A cruise following distance adjustment method and device

Abstract

The present application provides a cruise following distance adjustment method and device. In this method, on the basis of determining the initial following distance based on the gear set by the target vehicle and the speed of the target vehicle, the environment related to the following performance of the target vehicle is monitored to obtain environmental information, and the initial following distance is adjusted based on the environmental information. By combining the environmental information to adjust the following distance, the following distance adjustment is made more accurate, the following is ensured to be safer, and the following performance of the adaptive cruise system is improved.

Description

Technical Field

[0001] The present application relates to the field of intelligent transportation technology, and in particular to a method and device for adjusting a cruise-following distance. Background Art

[0002] Adaptive Cruise Control (ACC) is an intelligent, automatic control system and an active safety technology. It's an evolution of existing cruise control technology. ACC builds on traditional cruise control by using radar to detect the relative distance and speed of the vehicle ahead and proactively control the vehicle's speed to achieve automatic following cruise control. The system automatically switches between cruise control and following cruise control depending on the presence of a vehicle ahead.

[0003] Among them, in the adaptive cruise control system, a following distance adjustment switch is generally set. The following distance adjustment switch generally has 3-7 gears. After the user selects the gear, the adaptive cruise control system can adjust the following distance according to the gear selected by the user and the current speed of the vehicle to achieve following the vehicle.

[0004] However, the performance of the adaptive cruise control system in following the vehicle still needs to be improved. Summary of the Invention

[0005] To solve the above technical problems, the present invention provides a method and device for adjusting the cruise following distance to improve the following performance of the adaptive cruise control system. The technical solution is as follows:

[0006] A method for adjusting a cruise following distance comprises:

[0007] Obtaining an initial following distance of a target vehicle, wherein the initial following distance is determined based on a gear position set for the target vehicle and a speed of the target vehicle;

[0008] Monitoring an environment associated with the following performance of the target vehicle to obtain environmental information;

[0009] The initial following distance is adjusted based on the environmental information.

[0010] A cruise following distance adjustment device, characterized by comprising:

[0011] an acquisition module, configured to acquire an initial following distance of a target vehicle, wherein the initial following distance is determined based on a gear position set for the target vehicle and a speed of the target vehicle;

[0012] An environment monitoring module, configured to monitor an environment associated with the following performance of the target vehicle and obtain environmental information;

[0013] An adjustment module is used to adjust the initial following distance based on the environmental information.

[0014] Compared with the prior art, the present invention has the following advantages:

[0015] In the present application, on the basis of determining the initial following distance based on the gear set by the target vehicle and the speed of the target vehicle, the environment related to the following performance of the target vehicle is monitored to obtain environmental information, and based on the environmental information, the initial following distance is adjusted, so that the following distance can be adjusted in combination with the environmental information, making the following distance adjustment more accurate, ensuring safer following, and improving the following performance of the adaptive cruise system. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0017] Figure 1 This is a flowchart of Example 1 of the cruise following distance adjustment method provided by the present application;

[0018] Figure 2 This is a schematic diagram of a traffic flow scenario with vehicles in all three lanes provided by this application;

[0019] Figure 3 This is a schematic diagram of a traffic flow scenario provided by this application with vehicles in the vehicle and the lane to the right of the vehicle;

[0020] Figure 4 This is a schematic diagram of a traffic flow scenario provided by this application with a vehicle in the vehicle and the left lane of the vehicle;

[0021] Figure 5 This is a flowchart of Example 2 of the cruise following distance adjustment method provided by this application;

[0022] Figure 6 This is a flowchart of Example 3 of the cruise following distance adjustment method provided by this application;

[0023] Figure 7 This is a flowchart of Example 4 of the cruise following distance adjustment method provided by this application;

[0024] Figure 8 This is a logical structure diagram of a cruise following distance adjustment device provided by this application. DETAILED DESCRIPTION

[0025] The following will be combined with the drawings in the embodiments of this application to clearly and completely describe the technical solutions in the embodiments of this application. Obviously, the embodiments described are only part of the embodiments of this application, not all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.

[0026] like Figure 1 As shown, it is a flow chart of Example 1 of a cruise following distance adjustment method provided by the present application, which may include the following steps:

[0027] Step S11: Acquire an initial following distance of a target vehicle, where the initial following distance is determined based on a gear position set for the target vehicle and a speed of the target vehicle.

[0028] In this embodiment, the process of obtaining the initial following distance of the target vehicle may include but is not limited to:

[0029] Using the first relation Calculate the initial following distance of the target vehicle;

[0030] Among them, D drvrtgt is the initial following distance of the target vehicle, v ego is the speed of the target vehicle, It is the following time coefficient corresponding to the target vehicle, which is related to the speed of the target vehicle and the gear set for the target vehicle. SetDistLvl_indx is the gear set for the target vehicle, and d_0 represents the minimum following distance.

[0031] Step S12: Monitor the environment associated with the following performance of the target vehicle to obtain environmental information.

[0032] In this embodiment, the environment associated with the following performance of the target vehicle may include any one or more of: rainy and snowy environment, road type, slope grade, dark light environment, type of vehicle ahead, and traffic flow conditions.

[0033] Monitoring the environment associated with the following performance of the target vehicle to obtain environmental information may include but is not limited to:

[0034] S121, using sensors of the target vehicle related to the rain and snow environment to collect information, and using the collected information as rain and snow environment information;

[0035] And / or, S122, estimating the road type of the area where the target vehicle is located to obtain road type information;

[0036] And / or, S123, estimating the slope grade of the area where the target vehicle is located to obtain slope grade information;

[0037] And / or, S124, determining whether the target vehicle is in a dark light environment, and obtaining a dark light environment determination result;

[0038] And / or, S125, identifying the type of the vehicle in front of the target vehicle to obtain the type information of the vehicle in front;

[0039] And / or, S126, determining the traffic flow condition of the lane associated with the target vehicle.

[0040] In this embodiment, collecting information related to the rain and snow environment using the target vehicle's sensors may include:

[0041] S1211. Collect information using the rain and snow sensor of the target vehicle, and collect a wiper gear signal and an actual wiper frequency signal using the wiper sensor of the target vehicle.

[0042] In this embodiment, estimating the road type of the area where the target vehicle is located to obtain road type information may include:

[0043] S1221. Obtaining the ADAS internal road adhesion coefficient;

[0044] In this embodiment, the ADAS internal path adhesion coefficient can be obtained through a road surface recognition algorithm. The road surface recognition algorithm can be a road surface recognition algorithm in the prior art and will not be described in detail here.

[0045] S1222: Determine whether the magnitude relationships between the ADAS internal road surface adhesion coefficient and different adhesion coefficient monitoring thresholds conform to the set magnitude relationships corresponding to the adhesion coefficient monitoring thresholds;

[0046] If so, execute step S1223.

[0047] S1223, determining whether the duration of the set magnitude relationship corresponding to the adhesion coefficient monitoring threshold satisfies the set duration;

[0048] If satisfied, execute step S1224.

[0049] S1224: Obtain road surface type information corresponding to the adhesion coefficient monitoring threshold.

[0050] Steps S1221-S1224 can be executed by the following relationship:

[0051]

[0052] Among them, RoadCof_sg represents the road adhesion coefficient inside the ADAS, and RoadCof_indx_u8 represents the road type information. respectively represent different adhesion coefficient monitoring thresholds, t hi , t Mid , t Le respectively represent the duration corresponding to the set size relationship.

[0053] The adhesion coefficient monitoring threshold can be specifically calibrated through actual vehicle tests according to needs.

[0054] In this embodiment, estimating the ramp grade of the area where the target vehicle is located to obtain ramp grade information may include:

[0055] S1231. Obtain the slope value estimated in real time for the area where the target vehicle is located.

[0056] S1232. Respectively determine whether the size relationship between the slope value and different ramp thresholds conforms to the set size relationship corresponding to the ramp threshold.

[0057] If it conforms, execute step S1233.

[0058] S1233. Obtain the ramp grade information corresponding to the ramp threshold.

[0059] Steps S1231 - S1233 can be executed through the following relational expressions:

[0060]

[0061] Among them, abs() represents the absolute value, P_MinSlp_sg, P_MidSlp_sg, and P_MaxSlp_sg respectively represent different ramp thresholds, where 0 < P_MinSlp_sg < P_MidSlp_sg < P_MaxSlp_sg, and SldGrd_indx_u8 represents the ramp grade information.

[0062] In this embodiment, determining whether the target vehicle is in a dark light environment to obtain a dark light environment judgment result may include:

[0063] S1241. Collect the status information of the headlights of the target vehicle, the time information inside the target vehicle, and the information collected by the light sensor of the target vehicle.

[0064] S1242. Determine whether the target vehicle is in a dark light environment based on the state information of the target vehicle's headlights, the time information in the target vehicle, and information collected by the light sensor of the target vehicle, and obtain a dark light environment determination result.

[0065] In this embodiment, identifying the type of the vehicle in front of the target vehicle and obtaining the front vehicle type information may include:

[0066] S1251. Based on the front-view camera of the target vehicle, identify the type of the vehicle in front of the target vehicle and obtain the front vehicle type information.

[0067] In this embodiment, determining the traffic flow condition of the lane associated with the target vehicle may include:

[0068] S1261. Monitor the traffic speed changes of the lane containing the target vehicle and its adjacent lanes, and obtain the merging information of the vehicle ahead of the target vehicle from map information.

[0069] S1262: If the merging information of the vehicle ahead of the target vehicle indicates that there is no vehicle merging ahead, determine that the traffic flow condition of the lane associated with the target vehicle is normal traffic flow.

[0070] Normal traffic flow can be understood as: the overall traffic flow is not congested, and there is no need to pay attention to the congestion of the lane of this vehicle. At this time, the design is that the time distance of this vehicle is not compensated, which does not affect the normal following choice.

[0071] S1263: If the merging information of the vehicle ahead of the target vehicle indicates that there is a vehicle merging ahead, and there is a vehicle merging within the vehicle time range, determine that the traffic flow operation status of the lane associated with the target vehicle is side lane merging congestion.

[0072] The congestion of merging into the side lane can be understood as: if it is a merging condition of merging into the side lane, you can increase the distance and effectively avoid it.

[0073] S1264. If the merging information of the vehicle ahead of the target vehicle indicates that there is a vehicle merging from at least one lane other than the lane to which the target vehicle belongs, and there is no vehicle merging within the vehicle time range, and there is a vehicle ahead of the target vehicle in the lane containing the target vehicle, and the average traffic flow speed thereof is less than the speed limit value within the set time, then it is determined that the traffic flow operation condition of the lane associated with the target vehicle is normal congestion.

[0074] Ordinary congestion can be understood as: you need to shorten the distance between you and the car you are following to prevent being repeatedly cut in by cars in the adjacent lanes.

[0075] S1265. If the merging information of the vehicle in front of the target vehicle indicates that there is a vehicle merging from at least one lane other than the lane to which the target vehicle belongs, and there is no vehicle merging within the vehicle time range, and there is a vehicle in front of the target vehicle in the lane containing the target vehicle, and the average traffic flow speed of the vehicle is not less than the speed limit within the set time, then it is determined that the traffic flow operation condition of the lane associated with the target vehicle is normal traffic flow.

[0076] Now combined Figure 2-4 , steps S1361-S1265 are explained, as shown in FIG. Figure 2 As shown, when the vehicles marked as 03 and 05 (represented as vobj03 and vobj05) in the left lane (i.e., lane 1) of the vehicle do not merge into lane 2 (which can be represented as Trafc_jam_L(vobj03, vobj05) = false), and the vehicles marked as 04 and 06 (represented as vobj04 and vobj06) in the right lane (i.e., lane 3) of the vehicle do not merge into lane 2 (which can be represented as Trafc_jam_R(vobj04, vobj06) = false), the traffic flow operation condition of the lane associated with the vehicle is normal traffic flow (which can be represented as Trafc_indx_en = normal traffic flow).

[0077] When vehicles marked as 03 and 05 (represented as vobj03 and vobj05) in the left lane (i.e., lane 1) of this vehicle merge into lane 2 (which can be expressed as Trafc_jam_L(vobj03, vobj05) = true), and vehicles marked as 04 and 06 (represented as vobj04 and vobj06) in the right lane (i.e., lane 3) of this vehicle merge into lane 2 (which can be expressed as Trafc_jam_R(vobj04, vobj06) = true), and there is a vehicle merging within the vehicle time range (which can be expressed as LneMrge_bl = true), the traffic flow operation status of the lane associated with this vehicle is side lane merging congestion (which can be expressed as Trafc_indx_en = side lane merging congestion).

[0078] When vehicles marked as 03 and 05 (represented as vobj03 and vobj05) in the left lane (i.e., lane 1) of the vehicle merge into lane 2 (which can be represented as Trafc_jam_L(vobj03, vobj05) = true), and vehicles marked as 04 and 06 (represented as vobj04 and vobj06) in the right lane (i.e., lane 3) of the vehicle merge into lane 2 (which can be represented as Trafc_jam_R(vobj04, vobj06) = true), and there is no vehicle merging within the vehicle's time distance range (which can be represented as LneMrge_bl = false), the traffic flow operation condition of the lane associated with the vehicle is normal congestion (which can be represented as Trafc_indx_en = normal congestion).

[0079] like Figure 3 or Figure 4 As shown, when the merging information of the vehicle ahead of the target vehicle indicates that a vehicle is merging from at least one lane other than the lane to which the target vehicle belongs (expressed as [Trafc_jam_L(vobj03, vobj05)=true or Trafc_jam_R(vobj04, vobj06)=true]), and there is no vehicle merging within the vehicle time range (expressed as LneMrge_bl=false), and there is a vehicle ahead of the target vehicle in the lane containing the target vehicle, and the average traffic flow speed of the vehicle is less than the speed limit within the set time (expressed as Trafc_jam_ego(vobj01, vobj02)=true), the traffic flow operation condition of the lane associated with the target vehicle is normal congestion.

[0080] When the merging vehicle information ahead of the target vehicle indicates that a vehicle is merging from at least one lane other than the lane to which the target vehicle belongs (expressed as [Trafc_jam_L(vobj03, vobj05) = true or Trafc_jam_R(vobj04, vobj06) = true]), and no vehicle is merging within the vehicle headway range (expressed as LneMrge_bl = false), and there is a vehicle ahead of the target vehicle in the lane containing the target vehicle, and the average traffic flow speed of the vehicle is not less than the speed limit value within the set time (expressed as Trafc_jam_ego(vobj01, vobj02) = false), the traffic flow operation condition of the lane associated with the target vehicle is normal traffic flow.

[0081] Step S13: Adjust the initial following distance based on the environmental information.

[0082] Corresponding to the environmental information monitored in step S12, the initial following distance is adjusted based on the environmental information, which can be understood as: adjusting the initial following distance based on any one or more of rain and snow environment information, road type information, slope grade information, dark light environment judgment results, front vehicle type information and traffic flow conditions of the lane associated with the target vehicle.

[0083] Specifically, adjusting the initial following distance based on the environmental information may include:

[0084] S131. Determine a following distance compensation value in a rainy or snowy environment based on the rainy or snowy environment information;

[0085] And / or, S132, determining a road type following distance compensation value based on the road type information;

[0086] And / or, S133, determining a slope following distance compensation value based on the slope grade information;

[0087] And / or, S134, determining a following distance compensation value for a dark light environment based on the dark light environment determination result;

[0088] And / or, S135, determining a following distance compensation value associated with the type of the vehicle ahead based on the type of the vehicle ahead;

[0089] And / or, S136, determining a following distance compensation value associated with the traffic flow operation condition based on the traffic flow operation condition of the lane associated with the target vehicle;

[0090] S137. Compensate the initial following distance using the following distance compensation value for a rainy or snowy environment, and / or the following distance compensation value for a road surface type, and / or the following distance compensation value for a slope, and / or the following distance compensation value for a dark light environment, and / or the following distance compensation value associated with the type of vehicle ahead, and / or the following distance compensation value associated with the traffic flow condition.

[0091] Corresponding to step S1211, the process of determining the following distance compensation value in a rainy and snowy environment based on the rainy and snowy environment information may include:

[0092] S1311, determining whether the speed of the target vehicle is greater than a speed compensation threshold;

[0093] If it is greater, execute step S1332; if it is not greater, execute step S1334.

[0094] S1332: Searching a preset multidimensional table for a distance that matches the information collected by the rain and snow sensor, the wiper gear position signal, and the actual wiper frequency signal.

[0095] The pre-set multi-dimensional table can be obtained by actual vehicle calibration according to requirements.

[0096] S1333: Use the found distance as a following distance compensation value in rainy and snowy environments.

[0097] S1334: Set the value 0 as the following distance compensation value in rainy and snowy environments.

[0098] Steps S1311-S1314 can be executed by the following relationship:

[0099]

[0100] in, Indicates the information collected by the rain and snow sensor. Indicates the wiper gear signal. Indicates the actual frequency signal of the wiper, D wthsnsr It represents the following distance compensation value in rainy and snowy environments, WthSnsr_Spdthrd represents the speed compensation threshold, the unit of WthSnsr_Spdthrd can be m / s, and fun_wthSnsr() represents a function used to search for information in a pre-set multidimensional table.

[0101] Among them, the speed compensation threshold can be obtained by actual vehicle calibration according to needs.

[0102] Corresponding to steps S1221-S1224, determining the road type following distance compensation value based on the road type information may include:

[0103] S1321. Obtain the distance compensation time corresponding to the road surface type information.

[0104] S1322: Multiply the distance compensation time corresponding to the road surface type information by the speed of the target vehicle to obtain a road surface type following distance compensation value.

[0105] Steps S1321-S1322 can be executed by the following relationship:

[0106]

[0107] Among them, t MidCof and t LoCof They represent the time compensation time corresponding to different road type information, D RoadCof Indicates the road type following distance compensation value. The unit of the road type following distance compensation value can be m.

[0108] Corresponding to steps S1231-S1233, determining the slope following distance compensation value based on the slope grade information may include:

[0109] S1331. If the slope grade information indicates that the slope does not have the ability to affect the following performance of the target vehicle, a value of 0 is used as the slope following distance compensation value;

[0110] S1332. If the slope grade information indicates that the slope has the ability to affect the following performance of the target vehicle, obtain a following-stop distance compensation value corresponding to the slope grade information, and subtract the following-stop distance compensation value from the minimum following distance of the target vehicle to obtain a slope following distance compensation value.

[0111] Steps S1331-S1332 can be executed by the following relationship:

[0112]

[0113] Among them, P_d_MidSlp_sg and P_d_MaxSlp_sg represent different follow-stop distance compensation values, respectively. SlpGrd Indicates the slope following distance compensation value.

[0114] In this embodiment, the following stop distance compensation value can be obtained by actual vehicle calibration according to needs.

[0115] Corresponding to steps S1241-S1242, determining the dark light environment following distance compensation value based on the dark light environment judgment result may include:

[0116] S1341. If the dark light environment judgment result indicates that the target vehicle is in a dark light environment, obtain a distance compensation time in a dark light environment;

[0117] S1342: multiplying the distance compensation time in the dark light environment by the speed of the target vehicle by a result of a calculation, as a following vehicle distance compensation value in the dark light environment;

[0118] S1343: If the dark light environment judgment result indicates that the target vehicle is not in a dark light environment, a value of 0 is used as a following distance compensation value for a dark light environment.

[0119] Steps S1341-S1343 can be executed by the following relationship:

[0120]

[0121] Among them, t NgtDkIndicates the time distance compensation time in a dark light environment, and NgtDk_indx_bl indicates the dark light environment judgment result.

[0122] The time-to-distance compensation time in a dark light environment can be obtained through actual vehicle calibration according to needs.

[0123] Corresponding to step S1251, determining the following distance compensation value associated with the front vehicle type based on the front vehicle type information may include:

[0124] S1351. Determine whether the front vehicle represented by the front vehicle type information is a special vehicle;

[0125] If yes, execute step S1352; if no, execute step S1353.

[0126] Special vehicles may be, but are not limited to, trucks or special vehicles.

[0127] S1352. Obtain a time compensation coefficient for a special vehicle, and multiply the time compensation coefficient for the special vehicle by the target vehicle to obtain a result as a following distance compensation value associated with the type of the preceding vehicle.

[0128] S1353: Use the value 0 as the following distance compensation value associated with the type of the preceding vehicle.

[0129] Steps S1351-S1353 can be executed by the following relationship:

[0130]

[0131] Among them, t vehClas It represents the time compensation coefficient of special vehicles, and VehClas_indx_en represents the type information of the vehicle ahead.

[0132] Corresponding to steps S1261-S1265, determining the following distance compensation value associated with the traffic flow operation condition of the lane associated with the target vehicle may include:

[0133] S1361. If the traffic flow condition is normal, use a value of 0 as a following distance compensation value associated with the traffic flow condition.

[0134] S1362. If the traffic flow condition is normal congestion, multiply the congestion compensation time coefficient by the speed of the target vehicle to obtain a congestion compensation value, and subtract the congestion compensation value from 0 as the following distance compensation value associated with the traffic flow condition.

[0135] S1363: If the traffic flow operation condition is congestion due to merging into a side lane, a preset distance compensation value is used as a following distance compensation value associated with the traffic flow operation condition.

[0136] Furthermore, the congestion distance compensation value is as follows

[0137]

[0138] Among them, t veh_Trafc_jam A positive value is the congestion compensation time coefficient, which shortens the following distance by changing its sign. If the traffic is congested in the side lane, a fixed compensation value P_d_Trafc_jam_Comp_sg is added to increase the following distance and improve the safety of traffic merging.

[0139] In the present application, on the basis of determining the initial following distance based on the gear set by the target vehicle and the speed of the target vehicle, the environment related to the following performance of the target vehicle is monitored to obtain environmental information, and based on the environmental information, the initial following distance is adjusted, so that the following distance can be adjusted in combination with the environmental information, making the following distance adjustment more accurate, ensuring safer following, and improving the following performance of the adaptive cruise system.

[0140] As another optional embodiment of the present application, refer to Figure 5 , is a flow chart of a cruise following distance adjustment method embodiment 2 provided by this application. This embodiment is mainly a refinement of the cruise following distance adjustment method described in the above embodiment 1, such as Figure 5 As shown, the method may include but is not limited to the following steps:

[0141] Step S21: Acquire an initial following distance of a target vehicle, where the initial following distance is determined based on a gear position set for the target vehicle and a speed of the target vehicle.

[0142] The detailed process of step S21 can be found in the relevant introduction of step S11 in embodiment 1, and will not be repeated here.

[0143] Step S22: Utilize the target vehicle's sensors related to the rain and snow environment to collect information, use the collected information as rain and snow environment information, estimate the road surface type in the area where the target vehicle is located to obtain road surface type information, estimate the slope grade in the area where the target vehicle is located to obtain slope grade information, determine whether the target vehicle is in a dark light environment, obtain a dark light environment determination result, identify the type of the vehicle in front of the target vehicle, obtain the front vehicle type information, and determine the traffic flow operation status of the lane associated with the target vehicle.

[0144] In this embodiment, the target vehicle's sensors related to the rain and snow environment are used to collect information, and the collected information is used as the detailed process of the rain and snow environment information, or the road type of the area where the target vehicle is located is estimated to obtain road type information, or the slope grade of the area where the target vehicle is located is estimated to obtain slope grade information, or it is determined whether the target vehicle is in a dark light environment to obtain a dark light environment judgment result, or the type of the vehicle in front of the target vehicle is identified to obtain the front vehicle type information, or the detailed process of determining the traffic flow operation status of the lane associated with the target vehicle can be found in the relevant introduction in Example 1 and will not be repeated here.

[0145] Step S22 is a specific implementation of step S12 in Example 1.

[0146] Step S23: Determine a following distance compensation value for a rainy and snowy environment based on the rainy and snowy environment information, determine a following distance compensation value for a road surface type based on the road surface type information, determine a slope following distance compensation value based on the slope grade information, determine a following distance compensation value for a dark light environment based on the dark light environment judgment result, determine a following distance compensation value associated with the front vehicle type based on the front vehicle type information, and determine a following distance compensation value associated with the traffic flow operation condition of the lane associated with the target vehicle based on the traffic flow operation condition.

[0147] Based on the rain and snow environment information, the following distance compensation value for the rain and snow environment is determined, or, based on the road surface type information, the road surface type following distance compensation value is determined, or, based on the slope grade information, the slope following distance compensation value is determined, or, based on the dark light environment judgment result, the following distance compensation value for the dark light environment is determined, or, based on the front vehicle type information, the following distance compensation value associated with the front vehicle type is determined, or, based on the traffic flow operation condition of the lane associated with the target vehicle, the following distance compensation value associated with the traffic flow operation condition is determined. The detailed process can be found in the relevant introduction in Example 1 and will not be repeated here.

[0148] Step S24: Select a maximum value from the following distance compensation value for rainy and snowy environments, the following distance compensation value for road surface types, the following distance compensation value for slopes, the following distance compensation value for dark light environments, the following distance compensation value associated with the type of vehicle ahead, and the following distance compensation value associated with traffic flow conditions, and add the maximum value to the initial following distance.

[0149] Steps S23-S24 are a specific implementation of step S13 in Example 1.

[0150] In the present application, various environmental information such as rain and snow environment information, road surface type information, slope grade information, dark environment judgment results, front vehicle type information and traffic flow operation conditions are obtained through environmental monitoring to ensure the comprehensiveness of environmental monitoring. On this basis, the maximum value is selected from the rain and snow environment following distance compensation value, the road surface type following distance compensation value, the slope following distance compensation value, the dark light environment following distance compensation value, the following distance compensation value associated with the front vehicle type and the following distance compensation value associated with the traffic flow operation conditions, and the maximum value is added to the initial following distance to realize the use of the environmental information that has the greatest impact on the following performance to adjust the initial following distance and ensure the accuracy of the adjustment.

[0151] As another optional embodiment of the present application, refer to Figure 6 , is a flow chart of a cruise following distance adjustment method embodiment 3 provided by this application. This embodiment is mainly a refinement of the cruise following distance adjustment method described in the above embodiment 1, such as Figure 6 As shown, the method may include but is not limited to the following steps:

[0152] Step S31: Acquire an initial following distance of a target vehicle, where the initial following distance is determined based on a gear position set for the target vehicle and a speed of the target vehicle.

[0153] The detailed process of step S31 can be found in the relevant introduction of step S11 in embodiment 1, and will not be repeated here.

[0154] Step S32: Utilize the target vehicle's sensors related to the rain and snow environment to collect information, use the collected information as rain and snow environment information, estimate the road surface type in the area where the target vehicle is located to obtain road surface type information, estimate the slope grade in the area where the target vehicle is located to obtain slope grade information, determine whether the target vehicle is in a dark light environment, obtain a dark light environment determination result, identify the type of the vehicle in front of the target vehicle, obtain the front vehicle type information, and determine the traffic flow operation status of the lane associated with the target vehicle.

[0155] In this embodiment, the target vehicle's sensors related to the rain and snow environment are used to collect information, and the collected information is used as the detailed process of the rain and snow environment information, or the road type of the area where the target vehicle is located is estimated to obtain road type information, or the slope grade of the area where the target vehicle is located is estimated to obtain slope grade information, or it is determined whether the target vehicle is in a dark light environment to obtain a dark light environment judgment result, or the type of the vehicle in front of the target vehicle is identified to obtain the front vehicle type information, or the detailed process of determining the traffic flow operation status of the lane associated with the target vehicle can be found in the relevant introduction in Example 1 and will not be repeated here.

[0156] Step S32 is a specific implementation of step S12 in Example 1.

[0157] Step S33: Determine a following distance compensation value for a rainy and snowy environment based on the rainy and snowy environment information, determine a following distance compensation value for a road surface type based on the road surface type information, determine a slope following distance compensation value based on the slope grade information, determine a following distance compensation value for a dark light environment based on the dark light environment judgment result, determine a following distance compensation value associated with the front vehicle type based on the front vehicle type information, and determine a following distance compensation value associated with the traffic flow operation condition based on the traffic flow operation condition of the lane associated with the target vehicle.

[0158] Based on the rain and snow environment information, the following distance compensation value for the rain and snow environment is determined, or, based on the road surface type information, the road surface type following distance compensation value is determined, or, based on the slope grade information, the slope following distance compensation value is determined, or, based on the dark light environment judgment result, the following distance compensation value for the dark light environment is determined, or, based on the front vehicle type information, the following distance compensation value associated with the front vehicle type is determined, or, based on the traffic flow operation condition of the lane associated with the target vehicle, the following distance compensation value associated with the traffic flow operation condition is determined. The detailed process can be found in the relevant introduction in Example 1 and will not be repeated here.

[0159] Step S34: If the traffic flow condition of the lane associated with the target vehicle is normal congestion or normal traffic flow, a maximum value is selected from the following distance compensation value for rainy and snowy environments, the following distance compensation value for the road type, the following distance compensation value for slopes, the following distance compensation value for dark light environments, and the following distance compensation value associated with the type of vehicle ahead.

[0160] Step S35: performing an addition operation on the maximum value, the following distance compensation value associated with ordinary congestion or normal traffic flow, and the initial following distance.

[0161] Steps S33-S35 are a specific implementation of step S13 in Example 1.

[0162] In this application, through environmental monitoring, various environmental information such as rain and snow environment information, road type information, slope grade information, dark environment judgment results, front vehicle type information and traffic flow operation conditions are obtained to ensure the comprehensiveness of environmental monitoring. On this basis, according to the traffic flow operation conditions, the method of adjusting the initial following distance is determined, and the initial following distance is adjusted using the determined method to ensure the accuracy of the adjustment.

[0163] As another optional embodiment of the present application, refer to Figure 7 , is a flow chart of a cruise following distance adjustment method embodiment 4 provided by this application. This embodiment is mainly a refinement of the cruise following distance adjustment method described in the above embodiment 1, such as Figure 7 As shown, the method may include but is not limited to the following steps:

[0164] Step S41: Acquire an initial following distance of a target vehicle, where the initial following distance is determined based on a gear position set for the target vehicle and a speed of the target vehicle.

[0165] The detailed process of step S41 can be found in the relevant introduction of step S11 in embodiment 1, and will not be repeated here.

[0166] Step S42: Utilize the target vehicle's sensors related to the rain and snow environment to collect information, use the collected information as rain and snow environment information, estimate the road surface type in the area where the target vehicle is located to obtain road surface type information, estimate the slope grade in the area where the target vehicle is located to obtain slope grade information, determine whether the target vehicle is in a dark light environment, obtain a dark light environment determination result, identify the type of the vehicle in front of the target vehicle, obtain the front vehicle type information, and determine the traffic flow operation status of the lane associated with the target vehicle.

[0167] In this embodiment, the target vehicle's sensors related to the rain and snow environment are used to collect information, and the collected information is used as the detailed process of the rain and snow environment information, or the road type of the area where the target vehicle is located is estimated to obtain road type information, or the slope grade of the area where the target vehicle is located is estimated to obtain slope grade information, or it is determined whether the target vehicle is in a dark light environment to obtain a dark light environment judgment result, or the type of the vehicle in front of the target vehicle is identified to obtain the front vehicle type information, or the detailed process of determining the traffic flow operation status of the lane associated with the target vehicle can be found in the relevant introduction in Example 1 and will not be repeated here.

[0168] Step S42 is a specific implementation of step S12 in Example 1.

[0169] Step S43: Determine a following distance compensation value for a rainy and snowy environment based on the rainy and snowy environment information, determine a following distance compensation value for a road surface type based on the road surface type information, determine a slope following distance compensation value based on the slope grade information, determine a following distance compensation value for a dark light environment based on the dark light environment judgment result, determine a following distance compensation value associated with the front vehicle type based on the front vehicle type information, and determine a following distance compensation value associated with the traffic flow operation condition based on the traffic flow operation condition of the lane associated with the target vehicle.

[0170] Based on the rain and snow environment information, the following distance compensation value for the rain and snow environment is determined, or, based on the road surface type information, the road surface type following distance compensation value is determined, or, based on the slope grade information, the slope following distance compensation value is determined, or, based on the dark light environment judgment result, the following distance compensation value for the dark light environment is determined, or, based on the front vehicle type information, the following distance compensation value associated with the front vehicle type is determined, or, based on the traffic flow operation condition of the lane associated with the target vehicle, the following distance compensation value associated with the traffic flow operation condition is determined. The detailed process can be found in the relevant introduction in Example 1 and will not be repeated here.

[0171] Step S44: If the traffic flow condition of the lane associated with the target vehicle is congestion merging into a side lane, a maximum value is selected from the following distance compensation value for rainy and snowy environments, the following distance compensation value for road surface types, the following distance compensation value for slopes, the following distance compensation value for dark light environments, the following distance compensation value associated with the type of vehicle ahead, and the following distance compensation value associated with congestion merging into a side lane, and the maximum value is added to the initial following distance.

[0172] Step S44 is a specific implementation of step S13 in Example 1.

[0173] In this application, through environmental monitoring, various environmental information such as rain and snow environment information, road type information, slope grade information, dark environment judgment results, front vehicle type information and traffic flow operation conditions are obtained to ensure the comprehensiveness of environmental monitoring. On this basis, according to the traffic flow operation conditions, the method of adjusting the initial following distance is determined, and the initial following distance is adjusted using the determined method to ensure the accuracy of the adjustment.

[0174] Next, the cruise following distance adjustment device provided by the present application is introduced. The cruise following distance adjustment device introduced below and the cruise following distance adjustment method introduced above can be referred to each other.

[0175] See Figure 8 The cruise following distance adjustment device includes: an acquisition module 100, an environment monitoring module 200 and an adjustment module 300.

[0176] An acquisition module 100 is configured to acquire an initial following distance of a target vehicle, wherein the initial following distance is determined based on a gear position set for the target vehicle and a speed of the target vehicle;

[0177] An environment monitoring module 200 is used to monitor the environment associated with the following performance of the target vehicle and obtain environmental information;

[0178] The adjustment module 300 is configured to adjust the initial following distance based on the environmental information.

[0179] In this embodiment, the environment monitoring module 200 can be specifically used to:

[0180] collecting information using a sensor of the target vehicle related to the rain and snow environment, and using the collected information as rain and snow environment information;

[0181] and / or, estimating the road surface type of the area where the target vehicle is located to obtain road surface type information;

[0182] and / or, estimating the slope grade of the area where the target vehicle is located to obtain slope grade information;

[0183] and / or, determining whether the target vehicle is in a dark light environment, and obtaining a dark light environment determination result;

[0184] and / or, identifying the type of a vehicle located in front of the target vehicle to obtain front vehicle type information;

[0185] And / or, determining the traffic flow condition of the lane associated with the target vehicle.

[0186] Accordingly, the adjustment module 300 may be specifically configured to:

[0187] Determining a following distance compensation value for a rainy or snowy environment based on the rainy or snowy environment information;

[0188] and / or, determining a road surface type following distance compensation value based on the road surface type information;

[0189] and / or, determining a slope following distance compensation value based on the slope grade information;

[0190] and / or, determining a following distance compensation value for a dark light environment based on the dark light environment determination result;

[0191] and / or, determining a following distance compensation value associated with the type of the preceding vehicle based on the preceding vehicle type information;

[0192] and / or, determining a following distance compensation value associated with the traffic flow operation condition based on the traffic flow operation condition of the lane associated with the target vehicle;

[0193] The initial following distance is compensated using the following distance compensation value for rainy and snowy environments, and / or the following distance compensation value for road surface types, and / or the following distance compensation value for slopes, and / or the following distance compensation value for dark light environments, and / or the following distance compensation value associated with the type of vehicle ahead, and / or the following distance compensation value associated with traffic flow conditions.

[0194] In this embodiment, the adjustment module 300 can be specifically used to:

[0195] A maximum value is selected from the following distance compensation value for rainy and snowy environments, the following distance compensation value for road surface types, the following distance compensation value for slopes, the following distance compensation value for dark light environments, the following distance compensation value associated with the type of vehicle in front, and the following distance compensation value associated with traffic flow conditions, and the maximum value is added to the initial following distance.

[0196] In this embodiment, the environment monitoring module 200 can be specifically used to:

[0197] Using the rain and snow sensor of the target vehicle to collect information, and using the wiper sensor of the target vehicle to collect a wiper gear signal and an actual wiper frequency signal;

[0198] The adjustment module 300 is specifically configured to:

[0199] Determining whether the speed of the target vehicle is greater than a speed compensation threshold;

[0200] If it is greater than, searching a preset multidimensional table for a distance that matches the information collected by the rain and snow sensor, the wiper gear position signal, and the actual wiper frequency signal;

[0201] The found distance is used as the following distance compensation value in rainy and snowy environments;

[0202] If it is not greater than, the value 0 will be used as the following distance compensation value in rainy and snowy environments.

[0203] In this embodiment, the environment monitoring module 200 can be specifically used to:

[0204] Obtain ADAS internal road adhesion coefficient;

[0205] Determining whether the magnitude relationships between the ADAS internal road surface adhesion coefficient and different adhesion coefficient monitoring thresholds conform to the set magnitude relationships corresponding to the adhesion coefficient monitoring thresholds;

[0206] If yes, determining whether the duration of the set magnitude relationship corresponding to the adhesion coefficient monitoring threshold satisfies the set duration;

[0207] If satisfied, obtaining the road type information corresponding to the adhesion coefficient monitoring threshold;

[0208] The adjustment module 300 is specifically configured to:

[0209] Obtaining a distance compensation time corresponding to the road surface type information;

[0210] The time distance compensation time corresponding to the road surface type information is multiplied by the speed of the target vehicle to obtain a road surface type following distance compensation value.

[0211] In this embodiment, the environment monitoring module 200 can be specifically used to:

[0212] Obtaining a real-time estimated slope value for the area where the target vehicle is located;

[0213] Determining whether the magnitude relationships between the slope values ​​and different ramp thresholds conform to the set magnitude relationships corresponding to the ramp thresholds;

[0214] If it meets the requirements, the ramp level information corresponding to the ramp threshold is obtained;

[0215] The adjustment module 300 is specifically configured to:

[0216] If the slope grade information indicates that the slope does not have the ability to affect the following performance of the target vehicle, a value of 0 is used as the slope following distance compensation value;

[0217] If the slope grade information indicates that the slope has the ability to affect the following performance of the target vehicle, then a following distance compensation value corresponding to the slope grade information is obtained, and the following distance compensation value is subtracted from the minimum following distance of the target vehicle to obtain a slope following distance compensation value.

[0218] In this embodiment, the environment monitoring module 200 can be specifically used to:

[0219] Collecting status information of the target vehicle's headlights, time information inside the target vehicle, and information collected by the target vehicle's light sensor;

[0220] Determining whether the target vehicle is in a dark light environment based on the state information of the target vehicle's headlights, the time information in the target vehicle, and the information collected by the light sensor of the target vehicle, thereby obtaining a dark light environment determination result;

[0221] The adjustment module 300 is specifically configured to:

[0222] If the dark light environment judgment result indicates that the target vehicle is in a dark light environment, obtaining a time distance compensation time in a dark light environment;

[0223] The result of multiplying the distance compensation time in the dark light environment by the speed of the target vehicle is used as the following vehicle distance compensation value in the dark light environment;

[0224] If the dark light environment judgment result indicates that the target vehicle is not in a dark light environment, a value of 0 is used as the dark light environment following distance compensation value.

[0225] In this embodiment, the environment monitoring module 200 can be specifically used to:

[0226] Based on the front-view camera of the target vehicle, identifying the type of the vehicle located in front of the target vehicle and obtaining the front vehicle type information;

[0227] The adjustment module 300 is specifically configured to:

[0228] determining whether the front vehicle represented by the front vehicle type information is a special vehicle;

[0229] If so, obtaining a time compensation coefficient for the special vehicle, and multiplying the time compensation coefficient for the special vehicle by the target vehicle to obtain a result as a following distance compensation value associated with the type of the preceding vehicle;

[0230] If not, a value of 0 is used as the following distance compensation value associated with the preceding vehicle type.

[0231] In this embodiment, the environment monitoring module 200 can be specifically used to:

[0232] monitoring the traffic speed changes of the lane containing the target vehicle and its adjacent lanes, and obtaining the merging information of the vehicle ahead of the target vehicle from map information;

[0233] If the merging information of the vehicle ahead of the target vehicle indicates that there is no vehicle merging ahead, determining that the traffic flow condition of the lane associated with the target vehicle is normal traffic flow;

[0234] If the merging information of the vehicle ahead of the target vehicle indicates that there is a vehicle merging ahead, and there is a vehicle merging within the vehicle headway range, then determining that the traffic flow operation condition of the lane associated with the target vehicle is side lane merging congestion;

[0235] If the merging information of the vehicle ahead of the target vehicle indicates that there is a vehicle merging from at least one lane other than the lane to which the target vehicle belongs, and there is no vehicle merging within the vehicle headway range, and there is a vehicle ahead of the target vehicle in the lane containing the target vehicle, and the average traffic flow speed of the vehicle ahead of the target vehicle is less than the speed limit within the set time, then the traffic flow operation condition of the lane associated with the target vehicle is determined to be normal congestion;

[0236] If the merging information of the vehicle ahead of the target vehicle indicates that there is a vehicle merging from at least one lane other than the lane to which the target vehicle belongs, and there is no vehicle merging within the vehicle headway range, and there is a vehicle ahead of the target vehicle in the lane containing the target vehicle, and the average traffic flow speed of the vehicle ahead of the target vehicle is not less than the speed limit within the set time, then the traffic flow condition of the lane associated with the target vehicle is determined to be normal traffic flow;

[0237] The adjustment module 300 is specifically configured to:

[0238] If the traffic flow condition is normal, a value of 0 is used as the following distance compensation value associated with the traffic flow condition;

[0239] If the traffic flow operation condition is normal congestion, multiplying the congestion compensation time coefficient by the speed of the target vehicle to obtain a congestion compensation value, and subtracting the congestion compensation value from 0 as the following distance compensation value associated with the traffic flow operation condition;

[0240] If the traffic flow operation condition is congestion due to merging into a side lane, the preset distance compensation value is used as the following distance compensation value associated with the traffic flow operation condition.

[0241] In this embodiment, the adjustment module 300 can be specifically used to:

[0242] If the traffic flow condition of the lane associated with the target vehicle is normal congestion or normal traffic flow, selecting a maximum value from the following distance compensation value for rainy and snowy environments, the following distance compensation value for road type, the following distance compensation value for slopes, the following distance compensation value for dark light environments, and the following distance compensation value associated with the type of vehicle ahead;

[0243] The maximum value, a following distance compensation value associated with ordinary congestion or normal traffic flow, and the initial following distance are added together.

[0244] The adjustment module 300 can be specifically used to:

[0245] If the traffic flow condition of the lane associated with the target vehicle is congestion merging into the side lane, the maximum value is selected from the following distance compensation value for rainy and snowy environment, the following distance compensation value for the road surface type, the following distance compensation value for the slope, the following distance compensation value for the dark light environment, the following distance compensation value associated with the type of vehicle in front, and the following distance compensation value associated with congestion merging into the side lane, and the maximum value is added to the initial following distance.

[0246] The acquisition module 100 can be specifically used to:

[0247] Using the first relation Calculate the initial following distance of the target vehicle;

[0248] Among them, D drvrtgt is the initial following distance of the target vehicle, v ego is the speed of the target vehicle, It is the following time coefficient corresponding to the target vehicle, which is related to the speed of the target vehicle and the gear set for the target vehicle. SetDistLvl_indx is the gear set for the target vehicle, and d_0 represents the minimum following distance.

[0249] In another embodiment of the present application, a computer-readable storage medium is provided, on which computer instructions are stored. When the computer instructions are executed, the steps of the cruise following distance adjustment method introduced in any one of the method embodiments 1-4 are executed.

[0250] In another embodiment of the present application, a server is provided, including a memory and a processor, wherein the memory stores computer instructions that can be run on the processor, and when the processor runs the computer instructions, the processor executes the steps of the cruise following distance adjustment method introduced in any one of the method embodiments 1-4.

[0251] It should be noted that each embodiment focuses on the differences from other embodiments, and the same or similar parts between the various embodiments can be referred to in detail. For the device embodiments, since they are basically similar to the method embodiments, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiments.

[0252] Finally, it should be noted that, in this document, relational terms such as first and second, etc., are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the terms "comprises," "comprising," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or device comprising a series of elements includes not only those elements, but also other elements not explicitly listed, or elements inherent to such process, method, article, or device. In the absence of further limitations, an element defined by the phrase "comprising a ..." does not exclude the presence of additional identical elements in the process, method, article, or device comprising the element.

[0253] For the convenience of description, the above devices are described as being divided into various units according to their functions. Of course, when implementing this application, the functions of each unit can be implemented in the same or multiple software and / or hardware.

[0254] Through the description of the above embodiments, it can be seen that those skilled in the art can clearly understand that the present application can be implemented by means of software plus a necessary general hardware platform. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, can be embodied in the form of a software product, which can be stored in a storage medium such as ROM / RAM, a magnetic disk, an optical disk, etc., and includes a number of instructions for enabling a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in various embodiments of the present application or certain parts of the embodiments.

[0255] The above is a detailed introduction to a retrieval method, device and system provided by the present application. Specific examples are used herein to illustrate the principles and implementation methods of the present application. The description of the above embodiments is only used to help understand the method and core idea of ​​the present application. At the same time, for those skilled in the art, according to the idea of ​​the present application, there may be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as a limitation on the present application.

Claims

1. A method for adjusting the cruise distance, characterized in that: include: Obtaining an initial following distance of a target vehicle, wherein the initial following distance is determined based on a gear position set for the target vehicle and a speed of the target vehicle; Monitoring an environment associated with the following performance of the target vehicle to obtain environmental information; The environmental information includes: the type of vehicle ahead and the traffic flow; based on the environmental information, the initial following distance is adjusted; wherein, determining a method for adjusting the initial following distance based on traffic flow conditions, and adjusting the initial following distance using the determined adjustment method; the traffic flow conditions include normal traffic flow, side lane merging congestion, and general congestion; Determining a following distance compensation value associated with the preceding vehicle type based on the preceding vehicle type information, specifically comprising: determining whether the preceding vehicle represented by the preceding vehicle type information is a special vehicle; if so, obtaining a time compensation coefficient for the special vehicle, and multiplying the time compensation coefficient for the special vehicle by the target vehicle to obtain a result of a multiplication operation as the following distance compensation value associated with the preceding vehicle type; if not, setting a value of 0 as the following distance compensation value associated with the preceding vehicle type; Based on the traffic flow operation condition of the lane associated with the target vehicle, a following distance compensation value associated with the traffic flow operation condition is determined, specifically including: if the traffic flow operation condition is normal traffic flow, a value of 0 is used as the following distance compensation value associated with the traffic flow operation condition; if the traffic flow operation condition is ordinary congestion, a congestion compensation time coefficient is multiplied by the speed of the target vehicle to obtain a congestion compensation value, and a result obtained by subtracting the congestion compensation value from the value 0 is used as the following distance compensation value associated with the traffic flow operation condition; if the traffic flow operation condition is congestion merging into the side lane, a pre-set distance compensation value is used as the following distance compensation value associated with the traffic flow operation condition.

2. The method according to claim 1, characterized in that The monitoring of the environment associated with the following performance of the target vehicle to obtain environmental information includes: collecting information using a sensor of the target vehicle related to the rain and snow environment, and using the collected information as rain and snow environment information; and / or, estimating the road surface type of the area where the target vehicle is located to obtain road surface type information; and / or, estimating the slope grade of the area where the target vehicle is located to obtain slope grade information; and / or, determining whether the target vehicle is in a dark light environment, and obtaining a dark light environment determination result; and / or, identifying the type of a vehicle located in front of the target vehicle to obtain front vehicle type information; And / or, determining the traffic flow condition of the lane associated with the target vehicle.

3. The method according to claim 2, characterized in that The adjusting the initial following distance based on the environmental information includes: Determining a following distance compensation value for a rainy or snowy environment based on the rainy or snowy environment information; and / or, determining a road surface type following distance compensation value based on the road surface type information; and / or, determining a slope following distance compensation value based on the slope grade information; and / or, determining a following distance compensation value for a dark light environment based on the dark light environment determination result; and / or, determining a following distance compensation value associated with the type of the preceding vehicle based on the preceding vehicle type information; and / or, determining a following distance compensation value associated with the traffic flow operation condition based on the traffic flow operation condition of the lane associated with the target vehicle; The initial following distance is compensated using the following distance compensation value for rainy and snowy environments, and / or the following distance compensation value for road surface types, and / or the following distance compensation value for slopes, and / or the following distance compensation value for dark light environments, and / or the following distance compensation value associated with the type of vehicle ahead, and / or the following distance compensation value associated with traffic flow conditions.

4. The method according to claim 3, characterized in that The compensating the initial following distance by using the following distance compensation value for a rainy or snowy environment, and / or the following distance compensation value for a road surface type, and / or the following distance compensation value for a slope, and / or the following distance compensation value for a dark light environment, and / or the following distance compensation value associated with the type of the preceding vehicle, and / or the following distance compensation value associated with the traffic flow condition, includes: A maximum value is selected from the following distance compensation value for rainy and snowy environments, the following distance compensation value for road surface types, the following distance compensation value for slopes, the following distance compensation value for dark light environments, the following distance compensation value associated with the type of vehicle in front, and the following distance compensation value associated with traffic flow conditions, and the maximum value is added to the initial following distance.

5. The method according to claim 3, characterized in that The collecting of information by using sensors of the target vehicle related to the rain and snow environment includes: Using the rain and snow sensor of the target vehicle to collect information, and using the wiper sensor of the target vehicle to collect a wiper gear signal and an actual wiper frequency signal; The determining of a following distance compensation value for a rainy and snowy environment based on the rainy and snowy environment information includes: Determining whether the speed of the target vehicle is greater than a speed compensation threshold; If it is greater than, searching a preset multidimensional table for a distance that matches the information collected by the rain and snow sensor, the wiper gear position signal, and the actual wiper frequency signal; The found distance is used as the following distance compensation value in rainy and snowy environments; If it is not greater than, the value 0 will be used as the following distance compensation value in rainy and snowy environments.

6. The method according to claim 3, characterized in that The estimating the road type of the area where the target vehicle is located to obtain road type information includes: Obtain ADAS internal road adhesion coefficient; Determining whether the magnitude relationships between the ADAS internal road surface adhesion coefficient and different adhesion coefficient monitoring thresholds conform to the set magnitude relationships corresponding to the adhesion coefficient monitoring thresholds; If yes, determining whether the duration of the set magnitude relationship corresponding to the adhesion coefficient monitoring threshold satisfies the set duration; If satisfied, obtaining the road type information corresponding to the adhesion coefficient monitoring threshold; The determining of the road type following distance compensation value based on the road type information includes: Obtaining a distance compensation time corresponding to the road surface type information; The time distance compensation time corresponding to the road surface type information is multiplied by the speed of the target vehicle to obtain a road surface type following distance compensation value.

7. The method according to claim 3, characterized in that The estimating the slope grade of the area where the target vehicle is located to obtain slope grade information includes: Obtaining a real-time estimated slope value for the area where the target vehicle is located; Determining whether the magnitude relationships between the slope values ​​and different ramp thresholds conform to the set magnitude relationships corresponding to the ramp thresholds; If it meets the requirements, the ramp level information corresponding to the ramp threshold is obtained; The determining of the slope following distance compensation value based on the slope grade information includes: If the slope grade information indicates that the slope does not have the ability to affect the following performance of the target vehicle, a value of 0 is used as the slope following distance compensation value; If the slope grade information indicates that the slope has the ability to affect the following performance of the target vehicle, then a following distance compensation value corresponding to the slope grade information is obtained, and the following distance compensation value is subtracted from the minimum following distance of the target vehicle to obtain a slope following distance compensation value.

8. The method according to claim 3, characterized in that The determining whether the target vehicle is in a dark light environment and obtaining a dark light environment determination result includes: Collecting status information of the target vehicle's headlights, time information inside the target vehicle, and information collected by the target vehicle's light sensor; Determining whether the target vehicle is in a dark light environment based on the state information of the target vehicle's headlights, the time information in the target vehicle, and the information collected by the light sensor of the target vehicle, thereby obtaining a dark light environment determination result; The determining of the dark light environment following distance compensation value based on the dark light environment judgment result includes: If the dark light environment judgment result indicates that the target vehicle is in a dark light environment, obtaining a time distance compensation time in a dark light environment; The result of multiplying the distance compensation time in the dark light environment by the speed of the target vehicle is used as the following vehicle distance compensation value in the dark light environment; If the dark light environment judgment result indicates that the target vehicle is not in a dark light environment, a value of 0 is used as the dark light environment following distance compensation value.

9. The method according to claim 3, characterized in that The identifying the type of the vehicle in front of the target vehicle to obtain the front vehicle type information includes: Based on the front-view camera of the target vehicle, the type of the vehicle located in front of the target vehicle is identified to obtain the front vehicle type information.

10. The method according to claim 3, characterized in that Determining the traffic flow condition of the lane associated with the target vehicle includes: monitoring the traffic speed changes of the lane containing the target vehicle and its adjacent lanes, and obtaining the merging information of the vehicle ahead of the target vehicle from map information; If the merging information of the vehicle ahead of the target vehicle indicates that there is no vehicle merging ahead, determining that the traffic flow condition of the lane associated with the target vehicle is normal traffic flow; If the merging information of the vehicle ahead of the target vehicle indicates that there is a vehicle merging ahead, and there is a vehicle merging within the vehicle headway range, then determining that the traffic flow operation condition of the lane associated with the target vehicle is side lane merging congestion; If the merging information of the vehicle ahead of the target vehicle indicates that there is a vehicle merging from at least one lane other than the lane to which the target vehicle belongs, and there is no vehicle merging within the vehicle headway range, and there is a vehicle ahead of the target vehicle in the lane containing the target vehicle, and the average traffic flow speed of the vehicle ahead of the target vehicle is less than the speed limit within the set time, then the traffic flow operation condition of the lane associated with the target vehicle is determined to be normal congestion; If the merging information of the vehicle in front of the target vehicle indicates that there is a vehicle merging from at least one lane other than the lane to which the target vehicle belongs, and there is no vehicle merging within the vehicle time range, and there is a vehicle in front of the target vehicle in the lane containing the target vehicle, and the average traffic flow speed of the vehicle is not less than the speed limit within the set time, then the traffic flow operation condition of the lane associated with the target vehicle is determined to be normal traffic flow.

11. The method according to claim 10, characterized in that The compensating the initial following distance by using the following distance compensation value for a rainy or snowy environment, and / or the following distance compensation value for a road surface type, and / or the following distance compensation value for a slope, and / or the following distance compensation value for a dark light environment, and / or the following distance compensation value associated with the type of the preceding vehicle, and / or the following distance compensation value associated with the traffic flow condition, includes: If the traffic flow condition of the lane associated with the target vehicle is normal congestion or normal traffic flow, selecting a maximum value from the following distance compensation value for rainy and snowy environments, the following distance compensation value for road type, the following distance compensation value for slopes, the following distance compensation value for dark light environments, and the following distance compensation value associated with the type of vehicle ahead; The maximum value, a following distance compensation value associated with ordinary congestion or normal traffic flow, and the initial following distance are added together.

12. The method according to claim 10, characterized in that The compensating the initial following distance by using any one or more of the following distance compensation value for a rainy or snowy environment, the following distance compensation value for a road type, the following distance compensation value for a slope, the following distance compensation value for a dark light environment, the following distance compensation value associated with the type of the preceding vehicle, and the following distance compensation value associated with the traffic flow condition includes: If the traffic flow condition of the lane associated with the target vehicle is congestion merging into a side lane, a maximum value is selected from the following distance compensation value for rainy and snowy environments, the following distance compensation value for road surface types, the following distance compensation value for slopes, the following distance compensation value for dark light environments, the following distance compensation value associated with the type of vehicle in front, and the following distance compensation value associated with congestion merging into a side lane, and the maximum value is added to the initial following distance.

13. The method according to any one of claims 1 to 11, characterized in that The obtaining of the initial following distance of the target vehicle includes: Using the first relation (v ego ,SetDistLvl_indx)+d_0, calculate the initial following distance of the target vehicle; Among them, D drvrtgt is the initial following distance of the target vehicle, v ego is the speed of the target vehicle, It is the following time coefficient corresponding to the target vehicle, which is related to the speed of the target vehicle and the gear set for the target vehicle. SetDistLvl_indx is the gear set for the target vehicle, and d_0 represents the minimum following distance.

14. A cruise following distance adjustment device, characterized in that: include: an acquisition module, configured to acquire an initial following distance of a target vehicle, wherein the initial following distance is determined based on a gear position set for the target vehicle and a speed of the target vehicle; An environment monitoring module, configured to monitor an environment associated with the following performance of the target vehicle and obtain environmental information; The environmental information includes: the type of vehicle ahead and the traffic flow status; an adjustment module, configured to adjust the initial following distance based on the environmental information; wherein, determining a method for adjusting the initial following distance based on traffic flow conditions, and adjusting the initial following distance using the determined adjustment method; the traffic flow conditions include normal traffic flow, side lane merging congestion, and general congestion; Determining a following distance compensation value associated with the preceding vehicle type based on the preceding vehicle type information, specifically comprising: determining whether the preceding vehicle represented by the preceding vehicle type information is a special vehicle; if so, obtaining a time compensation coefficient for the special vehicle, and multiplying the time compensation coefficient for the special vehicle by the target vehicle to obtain a result of a multiplication operation as the following distance compensation value associated with the preceding vehicle type; if not, setting a value of 0 as the following distance compensation value associated with the preceding vehicle type; Based on the traffic flow operation condition of the lane associated with the target vehicle, a following distance compensation value associated with the traffic flow operation condition is determined, specifically including: if the traffic flow operation condition is normal traffic flow, a value of 0 is used as the following distance compensation value associated with the traffic flow operation condition; if the traffic flow operation condition is ordinary congestion, a congestion compensation time coefficient is multiplied by the speed of the target vehicle to obtain a congestion compensation value, and a result obtained by subtracting the congestion compensation value from the value 0 is used as the following distance compensation value associated with the traffic flow operation condition; if the traffic flow operation condition is congestion merging into the side lane, a pre-set distance compensation value is used as the following distance compensation value associated with the traffic flow operation condition.

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