相邻两辆车中每一个车辆的当前位置信息以及移动速度传输至两个不同
区域中的其中一个区域,以便该区域中的服务器能够根据相邻两辆车中每一个车辆的当前位置信息以及移动速度,计算相邻两辆车之间发生碰撞的风险系数。其中,为了保证其中一个区域中的服务器能够接收到另一个区域中边缘区域的车辆的位置信息和速度信息。那么,另一个区域的服务器中的发送单元需要实时将边缘区域中的车辆的位置信息和速度信息发送至相邻的区域中。以便于相邻的区域中的处理单元来计算分属于不同区域的相邻两个车辆之间的风险系数。
读者应理解,在本说明书的描述中,参考术语“一个实施例”、“一些实施例”、“示例”、“具体示例”、或“一些示例”等的描述意指结合该实施例或示例描述的具体特征、结构、材料或者特点包含于本发明的至少一个实施例或示例中。在本说明书中,对上述术语的示意性表述不必针对的是相同的实施例或示例。而且,描述的具体特征、结构、材料或者特点可以在任一个或多个实施例或示例中以合适的方式结合。此外,在不相互矛盾的情况下,本领域的技术人员可以将本说明书中描述的不同实施例或示例以及不同实施例或示例的特征进行结合和组合。
尽管上面已经示出和描述了本发明的实施例,可以理解的是,上述实施例是示例性的,不能理解为对本发明的限制,本领域的普通技术人员在本发明的范围内可以对上述实施例进行变化、修改、替换和变型。
Claims (10)
- 一种在雾霾天智能行驶的方法,其特征在于,所述方法包括:接收多个车辆中每一个车辆的车载终端分别发送的车辆行驶速度信息和车辆当前位置信息;根据所述多个车辆中的每一个车辆的车载终端分别发送的车辆当前位置信息,确定相邻两个车辆之间的距离;根据相邻两个车辆之间的距离,以及相邻两个车辆中每一个车辆行驶速度信息,计算相邻两个车辆之间发生碰撞的风险系数;当所述风险系数大于预设风险阈值时,提醒相邻两个车辆中至少一个车辆调整当前行驶速度。
- 根据权利要求1所述的方法,其特征在于,所述根据相邻两个车辆之间的距离,以及相邻两个车辆中每一个车辆行驶速度信息,计算相邻两个车辆之间发生碰撞的风险系数,具体包括:根据第一车辆的移动速度,以及所述第一车辆和第二车辆之间的距离,计算车间时距,其中车间时距为所述第一车辆按照所述第一车辆的移动速度,到达所述第二车辆当前位置时的时间;根据所述第一车辆的移动速度和所述第二车辆的移动速度,计算相对速度;并根据所述相对速度,所述第一车辆和第二车辆之间的距离,计算预碰撞时间;根据所述车间时距、所述预碰撞时间计算相邻两个车辆之间发生碰撞的风险系数,其中,所述第一车辆为相邻两个车辆中行驶在后的车辆,所述第二车辆为相邻两个车辆中行驶在前的车辆,所述第一车辆和第二车辆之间的距离为相邻两个车辆之间的距离。
- 根据权利要求2所述的方法,其特征在于,所述根据相邻两个车辆之间的距离,以及相邻两个车辆中每一个车辆行驶速度信息,计算相邻两个车辆之间发生碰撞的风险系数之前,所述方法还包括:接收多个车辆中每一个车辆的车载终端分别发送的当前空气中的雾霾浓度;根据所述车间时距、所述预碰撞时间,以及所述雾霾浓度,综合计算所述相邻两个车辆之间发生碰撞的风险系数。
- 根据权利要求3所述的方法,其特征在于,所述根据所述车间时距、所述预碰撞时间和所述雾霾浓度,计算相邻两个车辆之间发生碰撞的风险系数的公式,具体如下:碰撞风险系数=α车间时距+β预碰撞时间+γ雾霾浓度其中,为与所述车间时距对应的权重系数,为与所述预碰撞时间对应的权重系数,为雾霾浓度对应的权重系数,且α+β+γ=1。
- 根据权利要求1-4任一项所述的方法,其特征在于,所述接收多个车辆 中每一个车辆的车载终端分别发送的车辆行驶速度信息和车辆的当前位置信息之后,所述方法还包括:确定所述多个车辆中每一个车辆的当前位置所属区域;在同一区域中,计算相邻两个车辆之间发生碰撞的风险系数。
- 一种在雾霾天智能行驶的装置,其特征在于,所述装置包括:接收单元,用于接收多个车辆中每一个车辆的车载终端分别发送的车辆行驶速度信息和车辆的当前位置信息;处理单元,用于根据所述多个车辆中的每一个车辆的车载终端分别发送的车辆当前位置信息,确定相邻两个车辆之间的距离;根据相邻两个车辆之间的距离,以及相邻两个车辆中每一个车辆行驶速度信息,计算相邻两个车辆之间发生碰撞的风险系数;提醒单元,用于当所述风险系数大于预设风险阈值时,提醒相邻两个车辆中至少一个车辆调整当前行驶速度。
- 根据权利要求6所述的装置,其特征在于,所述处理单元具体用于,根据第一车辆的移动速度,以及所述第一车辆和第二车辆之间的距离,计算车间时距,其中车间时距为所述第一车辆按照所述第一车辆的移动速度,到达所述第二车辆当前位置时的时间;根据所述第一车辆的移动速度和所述第二车辆的移动速度,计算相对速度;并根据所述相对速度,所述第一车辆和第二车辆之间的距离,计算预碰撞时间;根据所述车间时距、所述预碰撞时间计算相邻两个车辆之间发生碰撞的风险系数,其中,所述第一车辆为相邻两个车辆中行驶在后的车辆,所述第二车辆为相邻两个车辆中行驶在前的车辆,所述第一车辆和第二车辆之间的距离为相邻两个车辆之间的距离。
- 根据权利要求7所述的装置,其特征在于,所述接收单元还用于:接收多个车辆中每一个车辆的车载终端分别发送的当前空气中的雾霾浓度;所述处理单元还用于,根据所述车间时距、所述预碰撞时间,以及所述雾霾浓度,综合计算所述相邻两个车辆之间发生碰撞的风险系数。
- 根据权利要求8所述的装置,其特征在于,所述处理单元根据所述车间时距、所述预碰撞时间和所述雾霾浓度,计算相邻两个车辆之间发生碰撞的风险系数的公式,具体如下:碰撞风险系数=α车间时距+β预碰撞时间+γ雾霾浓度其中,为与所述车间时距对应的权重系数,为与所述预碰撞时间对应的权重系数,为雾霾浓度对应的权重系数,且α+β+γ=1。
- 根据权利要求6-9任一项所述的装置,其特征在于,所述处理单元还用于:确定所述多个车辆中每一个车辆的当前位置所属区域;在同一区域中,计算相邻两个车辆之间发生碰撞的风险系数。
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