WO2018045974A1 - 用于确定红绿灯配时方案的方法、装置及系统 - Google Patents
用于确定红绿灯配时方案的方法、装置及系统 Download PDFInfo
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- the present disclosure relates to the field of intelligent transportation, and in particular to a method, device and system for determining a traffic light timing scheme.
- Traffic lights at road intersections also known as traffic lights
- traffic lights are of great significance in solving traffic congestion and reducing accidents.
- the rapid development of intelligent transportation, unmanned driving and other technologies have raised higher demand for traffic light status recognition.
- For the method of status recognition of traffic lights there are two common methods.
- One method is to use the image recognition method to identify the status of the traffic lights in the direction of the current intersection.
- the second method is the cooperation of the local traffic management bureau, which is provided by the Traffic Management Bureau.
- the traffic light timing scheme is provided by the Traffic Management Bureau.
- the first method uses image recognition. Due to the location of traffic lights in various cities, traffic light patterns and other object occlusion, light interference, rain and snow and other special weather, as well as the error of the image recognition algorithm itself, the recognition rate is not high, or recognition There are errors.
- the second method is to cooperate with the Government Traffic Management Bureau, and the traffic light timing scheme exists in the internal network of the Traffic Management Bureau.
- the internal network is physically isolated from the Internet, and it is difficult to obtain the traffic light timing scheme for reasons of safety and the like;
- the Traffic Management Bureau may adjust the configuration scheme according to the real-time traffic status. For this temporary adjustment scheme, if it does not establish direct contact with the internal network of the Traffic Management Bureau, it is impossible to obtain the timing scheme in real time.
- the purpose of the present disclosure is to provide a method, device and system for determining a traffic light timing scheme, which can dynamically obtain the traffic light status of each intersection in real time, and then determine the traffic light timing. Program.
- a method for determining a traffic light timing scheme comprising: acquiring travel data when a plurality of vehicles pass a intersection; calculating traffic light state data of the intersection using the travel data; And determining a traffic light timing scheme according to the traffic light state data.
- an apparatus for determining a traffic light timing scheme comprising: a data acquisition module for acquiring travel data when a plurality of vehicles pass a intersection; and a calculation module for utilizing the The driving data calculates the traffic light state data of the intersection; and the timing scheme determining module is configured to determine a traffic light timing scheme according to the traffic light state data.
- a system for determining a traffic light timing scheme comprising an in-vehicle terminal device comprising a data acquisition unit, a data processing unit, and a data reporting unit, the data acquisition unit For collecting driving data of the vehicle, the data processing unit is configured to process the collected driving data, the data reporting unit is configured to upload the processed driving data to the cloud platform; and the cloud platform includes the above The device described.
- the method, device and system for determining the timing scheme of the traffic light provided by the present disclosure, the traffic data of each vehicle is used to analyze and obtain the traffic light state data, thereby obtaining the traffic light timing scheme, without weather environment, image recognition algorithm, and law. Regulations and other restrictions can dynamically determine the status of traffic lights at various intersections, the estimated time remaining for the lights, and so on, thus providing important reference for intelligent transportation, driverless, advanced driver assistance systems (ADAS).
- ADAS advanced driver assistance systems
- FIG. 1 is an example flow diagram of a method for determining a traffic light timing scheme provided by the present disclosure
- FIG. 2 is a schematic view of two cases in which a vehicle passes through a junction
- FIG. 3 is a schematic diagram of a system for determining a traffic light timing scheme provided by the present disclosure
- FIG. 4 is a system block diagram of the present disclosure for determining a traffic light timing scheme.
- the present disclosure provides a method for determining a traffic light timing scheme, the method comprising: S1, acquiring driving data when multiple vehicles pass through a road junction; S2, calculating the intersection using the driving data. The traffic light status data; and S3, determining a traffic light timing scheme according to the traffic light status data.
- the driving data may include vehicle positioning data and vehicle body state data
- the in-vehicle terminal device may upload driving data to the wireless network to A device such as a cloud platform is used to complete the data processing of steps S1 to S3 by the cloud platform.
- the vehicle positioning data may include longitude, latitude, speed, direction, altitude, time, etc., and the positioning accuracy may be sub-meter level.
- Body status data may include stop, start, brake status, body speed, steering, and the like.
- the cloud platform After acquiring the vehicle driving data from the in-vehicle terminal device, the cloud platform performs the analysis processing of steps S1 to S2 on the driving data of each vehicle to obtain corresponding traffic light state data, and then obtains each intersection of the plurality of vehicles. Multiple sets of traffic light status data are fused to determine the traffic light timing scheme.
- the traffic light status data may include a green light start time, a green light knot Beam time, red light start time and red light end time.
- Calculating the traffic light state data of the intersection by using the driving data includes: obtaining, by using the vehicle positioning data, trajectory data of the plurality of vehicles passing through the intersection; and calculating, according to the trajectory data and the vehicle body state data The traffic light status data.
- the specific process of calculating the traffic light status data of the intersection by using the travel data passing through a certain intersection is described in detail below. The process is based on the vehicle positioning data when the vehicle passes a certain intersection, obtains the trajectory data of the vehicle passing through the intersection, and calculates the traffic light state data of the intersection according to the trajectory data and the vehicle body state data (such as stopping, starting, braking, etc.). .
- Some of the intersections passing by the vehicle are equipped with traffic lights, some are not configured. Combined with the electronic map data, the data without the traffic light intersection can be filtered out, and only the vehicle driving data of the intersection with the traffic lights is processed.
- the vehicle positioning data is combed to form a trajectory data passing through the intersection, the trajectory data is changed with time, and the position changes along the driving direction, that is, the trajectory data is sorted by time.
- 100m herein is merely an example.
- each car passes through the intersection: one is to pass directly. Since the signal light in the direction of travel of the car is a green light, it passes directly through the intersection. The second is after parking and then passed. Because the traffic light in the direction of the car is a red light, the car stops at a position in front of the intersection, and then the signal light turns green and then passes through the intersection. The travel direction of the intersection vehicle can be calculated, and the value of the traffic light at each time in two cases.
- FIG 2 is a schematic illustration of two scenarios in which a vehicle passes through a junction.
- the time of the yellow light is uniformly classified into the green light
- T1 is the real green light start time point and also the last red light. End time
- T2 is the real green light end time point and also the next red light start time point
- C1 and C2 are through the present disclosure
- the method calculates the green light start time and the green light end time.
- the S11 and E12 time points are within the green time period and can be used to verify the correct value of the green light timing.
- the first row in the second case in FIG. 2 is used to describe the method of calculating the green light start time.
- the vehicle stops indicating that the time point is a red light, and when the vehicle starts again, the distance between the vehicle and the intersection is passed.
- speed calculate the passage time dt1
- the intersection green light start time C1 vehicle start time point minus dt1, which is also the last red light end time.
- E21 in the first row of the second case in Fig. 2 is the vehicle transit time, which must be within the green time period.
- the second line of the second case in Figure 2 is used to illustrate the method of calculating the green light end time.
- the end time of the green light There are two possibilities for the end time of the green light.
- the vehicle when the vehicle is driving, when the green light turns red, the vehicle will have a brake deceleration action. For example, from the moment of E22 to the slow stop to the back of the last car in the lane, the brake deceleration can also be calculated. After that, and the quotient of the intersection distance difference and its current speed, the time difference is obtained, but this time difference cannot be used to calculate the green end/red start time, and can only be used to verify whether the time calculated in the previous possibility is correct.
- the traffic light state data of the intersection calculated based on the single vehicle can be obtained. Since the calculation data of a single vehicle is not reliable, the calculated value cannot be used as the final result. Therefore, it is necessary to use a large amount of vehicle driving data in the direction of the intersection to perform the same calculation, and then integrate the calculated plurality of traffic light state data. And verify the results of the fusion, and obtain the final trustworthy timing scheme value of the intersection. Therefore, determining a traffic light timing scheme according to the traffic light state data includes fusing the traffic light state data to obtain the traffic light timing scheme; and verifying the income The traffic light timing scheme to the arrival.
- the present disclosure is based on a large amount of vehicle traffic data.
- Vehicle access can cover all of the city's major intersections with traffic lights.
- the traffic light timing scheme of each intersection can be sequentially determined, and after all the intersection traffic light timing schemes in the city are obtained, the traffic light timing scheme is stored and/or released.
- the timing scheme data can be stored in a data table structure. The structure of the timing scheme data table is shown in Table 1:
- Table 1 Traffic light schedule scheme data structure table
- the present disclosure also provides an apparatus for determining a traffic light timing scheme, the apparatus comprising: a data acquisition module, configured to acquire travel data when a plurality of vehicles pass through a intersection; and a calculation module, configured to calculate the travel data by using the travel data Traffic light status data of the intersection; and a timing scheme determining module for determining a traffic light timing scheme according to the traffic light state data.
- the travel data may include vehicle positioning data and vehicle body status data
- the traffic light status data may include a green light start time, a green light end time, a red light start time, and a red light end time.
- the calculation module includes: a trajectory data acquisition sub-module, configured to obtain trajectory data of the plurality of vehicles passing through the intersection by using the vehicle positioning data; and a calculation sub-module, according to the trajectory data and the The body state data calculates the traffic light status data.
- a trajectory data acquisition sub-module configured to obtain trajectory data of the plurality of vehicles passing through the intersection by using the vehicle positioning data
- a calculation sub-module according to the trajectory data and the The body state data calculates the traffic light status data.
- the specific calculation example of the traffic light state data has been described in detail in the above description with reference to FIG. 2, and details are not described herein again.
- the timing scheme determining module includes: a fusion submodule, configured to fuse the traffic light state data to obtain the traffic light timing scheme; and a syndrome module for verifying the obtained traffic light Time plan.
- the apparatus further comprises means for storing and/or issuing a verified traffic light timing scheme.
- the system for determining the traffic light timing scheme provided by the present invention includes two parts of the vehicle terminal device 1 and the cloud platform 2.
- the in-vehicle terminal device 1 may include a data collection unit 10, a data processing unit 20, and a data reporting unit 30.
- the data collecting unit 10 is configured to collect driving data of the vehicle, the driving data includes vehicle positioning data and vehicle body state data, and the data collecting unit 10 may include a positioning collecting subunit for collecting vehicle positioning data and for collecting the vehicle body state.
- the vehicle positioning data may include longitude, latitude, speed, direction, altitude, time, etc., and the positioning accuracy may be sub-meter level.
- Body status data may include stop, start, brake status, body speed, steering, and the like.
- the data processing unit 20 is configured to process the collected driving data, such as cleaning, encryption, packaging, and the like.
- the data reporting unit 30 is configured to upload the processed driving data to the cloud platform 2.
- the in-vehicle terminal device 1 can be realized by the T-Box 1, and the vehicle body state data can be acquired through the CAN bus 3.
- the cloud platform 2 may include device data for determining a traffic light timing scheme according to the present disclosure as described above. After receiving the driving data from the in-vehicle terminal device 1, the cloud platform 2 may further perform processing operations such as decompression, decryption, unpacking, and the like, and then determine a traffic light timing scheme according to the driving data, which has been combined according to the present disclosure. This method is described in detail and will not be described here.
- the cloud platform 2 can also be used to release the determined traffic light timing scheme.
- the Http/Json mode access interface can be provided for other users to obtain the timing scheme data of all the intersections.
- the method, device and system for determining the timing scheme of the traffic light use the actual driving data of the vehicle to obtain the traffic light state data, thereby obtaining a traffic light timing scheme, which can accurately and dynamically determine the actual intersection traffic light timing in real time, which is intelligent. Provide important reference for driving and other occasions.
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Abstract
一种用于确定红绿灯配时方案的方法、装置及系统，确定方法包括：获取多台车辆经过路口时的行驶数据；利用行驶数据计算路口的红绿灯状态数据；以及根据红绿灯状态数据确定红绿灯配时方案。能实时动态地确定各个路口的红绿灯配时，从而给智能驾驶等提供重要参考。
Description
本公开涉及智能交通领域，具体地，涉及一种用于确定红绿灯配时方案的方法、装置及系统。
道路交叉路口的红绿灯，又称交通信号灯，对于解决交通拥堵、减少事故等方面具有重要意义，近年来迅速发展的智能交通、无人驾驶等技术对于红绿灯状态识别提出了更高需求。对于红绿灯状态识别的方法，常见有两种方式，一种方法是使用图像识别方法，识别出当前路口行驶方向上各个转向的红绿灯状态，第二种方法是当地交管局合作，由交管局提供准确的红绿灯配时方案。
第一种方法因为使用图像识别，由于各个城市红绿灯布设的位置、红绿灯样式和其他物体遮挡、光线干扰、雨雪等特殊天气，以及图像识别算法本身误差问题，会造成识别率不高，或者识别有误差出现。
第二种方法是与政府交管局合作，而红绿灯配时方案存在于交管局内网中，该内网与互联网是物理隔离的，而且出于安全等原因考虑，很难获取红绿灯配时方案；另外交管局可能根据实时交通状态调整配置方案，对于这种临时性调整方案，如果不与交管局的内网建立直接联系，不可能实时获取配时方案。
发明内容
本公开的目的是提供一种用于确定红绿灯配时方案的方法、装置及系统，能够实时动态地得到各个路口的红绿灯状态，进而确定出红绿灯配时
方案。
根据本公开的第一方面，提供一种用于确定红绿灯配时方案的方法，该方法包括：获取多台车辆经过路口时的行驶数据；利用所述行驶数据计算所述路口的红绿灯状态数据；以及根据所述红绿灯状态数据确定红绿灯配时方案。
根据本公开的第二方面，提供一种用于确定红绿灯配时方案的装置，该装置包括：数据获取模块，用于获取多台车辆经过路口时的行驶数据；计算模块，用于利用所述行驶数据计算所述路口的红绿灯状态数据；以及配时方案确定模块，用于根据所述红绿灯状态数据确定红绿灯配时方案。
根据本公开的第三方面，提供一种用于确定红绿灯配时方案的系统，该系统包括车载终端设备，该车载终端设备包括数据采集单元、数据处理单元和数据上报单元，所述数据采集单元用于采集车辆的行驶数据，所述数据处理单元用于处理所采集的行驶数据，所述数据上报单元用于将处理后的行驶数据上传到云平台；以及云平台，该云平台包括如上所述的装置。
本公开提供的用于确定红绿灯配时方案的方法、装置及系统，由于采用每辆车的行驶数据来分析得到红绿灯状态数据，进而得到红绿灯配时方案，不受天气环境、图像识别算法、法律法规等多方面的限制，能实时动态地确定各个路口的红绿灯状态、预计距离变灯还剩余的时间等，从而给智能交通、无人驾驶、高级驾驶辅助系统(ADAS)等提供重要参考。
本公开的其他特征和优点将在随后的具体实施方式部分予以详细说明。
附图是用来提供对本公开的进一步理解，并且构成说明书的一部分，
与下面的具体实施方式一起用于解释本公开，但并不构成对本公开的限制。在附图中：
图1是本公开提供的用于确定红绿灯配时方案的方法的示例流程图；
图2是车辆通过路口的两种情况的示意图；
图3是本公开提供的用于确定红绿灯配时方案的系统示意图；以及
图4是本公开提供的用于确定红绿灯配时方案的系统框图。
以下结合附图对本公开的具体实施方式进行详细说明。应当理解的是，此处所描述的具体实施方式仅用于说明和解释本公开，并不用于限制本公开。
如图1所示，本公开提供了一种用于确定红绿灯配时方案的方法，该方法包括：S1，获取多台车辆经过路口时的行驶数据；S2，利用所述行驶数据计算所述路口的红绿灯状态数据；以及S3，根据所述红绿灯状态数据确定红绿灯配时方案。
获取车辆的行驶数据为数据收集过程，可以从诸如T-Box之类的车载终端设备获取，所述行驶数据可以包括车辆定位数据和车身状态数据，车载终端设备可以将行驶数据通过无线网络上传到云平台等设备以便由云平台完成步骤S1至S3的数据处理。车辆定位数据可以包括经度、纬度、速度、方向、高度、时间等，定位精度可以是亚米级。车身状态数据可以包括停止、启动、刹车状态、车身速度、转向等。
所述云平台在从车载终端设备获取车辆行驶数据之后，对各个车辆的行驶数据分别进行步骤S1至S2的分析处理以得到相应的红绿灯状态数据，并然后对多辆车获得的每一路口的多组红绿灯状态数据进行融合处理以确定红绿灯配时方案。所述红绿灯状态数据可以包括绿灯开始时间、绿灯结
束时间、红灯开始时间和红灯结束时间。
所述利用所述行驶数据计算所述路口的红绿灯状态数据包括：利用所述车辆定位数据得到所述多台车辆经过所述路口的轨迹数据；以及根据所述轨迹数据和所述车身状态数据计算所述红绿灯状态数据。以下将详细描述，对于单台车，利用经过某一路口的行驶数据计算该路口的红绿灯状态数据的具体过程。这一过程是根据车辆经过某个路口时的车辆定位数据，得到车辆经过路口的轨迹数据，并根据轨迹数据和车身状态数据(如停止、启动、踩刹车等)来计算该路口的红绿灯状态数据。车辆经过的路口中有的配置了红绿灯，有的没有配置，结合电子地图数据，可以过滤掉没有红绿灯路口的数据，仅针对有红绿灯的路口的车辆行驶数据进行处理。
对车辆定位数据进行梳理，形成一条经过路口的轨迹数据，该轨迹数据是随时间变化的，位置沿着行车方向变化的，即轨迹数据按时间排序。使用电子地图，判断出当前车辆所经过的是哪个路口。然后以该路口为中心，从轨迹数据中取出车辆行驶方向进入路口的预定距离以内的矩形区域内的所有轨迹数据，所述预定距离可以例如为100m。本领域技术人员应当理解的是，这里的100m仅是示例。
每辆车通过路口的方式主要有两种情况：一种是直接通过。由于该车行进方向的信号灯是绿灯，所以直接通过路口。第二种是停车后，然后再通过。因为该车行进方向的信号灯是红灯，该车在路口前某个位置停下来，等信号灯变绿后再通过路口。可以计算出该路口车辆行进方向，在两种情况下红绿灯分项配时的数值。
图2为车辆通过路口的两种情况的示意图。在图2中第一行为示意的真实的红灯、绿灯、红灯的交替顺序，为简化起见，黄灯的时间统一归入绿灯考虑；T1为真实的绿灯开始时间点，也是上一个红灯结束时间；T2为真实的绿灯结束时间点，也是下一个红灯开始时间点；C1和C2为通过本公开
的方法计算出来的绿灯开始时间和绿灯结束时间。
图2中第一种情况下，S11和E12时间点是在绿灯时间段内的，可以用于校验绿灯配时的正确值。
图2中第二种情况下的第一行，用于说明计算绿灯开始时间的方法，在时间点S21车辆停止，表示该时间点是红灯，当车辆再次启动时，通过车与路口的距离和速度，算出通过时间dt1，那么该路口绿灯开始时间C1＝车辆启动时间点减去dt1，其也是上一红灯结束时间。图2中第二种情况第一行中的E21为车辆通过时间，该时间一定在绿灯时间段内。
图2中第二种情况的第二行，用于说明计算绿灯结束时间的方法。绿灯结束时间有两种可能，一种是车辆通过过程中看到绿灯变红灯，而以其当前速度不能通过路口，所以踩刹车，缓慢停止到车道停止线最前方，就是下一轮绿灯时，会第一个通过路口的车辆。所以这种情况下，S22是车辆踩下刹车的时刻，设P1为车辆停止位置和路口距离的差除以当前速度得出的时间差，从而计算出来绿灯结束时间C2＝S22-P1，也是下一红灯开始时间。另外一种是车辆行驶过程中，看到绿灯变红灯，车辆会有刹车减速动作，如从某个E22的时刻，直到缓慢停止到该车道最后一辆车的后面，同样可以计算出刹车减速后，以及用路口距离差和它当前速度的商得出时间差，但是这个时间差不能用于计算绿灯结束/红灯开始时间，只能用于校验前一种可能中计算的时间是否正确。
通过以上处理，可以得出基于单台车计算的该路口的红绿灯状态数据。由于单台车的计算数据不可靠性，该计算值不能作为最终结果，所以需要使用该路口行驶方向的大量车辆行驶数据，进行相同的计算，再将计算出的多组红绿灯状态数据进行融合，并校验融合后的结果，得出该路口的最终可信任的配时方案值。因此，根据所述红绿灯状态数据确定红绿灯配时方案包括对所述红绿灯状态数据进行融合，得到所述红绿灯配时方案；以及校验所得
到的红绿灯配时方案。
融合可以采用平均值方案进行处理。比如已经计算出多个绿灯开始时间S1、S2、S3、…、Sn，则SA＝AVG(S1+S2+…+Sn)，将SA作为绿灯开始时间，同时也是上一个红灯结束时间。同理利用平均值计算出绿灯结束时间EA，同时也是下一个红灯开始时间。然后使用校验方法校验计算得到上述数值的有效性，可以利用行驶数据对配时方案进行校验，例如可以采用图2中第一种情况下得到的S11和E12，这两个时间点应该在计算出来的SA和EA之间，即应当满足SA<S11，同时满足E12<EA，否则数据有问题。
本公开是基于大量车辆通行数据基础上进行的。车辆通行可以覆盖城市的所有主要有红绿灯的路口。使用上面描述的方法，可以依次求出每个路口的红绿灯配时方案，在得到城市中所有路口红绿灯配时方案之后，存储和/或发布所述红绿灯配时方案。例如，可以利用MySQL写入数据库中，作为配时方案发布的基础数据。配时方案数据可以采用数据表结构存储。配时方案数据表结构如表1所示：
表1：红绿灯配时方案数据结构表
本公开还提供一种用于确定红绿灯配时方案的装置，该装置包括：数据获取模块，用于获取多台车辆经过路口时的行驶数据；计算模块，用于利用所述行驶数据计算所述路口的红绿灯状态数据；以及配时方案确定模块，用于根据所述红绿灯状态数据确定红绿灯配时方案。所述行驶数据可以包括车辆定位数据和车身状态数据，所述红绿灯状态数据可以包括绿灯开始时间、绿灯结束时间、红灯开始时间和红灯结束时间。
优选地，所述计算模块包括：轨迹数据获取子模块，用于利用所述车辆定位数据得到所述多台车辆经过路口的轨迹数据；以及计算子模块，用于根据所述轨迹数据和所述车身状态数据计算所述红绿灯状态数据。红绿灯状态数据的具体计算示例在以上参考图2的描述中已经进行了详细说明，在此不再赘述。
优选地，所述配时方案确定模块包括：融合子模块，用于对所述红绿灯状态数据进行融合，得到所述红绿灯配时方案；以及校验子模块，用于校验所得到的红绿灯配时方案。优选地，所述装置还包括用于存储和/或发布校验后的红绿灯配时方案的模块。
如图3和图4所示，本发明提供的用于确定红绿灯配时方案的系统包括车载终端设备1和云平台2两大部分。车载终端设备1可以包括数据采集单元10、数据处理单元20和数据上报单元30。所述数据采集单元10用于采集车辆的行驶数据，所述行驶数据包括车辆定位数据和车身状态数据，数据采集单元10可以包括用于采集车辆定位数据的定位采集子单元和用于采集车身状态数据的控制局域网(CAN)总线采集子单元。车辆定位数据可以包括经度、纬度、速度、方向、高度、时间等，定位精度可以是亚米级。车身状态数据可以包括停止、启动、刹车状态、车身速度、转向等。所述
数据处理单元20用于处理所采集的行驶数据，如进行清洗、加密、打包等等处理工作。所述数据上报单元30用于将处理后的行驶数据上传到云平台2。如图3所示，车载终端设备1可由T-Box 1实现，并可以通过CAN总线3来获取车身状态数据。
云平台2可以包括如上描述的根据本公开的用于确定红绿灯配时方案的装置数据。云平台2在从所述车载终端设备1接收到所述行驶数据之后，还可以进行解压、解密、拆包等处理工作，然后根据所述行驶数据确定红绿灯配时方案，以上已经结合根据本公开的方法对此进行了详细描述，此处不再赘述。云平台2还可以用于发布所确定的红绿灯配时方案，例如可以提供Http/Json方式访问接口，供其他使用者获取所有路口的配时方案数据。
本公开提供的用于确定红绿灯配时方案的方法、装置及系统，利用车辆实际行驶数据分析得到红绿灯状态数据，进而得到红绿灯配时方案，能够实时准确动态地确定实际路口红绿灯配时，为智能驾驶等场合提供重要参考。
以上结合附图详细描述了本公开的优选实施方式，但是，本公开并不限于上述实施方式中的具体细节，在本公开的技术构思范围内，可以对本公开的技术方案进行多种简单变型，这些简单变型均属于本公开的保护范围。
另外需要说明的是，在上述具体实施方式中所描述的各个具体技术特征，在不矛盾的情况下，可以通过任何合适的方式进行组合，为了避免不必要的重复，本公开对各种可能的组合方式不再另行说明。
此外，本公开的各种不同的实施方式之间也可以进行任意组合，只要其不违背本公开的思想，其同样应当视为本公开所公开的内容。
Claims (12)
- 一种用于确定红绿灯配时方案的方法，该方法包括：获取多台车辆经过路口时的行驶数据；利用所述行驶数据计算所述路口的红绿灯状态数据；以及根据所述红绿灯状态数据确定红绿灯配时方案。
- 根据权利要求1所述的方法，其中，所述行驶数据包括车辆定位数据和车身状态数据，所述红绿灯状态数据包括绿灯开始时间、绿灯结束时间、红灯开始时间和红灯结束时间。
- 根据权利要求2所述的方法，其中，所述利用所述行驶数据计算所述路口的红绿灯状态数据包括：利用所述车辆定位数据得到所述多台车辆经过所述路口的轨迹数据；以及根据所述轨迹数据和所述车身状态数据计算所述红绿灯状态数据。
- 根据权利要求1-3中任一权利要求所述的方法，其中，所述根据所述红绿灯状态数据确定红绿灯配时方案包括：对所述红绿灯状态数据进行融合，得到所述红绿灯配时方案；以及校验所得到的红绿灯配时方案。
- 根据权利要求4所述的方法，该方法还包括：存储和/或发布校验后的红绿灯配时方案。
- 一种用于确定红绿灯配时方案的装置，该装置包括：数据获取模块，用于获取多台车辆经过路口时的行驶数据；计算模块，用于利用所述行驶数据计算所述路口的红绿灯状态数据；以及配时方案确定模块，用于根据所述红绿灯状态数据确定红绿灯配时方案。
- 根据权利要求6所述的装置，其中，所述行驶数据包括车辆定位数据和车身状态数据，所述红绿灯状态数据包括绿灯开始时间、绿灯结束时间、红灯开始时间和红灯结束时间。
- 根据权利要求7所述的装置，其中，所述计算模块包括：轨迹数据获取子模块，用于利用所述车辆定位数据得到所述多台车辆经过所述路口的轨迹数据；以及计算子模块，用于根据所述轨迹数据和所述车身状态数据计算所述红绿灯状态数据。
- 根据权利要求6-8中任一权利要求所述的装置，其中，所述配时方案确定模块包括：融合子模块，用于对所述红绿灯状态数据进行融合，得到所述红绿灯配时方案；以及校验子模块，用于校验所得到的红绿灯配时方案。
- 根据权利要求9所述的装置，该装置还包括用于存储和/或发布校验后的红绿灯配时方案的模块。
- 一种用于确定红绿灯配时方案的系统，该系统包括：车载终端设备，该车载终端设备包括数据采集单元、数据处理单元和数据上报单元，所述数据采集单元用于采集车辆的行驶数据，所述数据处理单元用于处理所采集的行驶数据，所述数据上报单元用于将处理后的行驶数据上传到云平台；以及云平台，该云平台包括根据权利要求6至10中任一权利要求所述的装置。
- 根据权利要求11所述的系统，其中，所述行驶数据包括车辆定位数据和车身状态数据，所述数据采集单元包括用于采集所述车辆定位数据的定位数据采集单元和用于采集所述车身状态数据的控制局域网总线采集单元。
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