Disclosure of Invention
In order to solve the problems, the invention provides an unmanned vehicle control system based on a multi-sensor fusion technology.
The invention provides an unmanned vehicle control system based on a multi-sensor fusion technology, which comprises a sensing module, a control module and a control module, wherein the sensing module is used for acquiring and transmitting information of surrounding environment of a vehicle;
The map fusion module comprises a map unit and a positioning fusion unit, wherein the map unit is used for acquiring map information near a vehicle through a GPS, and the positioning fusion unit judges whether the vehicle belongs to a remote area, an unknown path or an urban road or a road section driven frequently through the map information on the GPS and historical vehicle driving data and transmits a judging result;
The driving control module comprises a decision unit and a control unit, wherein the decision unit is used for receiving the vehicle surrounding information of the perception module and the judgment result of the positioning fusion unit, outputting a control decision and transmitting the control decision to the control unit;
The specific steps of the output control decision are as follows:
When the positioning fusion unit judges that the vehicle is on an urban road or a road section driven frequently through GPS and historical data, the decision unit outputs a high-speed mode decision signal;
when the positioning fusion unit judges that the vehicle is in a remote area or a path with less historical driving data, the decision unit outputs a safety mode decision signal;
monitoring the surrounding environment information of the vehicle of the sensing module, and outputting an emergency decision signal by the decision unit when the emergency signal is monitored;
The control unit is used for adjusting parameters when the vehicle runs and switching control states according to control decisions of the decision unit;
the control unit comprises a first control state and a second control state;
When the control unit receives a high-speed mode decision signal of the decision unit, switching to a first control state;
When the control unit receives the safety mode decision signal of the decision unit, switching to a second control state;
the control unit also comprises an emergency control state, and is switched to an emergency mode control state when the decision unit outputs an emergency decision signal;
and the communication coordination module is used for realizing communication between vehicles and between the vehicles and the infrastructure, and adjusting coordination states according to control decisions of the decision unit.
Preferably, the specific working mode of the positioning fusion unit is as follows:
Acquiring real-time position coordinates of the vehicle through a GPS receiver, and retrieving map information of the vicinity of the vehicle from map data of the map unit using the real-time position coordinates of the vehicle;
drawing a circle with a preset radius by taking the real-time position of the vehicle as the circle center to obtain a surrounding area of the vehicle;
obtaining the number D of roads in the surrounding area of the vehicle through the map information of the map unit;
Dividing the number of road segments in the surrounding area of the vehicle by the number D of roads to obtain road connectivity C;
acquiring the number T of vehicles passing through the surrounding areas of the vehicles in a specific time period before the current time point;
Acquiring an average speed V of a vehicle surrounding area in a specific time period before a current time point;
counting the historical accident times A of the surrounding area of the vehicle;
Setting a first threshold corresponding to the number T of vehicles, a second threshold corresponding to the average speed V and a third threshold corresponding to the number A of historical accidents based on the historical data;
setting a fourth threshold corresponding to the number D of the roads and a fifth threshold corresponding to the connectivity C of the roads;
And judging whether the vehicle belongs to a remote area and an unknown path or an urban road or a road section frequently driven according to the road number D, the road connectivity C, the vehicle number T, the average speed V, the historical accident number A and the corresponding threshold value.
Preferably, the specific way of determining whether the vehicle belongs to a remote area and an unknown path or an urban road or a road section driven frequently is as follows:
if the number T of vehicles in the area around the vehicles is greater than a first threshold value and the average speed V is greater than a second threshold value, the urban road possibility is divided by one;
If the number A of historical accidents in the area around the vehicle is smaller than a third threshold value, the urban road possibility is added by one score;
if the number D of roads in the area around the vehicle is larger than the fourth threshold value and the connectivity C of the roads is larger than the fifth threshold value, the urban road possibility is divided into two parts;
If the number T of vehicles in the area around the vehicles is smaller than the first threshold value and the average speed V is smaller than the second threshold value, the possibility of the remote area is divided into two parts;
If the number A of historical accidents in the surrounding area of the vehicle is larger than a third threshold value, the possibility of the remote area is divided into two parts;
If the number D of roads in the area around the vehicle is smaller than the fourth threshold value and the connectivity C of the roads is smaller than the fifth threshold value, the probability of the remote area is divided into one part;
If the urban road possibility is greater than or equal to three, judging the urban road or the road section frequently driven;
If the likelihood of the remote area is greater than or equal to three minutes, it is determined that the remote area or the path with less historical driving data.
Preferably, the specific way for determining whether the vehicle belongs to a remote area and an unknown path or an urban road or a road section driven frequently further comprises:
if the number T of vehicles in the area around the vehicles is greater than a first threshold value and the average speed V is less than a second threshold value, the urban road possibility is divided into two parts;
If the number T of vehicles in the area around the vehicles is smaller than the first threshold value and the average speed V is larger than the second threshold value, the possibility of the remote area is divided into two parts;
If the number D of roads in the area around the vehicle is larger than the fourth threshold value and the connectivity C of the roads is the fifth threshold value, the urban road possibility is divided into two parts;
If the number of roads D in the area around the vehicle is smaller than the fourth threshold value and the road connectivity C is larger than the fifth threshold value, the likelihood of the remote road is increased by a fraction.
Preferably, the specific steps of the decision unit outputting the emergency decision signal are as follows:
Acquiring vehicle surrounding environment information of the sensing module, wherein the vehicle surrounding environment information comprises image information, weather information, road surface state information and traffic rule information of the surrounding of a vehicle;
If the image information of the vehicle running path direction has an obstacle, generating an emergency decision signal and transmitting the emergency decision signal;
The vehicle surrounding environment information further comprises a laser radar, and when the image information identifies an obstacle, the information of the laser radar is used for verification to confirm whether the obstacle exists;
if the weather information is abnormal, namely a local weather forecast issues an early warning signal or road surface state information is abnormal, generating a second-class emergency decision signal and transmitting the second-class emergency decision signal;
Further, if the local weather forecast issues an early warning signal or a heavy rain or strong wind weather is monitored, whether the weather information is correct or not is verified through the road surface state information;
And according to the traffic rule information, three types of emergency decision signals are issued.
Preferably, when the control unit receives the high-speed mode decision signal of the decision unit, the specific working mode of switching to the first control state is as follows:
Obtaining an initial highest speed limit value H and a speed increase value J of the vehicle, obtaining a new speed limit value H1 according to the initial highest speed limit value H and the speed increase value J, and adapting to the requirement of high-speed running by improving the speed limit;
And calculating and obtaining new vehicle acceleration N1 according to a formula N1=N×k, wherein N is initial acceleration, k is an acceleration adjustment coefficient determined according to vehicle performance, and adjusting the vehicle acceleration N1 to change a vehicle accelerator response curve.
Preferably, when the control unit receives the security mode decision signal of the decision unit, the specific working mode of switching to the second control state is as follows:
obtaining a speed reduction value M of the vehicle, subtracting the speed reduction value M from an initial highest speed limit value H to obtain a new speed limit value H2, and reducing the speed limit value;
The method comprises the steps of obtaining initial information acquisition frequency G of the sensing module, obtaining new material frequency G1 through multiplying the initial information acquisition frequency G by an adjustment coefficient J, and improving environment sensing capability through improving the sampling rate of sensor data of the sensing module.
Preferably, the specific working mode of switching to the emergency mode control state when the decision unit outputs the emergency decision signal is:
When the control unit receives an emergency decision signal, the control unit immediately controls the vehicle to brake, stop or turn;
When the control unit receives the two kinds of emergency decision signals, the new speed limit H2 is obtained by subtracting the emergency speed reduction value F from the initial highest speed limit H, and the speed is further reduced, wherein in the embodiment, the emergency speed reduction value F can be set by a user or a manufacturer, and can be 60 km/H;
And when the control unit receives the three types of emergency decision signals, the speed limit or the line limit rule of the traffic rule information is read to correspondingly control the vehicle.
Preferably, the specific working mode of the communication collaboration module in the initial situation is as follows:
Configuring communication parameters according to the current position and the running state of the vehicle;
Exchanging position, speed and running direction information with surrounding vehicles, and exchanging traffic rules and road condition information with traffic signal lamps and road side units;
receiving a control decision, in particular a high speed mode, a safe mode or an emergency mode, from a decision unit;
based on the control decisions, the collaboration state with surrounding vehicles and infrastructure is adjusted.
Preferably, the specific operation of the communication collaboration module further includes:
After the decision unit outputs an emergency decision signal, broadcasting emergency information;
But also for receiving emergency information from other vehicles or infrastructure and taking corresponding emergency action.
The method has the beneficial effects that the adaptability of the unmanned automobile under different environmental conditions is improved by integrating various sensors and advanced decision algorithms, particularly under complex or rugged road conditions, the unmanned automobile can accurately identify and manage various traffic participants including pedestrians, bicycles, tricycles, automobiles and animals, so that the unmanned automobile can be intelligently switched between a high-speed mode and a safe mode according to real-time environmental changes and traffic conditions, and the driving safety in a complex traffic environment is ensured.
Detailed Description
In the practical use process, however, the unmanned automobile must be able to accurately identify and manage various traffic participants including pedestrians, bicycles, tricycles, automobiles and animals, and the complexity and unpredictability of traffic conditions cause difficulties for the unmanned automobile, especially under complex or rough road conditions;
moreover, unmanned vehicles are mainly tested and applied in limited road sections and environments, have limited free driving space, and can have potential safety hazards when encountering emergency situations and extreme weather.
As shown in FIG. 1, the unmanned vehicle control system based on the multi-sensor fusion technology comprises a sensing module, a control module and a control module, wherein the sensing module is used for acquiring and transmitting the information of the surrounding environment of a vehicle;
In this embodiment, the data from the various sensors such as the laser radar, the camera, the millimeter wave radar, the GPS, the I MU and the like are fused to realize the real-time acquisition of the surrounding environment information of the vehicle;
The specific vehicle surrounding environment information comprises image information of the surrounding of the vehicle, weather information in the running process of the vehicle, road surface condition information of a running area of the vehicle, traffic rule information of the running area of the vehicle and the like;
in this embodiment, image information around the vehicle, including road signs, traffic signals, pedestrians, vehicles, and the like, may be collected by a high-definition camera;
Weather information such as rainfall, snowfall, temperature, humidity and the like is collected by using a weather sensor so as to adapt to driving under different weather conditions;
analyzing road surface conditions such as wet skid, potholes, icing and the like through a road surface condition sensor (such as a wheel speed sensor and an accelerometer) and a camera;
Identifying traffic signs and signals by visual sensors and obtaining real-time traffic rule information by V2X communication (communication between the vehicle and the infrastructure);
The map fusion module comprises a map unit and a positioning fusion unit, wherein the map unit is used for acquiring map information near a vehicle through a GPS, and the positioning fusion unit judges whether the vehicle belongs to a remote area, an unknown path or an urban road or a road section driven frequently through the map information on the GPS and historical vehicle driving data and transmits a judging result;
The driving control module comprises a decision unit and a control unit, wherein the decision unit is used for receiving the vehicle surrounding information of the perception module and the judgment result of the positioning fusion unit, outputting a control decision and transmitting the control decision to the control unit;
The specific steps of the output control decision are as follows:
When the positioning fusion unit judges that the vehicle is on an urban road or a road section driven frequently through GPS and historical data, the decision unit outputs a high-speed mode decision signal;
when the positioning fusion unit judges that the vehicle is in a remote area or a path with less historical driving data, the decision unit outputs a safety mode decision signal;
monitoring the surrounding environment information of the vehicle of the sensing module, and outputting an emergency decision signal by the decision unit when the emergency signal is monitored;
The control unit is used for adjusting parameters when the vehicle runs and switching control states according to control decisions of the decision unit;
the control unit comprises a first control state and a second control state;
When the control unit receives the high-speed mode decision signal of the decision unit, the control unit is switched to a first control state, wherein in the first control state, the control unit adjusts the running parameters of the vehicle, such as improving the speed limit, optimizing the acceleration and the steering response, so as to adapt to the requirement of high-speed running;
When the control unit receives the safety mode decision signal of the decision unit, the control unit is switched to a second control state, wherein in the second control state, the control unit reduces the speed limit of the vehicle, and increases the monitoring frequency and sensitivity of the sensor so as to improve the perceptibility of the sensor to the surrounding environment;
The control unit also comprises an emergency control state, and is switched to the emergency mode control state when the decision unit outputs an emergency decision signal, wherein in the emergency mode, the control unit adopts emergency danger avoiding measures such as emergency braking and emergency obstacle avoiding operation, and meanwhile, a dangerous warning lamp can be started to remind other vehicles and pedestrians;
And the communication coordination module is used for realizing communication between vehicles and between the vehicles and the infrastructure, and adjusting coordination states according to control decisions of the decision unit. It should be noted that, according to the control decision of the decision unit, the cooperative state with other vehicles and infrastructure is adjusted to optimize traffic flow and improve safety, and in an emergency situation, emergency information is broadcast through the vehicle and infrastructure communication system to remind surrounding vehicles and traffic participants.
As an alternative embodiment, the positioning fusion unit works in the following manner:
Acquiring real-time position coordinates of the vehicle through a GPS receiver, and retrieving map information of the vicinity of the vehicle from map data of the map unit using the real-time position coordinates of the vehicle;
drawing a circle with a preset radius by taking the real-time position of the vehicle as the circle center to obtain a surrounding area of the vehicle;
obtaining the number D of roads in the surrounding area of the vehicle through the map information of the map unit;
Dividing the number of road segments in the surrounding area of the vehicle by the number D of roads to obtain road connectivity C;
the number T of vehicles passing through the surrounding areas of the vehicles in the characteristic time period before the current time point is obtained, wherein the characteristic time period can be one week, one day or one month in the embodiment;
It should be further noted that, by using video monitoring data, the vehicle monitoring and counting are performed by a computer vision technology (such as OpenCV), and the specific steps include:
extracting frames from the video stream, and converting each frame image into a gray level image;
Applying a background subtraction method (such as MOG2 algorithm) to separate out the foreground, i.e. moving vehicle;
Morphological processing of the separated foreground, such as erosion, dilation and closure operations, to remove noise and fill voids within the vehicle contour;
monitoring the contour in the processed image, calculating the area of the contour, and filtering out the contour with too small area to exclude non-vehicle targets;
counting the number of vehicles passing through a specific area in a specific time period to obtain T;
The method comprises the specific steps of obtaining the average speed V of the surrounding area of the vehicle in a specific time period before the current time point, wherein the speed is calculated by analyzing the time difference of the vehicle passing through the specific monitoring area, and the specific steps comprise:
installing a speed monitoring device, such as a radar gun or a laser velocimeter, at a specific location on the roadway, or using video analysis techniques to track the time of the vehicle passing a specific point;
Recording the time stamp of each vehicle passing through the monitoring area;
Calculating the time difference of each vehicle passing through the area, and calculating the average speed according to the distance;
Averaging the speeds of all vehicles to obtain V;
The method comprises the steps of counting the historical accident times A of the surrounding area of the vehicle, and inquiring the historical accident data in a specific area from an accident record database of a traffic management department, wherein the steps comprise:
Accessing an accident record database provided by a traffic management department;
inquiring all accidents recorded in the area according to the position and the time range of the vehicle;
counting the total number of accidents in the query result, namely A;
In this embodiment, the average value of the historical data of the road segments in the city before the current time period can be used as the threshold value of the surrounding area of the vehicle;
Setting a fourth threshold value corresponding to the number of roads D and a fifth threshold value corresponding to the number of roads C, wherein the threshold value of the number of roads D can be obtained by multiplying the average value of the number of roads per square kilometer in the city where the vehicle is located by the surrounding area of the vehicle, and the threshold value of the number of roads C can be set to be the minimum proportion for ensuring navigation connectivity and can be set to be 0.8 or 0.9 so as to ensure that most roads are communicated;
And judging whether the vehicle belongs to a remote area and an unknown path or an urban road or a road section frequently driven according to the road number D, the road connectivity C, the vehicle number T, the average speed V, the historical accident number A and the corresponding threshold value.
As an alternative embodiment, the specific way of determining whether the vehicle belongs to a remote area and an unknown path or an urban road or a road section driven frequently is as follows:
if the number T of vehicles in the area around the vehicles is larger than a first threshold value and the average speed V is larger than a second threshold value, the probability of the urban road is divided into a plurality of parts;
If the number of historic accidents A in the area around the vehicle is smaller than the third threshold value, the probability of the urban road is divided into a plurality of parts, and the fact that the accident rate of the urban road is far lower than that of a remote area and an unknown path on the basis of unmanned driving is needed to be explained;
If the number D of the roads in the area around the vehicle is larger than a fourth threshold value and the connectivity C of the roads is larger than a fifth threshold value, the probability of the urban roads is divided into a plurality of parts;
If the number T of vehicles in the area around the vehicles is smaller than a first threshold value and the average speed V is smaller than a second threshold value, the possibility of the remote area is divided into a plurality of parts;
if the number A of historical accidents in the surrounding area of the vehicle is larger than a third threshold value, the possibility of the remote area is divided into two parts; it should be noted that a high accident rate may mean that traffic management in the area is not perfect, and drivers may not follow traffic rules too much, which is more common in remote areas or paths with less historical driving data;
If the number D of the roads in the area around the vehicle is smaller than the fourth threshold value and the connectivity C of the roads is smaller than the fifth threshold value, the probability of the remote area is divided into a plurality of parts;
it should be noted that, the case of equality is not considered, because the number of samples is small, if the number of roads D, the number of roads connectivity C, the number of vehicles T, the average speed V, and the number of historic accidents a are equal to the corresponding threshold values, it is judged as being greater than;
If the urban road possibility is greater than or equal to three, judging the urban road or the road section frequently driven;
If the likelihood of the remote area is greater than or equal to three minutes, it is determined that the remote area or the path with less historical driving data.
As an alternative embodiment, the specific way for judging whether the vehicle belongs to a remote area and an unknown path or an urban road or a road section driven frequently further comprises:
If the number T of vehicles in the area around the vehicle is greater than the first threshold value and the average speed V is less than the second threshold value, the urban road possibility is divided by a fraction, and it should be noted that this may indicate that the road is busy, but the vehicle is traveling at a slower speed, possibly due to traffic congestion or road condition limitation. This may mean that the road section is an urban road, but there may be traffic problems;
If the number T of vehicles in the area around the vehicle is smaller than the first threshold value and the average speed V is larger than the second threshold value, the possibility of the remote area is divided by a fraction, and it should be noted that this situation may indicate that the road section is not busy, but the vehicle can run at a high speed, possibly because the road is open or the road condition is good. This may mean that the road segment is a remote road, but the traffic flow is not large;
If the number D of the roads in the area around the vehicle is larger than the fourth threshold value and the connectivity C of the roads is the fifth threshold value, the probability of the urban roads is divided into a plurality of parts;
If the number of roads D in the area around the vehicle is smaller than the fourth threshold value and the road connectivity C is larger than the fifth threshold value, the likelihood of the remote road is increased by a fraction. This may indicate that although the number of roads is not large, the connectivity is good, which may be a feature of the roads in a remote area, but the good connectivity may mean that there is some traffic flow in that area;
it should be noted that, the above method is used for determining the score in the special case.
As an alternative embodiment, the specific steps of the decision unit outputting an emergency decision signal are as follows:
Acquiring vehicle surrounding environment information of the sensing module, wherein the vehicle surrounding environment information comprises image information, weather information, road surface state information and traffic rule information of the surrounding of a vehicle;
If the image information of the vehicle running path direction has an obstacle, generating an emergency decision signal and transmitting the emergency decision signal, wherein the situation needs to stop braking or steering the vehicle immediately;
The vehicle surrounding environment information further comprises a laser radar, and when the image information identifies an obstacle, the information of the laser radar is used for verification to confirm whether the obstacle exists;
for example, a lidar confirms the three-dimensional position of an obstacle through point cloud data, whereas a millimeter wave radar verifies the speed of the obstacle through doppler effect;
If the weather information is abnormal, namely a local weather forecast issues an early warning signal or road surface state information is abnormal, a second type of emergency decision signal is generated and transmitted;
Further, if the local weather forecast issues an early warning signal or a heavy rain or strong wind weather is monitored, whether the weather information is correct or not is verified through the road surface state information;
It should be noted that, for weather information and road surface state information, data of a weather sensor and a road surface state sensor (such as a wheel speed sensor, an accelerometer) are fused to determine whether an abnormality exists. For example, if a weather sensor detects heavy rain and a road sensor detects slippery road, the information would be fused to generate and transmit a second type of emergency decision signal;
and according to the traffic rule information, three types of emergency decision signals are issued. The speed limit data of the vehicle is changed according to the local traffic rules, so that overspeed of the vehicle is avoided.
As an alternative embodiment, when the control unit receives the high-speed mode decision signal of the decision unit, the specific working mode of switching to the first control state is as follows:
Obtaining an initial highest speed limit value H and a speed increase value J of the vehicle, obtaining a new speed limit value H1 according to the initial highest speed limit value H and the speed increase value J, and adapting to the requirement of high-speed running by improving the speed limit; it should be noted that, in the first control state, the maximum speed limit of the vehicle may be appropriately increased by setting a maximum speed limit to be set by the vehicle manufacturer, in this embodiment, the initial maximum speed limit H may be 100 km/hour, the speed increase J may be set according to the vehicle user, and the maximum value may not exceed 40 km/hour;
And calculating and obtaining new vehicle acceleration N1 according to a formula N1=N×k, wherein N is initial acceleration, k is an acceleration adjustment coefficient determined according to vehicle performance, and adjusting the vehicle acceleration N1 to change a vehicle accelerator response curve. It should be noted that, in this embodiment, both the initial acceleration and the acceleration adjustment coefficient may be obtained according to the vehicle manufacturer setting;
The vehicle can better adapt to different road conditions, such as expressways and urban roads, by adjusting the speed limit and the acceleration, and optimize the throttle response, namely adjusting the acceleration can change the throttle response curve, so that the vehicle accelerates more smoothly and the driving comfort is improved;
in the case where rapid acceleration or deceleration is required, adjusting the acceleration can increase the reaction speed of the vehicle, thereby improving safety.
As an alternative embodiment, when the control unit receives the security mode decision signal of the decision unit, the specific working mode of switching to the second control state is as follows:
obtaining a speed reduction value M of the vehicle, subtracting the speed reduction value M from an initial highest speed limit value H to obtain a new speed limit value H2, and reducing the speed limit value;
The method comprises the steps of obtaining initial information acquisition frequency G of the sensing module, obtaining new material frequency G1 through multiplying the initial information acquisition frequency G by an adjustment coefficient J, and improving environment sensing capability through improving the sampling rate of sensor data of the sensing module. It should be noted that, in this embodiment, the speed reduction value M of the vehicle may be set by a manufacturer and may also be adjusted according to a user, the adjustment coefficient J may be 1.203 in this embodiment, and a specific value is set according to the manufacturer of the vehicle, but the value range is between 1 and 2, so as to increase the monitoring frequency of the sensor in the sensing module.
As an alternative embodiment, the specific working mode of switching to the emergency mode control state when the decision unit outputs the emergency decision signal is as follows:
When the control unit receives an emergency decision signal, the control unit immediately controls the vehicle to brake, stop or turn;
When the control unit receives the two kinds of emergency decision signals, the new speed limit H2 is obtained by subtracting the emergency speed reduction value F from the initial highest speed limit H, and the speed is further reduced, wherein in the embodiment, the emergency speed reduction value F can be set by a user or a manufacturer, and can be 60 km/H;
And when the control unit receives the three types of emergency decision signals, the speed limit or the line limit rule of the traffic rule information is read to correspondingly control the vehicle.
By means of the hierarchical response mechanism of the emergency decision signal, the unmanned vehicle can more accurately and rapidly cope with various emergency situations, and therefore driving safety and efficiency are remarkably improved. Specifically, when an obstacle which directly threatens the driving safety is detected, one type of emergency decision signal ensures that the vehicle can immediately take measures of braking, parking or steering to avoid the obstacle, and collision is effectively avoided. In the face of severe weather or road conditions, the two types of emergency decision signals enhance the stability and controllability of the vehicle by reducing the speed of the vehicle, and reduce the risk of accidents. The three types of emergency decision signals ensure that vehicles strictly adhere to traffic rules, avoid being penalized due to overspeed or violation of limit rules, and ensure driving safety.
As an alternative embodiment, the specific working mode of the communication cooperative module in the initial condition is as follows:
The communication cooperative module configures communication parameters according to the current position (such as city center, expressway and the like) and the running state (such as speed and direction) of the vehicle before the unmanned vehicle starts running, which comprises setting communication range to ensure effective communication between the vehicle and surrounding vehicles and infrastructure, setting communication frequency to adapt to different communication environments and reduce interference, wherein the configuration of the parameters is dynamic and can be adjusted according to the running environment of the vehicle;
The communication coordination module enables the vehicle to exchange data with surrounding vehicles (V2V) and infrastructure (V2I), and the information comprises the position, the speed, the running direction and the like of the vehicle, which are essential for avoiding collision and optimizing traffic flow. Meanwhile, traffic rules and road condition information are exchanged with the traffic signal lamps and the road side units, vehicles are helped to follow the traffic rules, congestion areas are avoided, and an optimal route is selected;
The communication cooperative module receives the control decisions from the decision unit, wherein the decisions can be the high-speed mode, the safe mode or the emergency mode, and each mode corresponds to different driving strategies and behaviors such as speed limitation, acceleration and adjustment of steering response;
Based on the control decisions, the collaboration state with surrounding vehicles and infrastructure is adjusted. It should be noted that, according to the control decision received from the decision unit, the communication coordination module adjusts the coordination state with the surrounding vehicles and the infrastructure;
for example, in a high speed mode, the vehicle may need to maintain a greater safety distance from the lead vehicle, and in a safety mode, the vehicle may need to decrease speed and increase the frequency of monitoring by the sensor.
As an alternative embodiment, the specific operation of the communication cooperation module further comprises:
After the decision unit outputs an emergency decision signal, broadcasting emergency information;
When the decision unit outputs an emergency decision signal, the communication cooperative module is responsible for broadcasting emergency information such as vehicle faults, accidents or environment anomalies to surrounding vehicles and infrastructure, and the broadcasting of the information can help surrounding traffic participants to respond in time so as to avoid further accidents;
But also for receiving emergency information from other vehicles or infrastructure and taking corresponding emergency action.
It should be noted that, the communication coordination module is not only required to broadcast emergency information, but also is required to receive the emergency information from other vehicles or infrastructures, and take emergency measures according to the information;
For example, if emergency information for road construction ahead is received, the vehicle may need to slow down or change roads;
The communication coordination module ensures that the unmanned vehicle can maintain effective communication and coordination with the surrounding environment and other traffic participants under various conditions, thereby improving driving safety and traffic efficiency.
Principle of operation
The adaptability of the unmanned automobile under different environmental conditions is improved through integrating various sensors and advanced decision algorithms, particularly under complex or rugged road conditions, the unmanned automobile can accurately identify and manage various traffic participants including pedestrians, bicycles, tricycles, automobiles and animals, and the unmanned automobile can be intelligently switched between a high-speed mode and a safe mode according to real-time environmental changes and traffic conditions, so that the driving safety in the complex traffic environment is ensured.
The above is only a preferred embodiment of the present invention, and the protection scope of the present invention is not limited to the above examples, and all technical solutions belonging to the concept of the present invention belong to the protection scope of the present invention. It should be noted that modifications and adaptations to those skilled in the art without departing from the principles of the present invention are intended to be within the scope of the present template.