WO2018028025A1 - 车联网环境下行车服务主动感知系统及方法 - Google Patents

车联网环境下行车服务主动感知系统及方法 Download PDF

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Publication number
WO2018028025A1
WO2018028025A1 PCT/CN2016/099511 CN2016099511W WO2018028025A1 WO 2018028025 A1 WO2018028025 A1 WO 2018028025A1 CN 2016099511 W CN2016099511 W CN 2016099511W WO 2018028025 A1 WO2018028025 A1 WO 2018028025A1
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Prior art keywords
vehicle
information
driving
service
driving service
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PCT/CN2016/099511
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English (en)
French (fr)
Inventor
梁军
赵振超
陈龙
江浩斌
陈小波
马世典
周卫琪
蔡英凤
赵彤阳
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江苏大学
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Priority to US16/070,976 priority Critical patent/US11100795B2/en
Publication of WO2018028025A1 publication Critical patent/WO2018028025A1/zh

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Definitions

  • the invention relates to the field of road traffic safety, in particular to a road driving service sensing system.
  • the traditional driving service system is mainly composed of two parts: the G-BOS terminal and the data processing center: the G-BOS terminal is installed on the vehicle, and collects engine operation data, vehicle condition information, and driver's control behavior from the CAN bus and the sensor. At the same time, the information of the location of the vehicle where the GPS satellite positioning information is recorded is received, and all of the information is transmitted to the data processing center through wireless communication technology.
  • the data processing center analyzes and organizes the received data information through certain calculations, and provides drivers with suggestions for poor driving behavior warning, fuel consumption data, vehicle operation, and maintenance plan.
  • the traditional driving service system brings convenience to the driver to a certain extent, but the traditional system has many problems, such as: 1
  • the traditional driving service system is for a specific type of car users, passenger cars, or trucks, etc. Users; for example, the G-BOS system is a system specifically for passenger cars, and it is not possible to provide driving services for passenger cars.
  • the traditional driving service system collects vehicle information mainly by collecting vehicle engine parameters, vehicle speed, driver's mental state, etc., mainly focusing on the economics of the vehicle commercial process, and is the vehicle. The security provided is not sufficient.
  • 3 The driving service provided by the traditional driving service system has the disadvantages of lack of real-time and initiative.
  • the invention aims at the shortcomings of the above-mentioned traditional driving service system, the lack of driving safety guarantee, the lack of real-time and initiative of the provided driving service, and the invention provides a driving service active sensing system and method in the vehicle networking environment. It can solve the shortcomings of the traditional driving service system and provide real-time and active driving services for the driver to ensure driving safety.
  • the present invention adopts a technical method adopted by an active sensing system for a vehicle service environment in a vehicle network environment.
  • the vehicle service active sensing system includes interconnected sensor devices and intelligent vehicle terminals disposed on the vehicle.
  • the intelligent vehicle terminal communicates with the roadside equipment via 4G and DSRC, and passes the 4G mode and the driving service information processing center.
  • Communication, roadside equipment and driving service information processing center use 4G communication; sensor equipment includes camera, OBD module, radar sensor, GPS differential module, steering wheel angle sensor and gear position information sensor; intelligent vehicle terminal includes electronic control unit, Video processing module, Bluetooth module and vehicle control module; roadside equipment is arranged on both sides of the road, including storage module and ECU; driving service information processing center includes driving service cloud computing platform, driving information state library and driving service catalogue; sensor The device outputs the obtained vehicle driving information to the intelligent vehicle terminal, and the intelligent vehicle terminal firstly processes the received vehicle driving information, and then transmits the information to the roadside device and the driving service information processing center; the driving service cloud computing platform Fusion Information processing, output driving service information, and delivery to roadside devices and smart vehicle terminals.
  • the sensor device transmits the information collected in real time to the electronic control unit, and the electronic control unit performs fusion processing on all the information;
  • the vehicle in the roadside equipment monitoring area travels, when detecting that the vehicle is abnormally traveling, sends a warning message, and generates a danger information code to be transmitted to the driving service information processing center;
  • the driving service information processing center preferentially processes the dangerous information code, and the driving information state library matches the received fusion information, and uses the service demand state matching algorithm to determine whether the vehicle is currently in the driving service demand state, and if so, the driving The service catalogue is matched with the fusion information of the driving service demand status, and the driving service catalog generation matching algorithm is used to generate the driving service catalog, and the driving service catalog is pushed to the demanding vehicle.
  • the system of the present invention has a wider range of uses.
  • the driving service information processing center can provide driving services for them, and is no longer limited to passenger cars or freight vehicles, and the driving service information processing center can receive according to the received information.
  • the roadside equipment and sensor collection information actively provide security warning and path planning services for the vehicle owner.
  • the system of the present invention pays more attention to vehicle driving safety. Due to the more sensor arrangement of the system, not only can the vehicle operating parameters of the serviced vehicle itself be collected, but also the driving parameters of the vehicle in front of the serviced vehicle can be collected, depending on the high-speed transmission of information and the information system of the driving service information processing center in the vehicle networking environment. And a powerful back-end cloud computing platform to ensure the safe driving of vehicles, and provide more driving services for vehicles under the premise of ensuring vehicle safety.
  • the system of the present invention realizes the driving service from the "request-response" traditional driving service to the "automatic identification-active pushing" mode, and the serviced vehicle does not monitor the operating parameters of the self-vehicle vehicle unlike the traditional driving service system.
  • sensors and intelligent vehicle terminals on the vehicle, real-time transmission of information by the sensing device is realized by means of mature wireless communication technology, and the roadside equipment and the driving service information processing center receive the driving information extracted by the feature, fast and automatic.
  • the driving process of driving services is automated, so that there can be more sufficient time to respond to accidents such as traffic accidents, and timely automatic identification to ensure safe driving and slow traffic congestion.
  • the system of the invention independently generates a service through the driving service component library of the driving service information processing center, and finally realizes the active pushing of the corresponding service to the user and provides an effective guarantee for the service quality.
  • the information collected by the sensor of the service vehicle is extracted by the processing of the intelligent vehicle terminal to extract the feature information, and the current vehicle is supported by the driving information state library to determine whether the current vehicle is in a driving service demand state.
  • the feature information is Search matching is supported by the driving service catalog, and finally the directory of the driving service is generated.
  • FIG. 1 is a block diagram of an overall hardware connection of an active sensing system for a vehicle traveling environment in a vehicle networking environment according to the present invention
  • FIG. 2 is an overall flow chart of an active sensing method for a downlink service in a vehicle networking environment according to the present invention.
  • the vehicle network environment downlink service active sensing system is composed of a sensor device 1, an intelligent vehicle terminal 2, a roadside device 3, and a driving service information processing center.
  • the sensor device 1 and the smart vehicle terminal 2 are disposed on a vehicle, and the sensor device 1 and the smart vehicle terminal 2 are installed in each vehicle to which the system is applied.
  • the roadside device 3 is arranged on the intelligent road network, and the background driving service information processing center 4 includes a driving information state library, a driving service directory library and a powerful driving service cloud computing platform.
  • Both the sensor device 1 and the intelligent vehicle terminal 2 in the vehicle obtain self-vehicle operation data by means of a CAN bus and a dedicated hard wire connection.
  • the communication between the intelligent vehicle-mounted terminal 2 and the roadside device 3 uses the 4G method and the DSRC (Dedicated Short-Range Wireless Communication 802.11p) communication to meet the communication requirements under high-speed movement.
  • the intelligent in-vehicle terminal 2 and the driving service information processing center 4 are directly communicated by the 4G method, or are forwarded to the driving service information processing center 4 via the roadside device 3; and the roadside device 3 and the driving service information processing center 4 are connected by 4G. Communication.
  • the sensor device 1 includes a camera, an OBD module (vehicle self-diagnosis system), a radar sensor, a GPS differential module, a steering wheel angle sensor, and a gear position information sensor.
  • the camera provides video and image information of the vehicle in front.
  • the OBD module is used to obtain the vehicle speed v 1 , the acceleration a 1 , the engine speed n, the exhaust system operating parameters, and the vehicle fault code X of the vehicle (the active service vehicle).
  • the radar sensor detects the speed v 2 and the acceleration a 2 of the preceding vehicle (the vehicle in front), the relative speed v rel of the vehicle and the preceding vehicle, the distance s between the vehicle and the preceding vehicle, the vehicle ID, and the vehicle ID in real time during the running of the vehicle.
  • the GPS differential module is used to obtain the precise geographical location information of the differentiated vehicle: coordinate information of longitude, latitude and altitude.
  • Steering wheel angle sensor for steering wheel angle The gear position information sensor is used to acquire the current gear position information N of the vehicle.
  • the vehicle travel parameter information obtained by all the components in the sensor device 1 is output to the smart vehicle terminal 2 in real time.
  • the OBD module and the intelligent in-vehicle terminal 2 communicate using a Bluetooth connection.
  • the intelligent vehicle terminal 2 includes an electronic control unit, a video processing module, a Bluetooth module, a communication module 1 and a vehicle control module.
  • the communication module 1 includes a DSRC (Dedicated Short Range Wireless Communication) communication module and a 4G communication module.
  • the video and image information of the preceding vehicle obtained by the camera in the sensor device 1 is input into the video processing module, converted into digital information by the video processing module, and transmitted to the electronic control unit for processing.
  • the vehicle speed v 1 , the acceleration a 1 , the engine speed n , the exhaust system operating parameter and the vehicle fault code X information acquired by the OBD module in the sensor device 1 are transmitted to the electronic control via the Bluetooth module in the smart vehicle terminal 2 in real time.
  • the unit, the electronic control unit processes the information and transmits it to the roadside device 3.
  • the radar sensor, the GPS differential module, the steering wheel angle sensor and the gear position information sensor in the sensor device 1 are directly transmitted to the electronic control unit through the serial port.
  • the electronic control unit solves the GPS coordinate information of the longitude, latitude and altitude obtained by the GPS differential module into the xyz coordinates in the space rectangular coordinate system, and simultaneously packs the GPS coordinates and the xyz coordinates to the roadside device 3.
  • the DSRC communication module in the communication module 1 is used for communicating with the roadside device 3 during the running of the vehicle, and receiving the decision instruction signal of the roadside device 3, and the 4G communication module is used for communicating with the driving service information processing center 4 to receive the driving.
  • the service decision signal of the service information processing center 4 is determined.
  • the electronic control unit performs preliminary processing on the received vehicle travel information, and then transmits the information to the roadside device 3 and the driving service information processing center 4.
  • the output of the electronic control unit is connected to the vehicle control module for executing the service decision instruction transmitted by the roadside device 3 and the driving service information processing center 4, prompting the vehicle or even controlling the vehicle to perform braking, steering, etc., and securing the vehicle. Driving safely.
  • the roadside device 3 includes a storage module, an ECU, and a communication module 2.
  • the ECU is respectively connected to the storage module and the communication module 2.
  • the communication module 2 is composed of a DSRC communication module and a 4G/fiber communication module.
  • the roadside device 3 is interconnected with the communication module in the smart vehicle terminal 2 via its communication module 2.
  • the roadside device 3 is installed on both sides of the road. Considering the interference of the obstacle to the signal, the roadside device 3 is arranged at a higher position as much as possible, and can communicate with the intelligent vehicle terminal 2 and the driving service information processing center 4, respectively. Have a certain regional decision-making ability.
  • the roadside device 3 receives all vehicle GPS coordinates, spatial rectangular coordinate system coordinates (x 1 , y 1 , z 1 ), ..., (x n , y n , z n ) on the road segment transmitted by the smart vehicle terminal 2 and The speed of the vehicle v 1 , v 2 ,..., v n , real-time monitoring of the traffic flow of the current section, the average driving speed of the vehicle, and the traffic density.
  • 1 ⁇ n is the vehicle number of the road section.
  • the speed limit v x and the coordinate information set by the link are stored in the storage module in the roadside device 3, and are transmitted to the driving service information processing center 4 via the 4G/fiber communication method of the communication module 2.
  • the ECU in the roadside equipment 3 performs regional decision processing on the received information, and the ECU focuses on monitoring abnormal driving behaviors such as retrograde, overspeed, and abnormal parking of the road section.
  • the roadside device 3 specifically monitors the abnormal driving of the vehicle: the ECU can determine the driving lane and the driving direction of the current vehicle according to the spatial rectangular coordinates (x, y, z) sent by the intelligent vehicle-mounted terminal 2, and the vehicle in the road section. When the current normal running, the coordinate is positive change, and when the coordinate changes backward, it is retrograde. If it is retrograde, the ECU sends an alarm message to the vehicle in the road segment and transmits the danger information code to the driving service information processing center 4 through the optical fiber communication.
  • the ECU determines that the vehicle is overspeed, and sends a warning message to the vehicle ahead of the vehicle traveling direction via the DSRC communication mode of the communication module 2,
  • the optical fiber and 4G communication transmit the perceived danger information code to the driving service information processing center 4, and the driving service information processing center 4 performs further calculation processing, wherein v n is the current traveling speed of the vehicle n, and v x is the current road section setting.
  • the fixed speed limit value is the current traveling speed of the vehicle n.
  • the warning information code is pushed to the vehicle in the area, and is transmitted to the communication module 1 of the intelligent vehicle terminal 2 via the DSRC communication mode of the communication module 2, and the smart vehicle terminal 2 receives the road. After the warning information code transmitted by the side device 3, the code is parsed and its specific warning message is displayed on the smart vehicle terminal 2.
  • the driving service information processing center 4 includes a driving service cloud computing platform, a driving information status library, a driving service catalog library, and a communication module 3.
  • the communication module 3 is composed of a DSRC communication module and a 4G/fiber communication module, and communicates with the communication module 1 and the communication module 2 in the form of DSRC or 4G/fiber respectively.
  • the information fusion sensor device collects information in the driving information status library, and the electronic control unit in the sensor device 1 fuses the information and transmits it to the driving service information processing center 4, and stores it in the driving information state library. .
  • the driving service catalogue stores a description of the driving service catalogue that can be directly provided by the system.
  • the driving information state library and the driving service catalogue are linked by an outer code to ensure that the driving information state library is matched to the driving service demand, and the service existing in the driving service catalogue can be quickly provided.
  • the danger information code of the roadside device 3 and the sensor device acquisition information that has undergone preliminary processing and information fusion on the smart vehicle terminal 2 are respectively input to the driving service cloud computing platform.
  • the driving service cloud computing platform preferentially processes the danger information code of the roadside device 3 and the vehicle fault code X in the smart vehicle terminal 2, and immediately triggers the driving service in the driving service catalog corresponding to the codes.
  • the driving service cloud computing platform 4 processes the fusion information transmitted by the intelligent vehicle terminal 2 as follows: First, the fusion information is matched with the service demand state matching algorithm in the driving information state library to determine whether there is a current demand for driving service; After determining the driving service demand, the fusion information is matched with the driving service catalog generation matching algorithm in the driving service catalogue to obtain the driving service required by the current vehicle.
  • the output of the driving service cloud computing platform 4 is the driving service information automatically sensed by the system, and is transmitted to the roadside device 3 and the intelligent vehicle terminal 2 via the communication module 3, displaying the warning information through the intelligent vehicle terminal 2 or the intelligent vehicle in an emergency situation.
  • the terminal 2 issues an instruction to the vehicle control module to control the vehicle to decelerate and stop.
  • the driving service information processing center 4 receives the information and calculates the current optimal driving route, and can promptly push the message to prompt the driver to prevent the vehicle from entering the accident-affected road section and delaying the self-traveling journey.
  • the construction process of the driving information state library and the driving service catalogue is as follows: First, in order to facilitate subsequent data processing, the driving service is generally classified according to the urgency of the service, in order: safety services (including dangerous warnings, extremely dangerous situations) Under the control of the vehicle), efficient services (real-time navigation, vehicle maintenance and repair reminders, etc.), convenient services (by third parties to achieve scheduled restaurants, hotels and other services).
  • safety services including dangerous warnings, extremely dangerous situations
  • efficient services real-time navigation, vehicle maintenance and repair reminders, etc.
  • convenient services by third parties to achieve scheduled restaurants, hotels and other services.
  • the database structure is designed as a classification tree form, forming three types of driving services, vehicle driving data collection under road traffic scenarios, three-level data tables for driving services linked by external codes, and establishing "people-car-roads" respectively.
  • the static table mainly stores some parameters that are not changing frequently, such as: people (owner gender, age, driving age), car (model, length, width, height, maximum acceleration, etc.), road ( The type of road, the number of lanes, etc.), the danger information code of the roadside equipment 3 and its corresponding meaning;
  • the dynamic table is used to store dynamic data that changes with time during the data acquisition process, such as: human (eye gaze direction, blink frequency, etc.) , vehicle (ID, time, speed, acceleration, etc.), road (starting GPS positioning information, dead-point GPS positioning information, event description information, etc.), environment (temperature, road surface adhesion coefficient, etc.).
  • the matching algorithm used by the driving service cloud computing platform is as follows:
  • the service demand state matching algorithm Adopt a data stream comparison algorithm for high-speed network environments.
  • the driving information state data set B ⁇ y 1 , y 2 , . . . , y j ⁇ .
  • the algorithm gives a similar radius r and a sliding window value k, then the similarity calculation formulas of A and B are as follows:
  • d(x I , y J ) is a similar distance measure function
  • ⁇ ij is the Euclidean distance of the data segments x i and y j
  • r AB is the similarity between the data set A and the data set B
  • k/r AB is the data set A
  • the weighted matching slope of the data of the same type of data set B is matched.
  • the driving service directory generates a matching algorithm.
  • the driving information state library and the driving service catalogue are databases designed in the form of a classification tree.
  • the driving service catalog generation matching algorithm is calculated according to the semantic distance dis(p, q) between the nodes (p, q) in the classification tree.
  • the similarity between the concepts represented by nodes (Cp, Cq), expressed by sim(C p , C q ), and the similarity is normalized, ie sim(C p , C q ) ⁇ (0,1) ),
  • the overall flow chart of the active sensing system of the vehicle service environment in the vehicle network environment is realized, and the active sensing process of the driving service is as follows:
  • Step 1 Traffic information collection: The sensor device 1 collects the running information of the self-vehicle vehicle in real time, including the self-vehicle speed v 1 , the acceleration a 1 , and the steering wheel angle.
  • the engine speed n, the preceding vehicle travel information, and the forward road information (road image and video information) are transmitted to the smart vehicle terminal.
  • the preceding vehicle driving information includes the vehicle ID of the preceding vehicle, the speed v 2 of the vehicle traveling, the acceleration a 2 , the self-vehicle and the preceding vehicle distance s.
  • Step 2 Multi-multiple/multi-source information fusion:
  • the video processing module in the intelligent vehicle-mounted terminal 2 extracts the video and image information and processes it into an identifiable vehicle and lane line information;
  • the Bluetooth module of the intelligent vehicle-mounted terminal 2 collects the OBD module.
  • the information is transmitted to the electronic control unit, and the electronic control unit resolves the coordinate information acquired by the GPS differential module into (x, y, z) coordinates in the space rectangular coordinate system xyz, and the information collected by other sensors is transmitted to the electronic through the serial port.
  • the control unit uses the Kalman filtering method which is mature and suitable for real-time processing and calculation of the computer to filter the information collected by all the sensors, removes the white noise from the signal collected by the sensor, and then performs multi-/multi-source information fusion.
  • the input of the multivariate/multi-source information fusion is the image data (digital information) after feature extraction, the xyz coordinates after the GPS coordinate calculation, and the electronic control unit transmitted by the sensor can directly process (v 1 , a 1 , n, N, v 2 , a 2 , v rel , s, ID, ⁇ ) information.
  • the output of the multivariate/multisource information fusion is a standardized data set that facilitates the detection of anomalous events, such as ⁇ (x, y, z), (x, y, z, v n ), (v 1 , a 1 , s , v 2 , a 2 , v rel ),... ⁇ .
  • v n is the current travel speed of the vehicle with ID n.
  • the intelligent in-vehicle terminal 2 transmits the merged information to the roadside device 3 through the DSRC, and the roadside device 3 monitors the driving safety of the vehicle in the region according to the running information of the vehicle in the collected region, and generates a copy when the vehicle is abnormally detected.
  • the driving strategy of the area is pushed to the vehicle in the area, and the warning information is sent to the driver through the smart vehicle terminal 2; when the roadside device 3 detects the abnormal driving tendency of the vehicle (for example, the driver arbitrarily changes lane but does not affect the surrounding vehicles)
  • the roadside device 3 detects the abnormal driving tendency of the vehicle (for example, the driver arbitrarily changes lane but does not affect the surrounding vehicles)
  • the xyz coordinates are compared with the road coordinates to determine the frequent lateral displacement
  • a dangerous information code is generated, which is reported to the driving service information center 4 through the 4G/fiber communication of the communication module 2, and the driving service information processing center 4 performs analysis, calculation, and processing.
  • the intelligent in-vehicle terminal 2 directly transmits the collected information to the driving service information processing center 4 through 4G communication.
  • Step 3 The fusion information is matched with the status information: the driving service information processing center 4 preferentially processes the dangerous information code sent by the roadside device 3, and the specific content of the dangerous information can be obtained by calling the static table, and if necessary, it is sent to the roadside device 3 to broadcast the range.
  • the vehicle other than the vehicle; the driving service information processing center 4 matches the received information of the driving information state (dynamic table) with the received fusion information, and uses the service demand status matching algorithm to determine whether the vehicle is currently in the driving service demand state.
  • the system If the match is unsuccessful (d(x I , y J ) ⁇ r), the system considers that there is no driving service demand, and turns to step one; if the match is successful (d(x I , y J )>r), the system considers that the vehicle has The demand for driving services continues to the next step.
  • Step 4 The driving service catalogue in the driving service information processing center 4 is matched with the fusion information of the driving service demand state, and the driving service catalog is used to generate a matching algorithm:
  • sim() ⁇ 0.5
  • the driving service automatically senses failure.
  • the new service is formed by the component technology to reorganize the driving service, and the matching algorithm is generated by the driving service catalog to rematch.
  • sim()>0.5 Add new services to the driving service catalog; if sim() ⁇ 0.5, reassemble and match the driving service until the required driving service is assembled (component technology is to break down the driving service into the most basic service actions).
  • the program can be reorganized and generated through the interface.
  • the intelligent vehicle-mounted terminal 2 can directly control the braking and steering of the vehicle through the vehicle control module, timely and actively prevent the occurrence of traffic accidents, and improve the road traffic efficiency.

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Abstract

一种道路交通安全领域中车联网环境下行车服务主动感知系统及方法，包括布置在车辆上的相互连接的传感器设备（1）和智能车载终端（2），智能车载终端（2）经4G和DSRC方式与路侧设备（3）通信、经4G方式与行车服务信息处理中心（4）通信，路侧设备（3）与行车服务信息处理中心（4）之间采用4G方式通信；路侧设备（3）设置在道路的两侧，传感器设备（1）将获取到的车辆行驶信息输给智能车载终端（2），智能车载终端（2）将接收到的车辆行驶信息先初步处理，再进行信息融合后传递到路侧设备（3）与行车服务信息处理中心（4）；行车服务云计算平台对融合信息处理，输出行车服务信息，传递到路侧设备（3）和智能车载终端（2）；在保障车辆安全的前提下提供了更多的行车服务。

Description

车联网环境下行车服务主动感知系统及方法 技术领域
本发明涉及道路交通安全领域，具体是一种道路行车服务感知系统。
背景技术
目前传统的行车服务系统主要由G-BOS终端和数据处理中心两部分构成：G-BOS终端安装在车辆上，从CAN总线、传感器上采集发动机运行数据、车辆状况信息、驾驶员的操控行为，同时接收GPS卫星定位信息记录的车辆所在位置的信息，所有这些信息都通过无线通信技术传递到数据处理中心。数据处理中心通过一定的运算将接收到的数据信息进行分析、整理，为驾驶员提供不良驾驶行为警告、油耗数据、车辆运行情况、维修保养计划等建议。
传统的行车服务系统在一定程度上给驾驶员带来了便利，但是传统的系统存在着很多问题，比如：①传统的行车服务系统都是针对一类特定类型的汽车用户，客车、或货车等用户；例如G-BOS系统就是专门针对客车的系统，还不能为乘用车提供行车服务。②正是由于这些用户的特殊性，传统的行车服务系统在采集车辆信息时，主要是采集自车发动机参数、车速、驾驶员精神状态等，主要注重车辆商用过程中的经济性，而为车辆提供的安全性保障不够充分。③传统的行车服务系统提供的行车服务存在实时性与主动性不足的缺点，例如，为驾驶员提供导航服务时，仅仅考虑了一段时间内的综合拥挤程度，当有交通事故等意外发生时，导航后台系统无法及时准确识别，进而给驾驶员的路径规划依然是没有交通事故时的路径，如果交通事故发生在这条规划好的路径上，那么必然存在由于传统的行车服务系统提供的行车服务实时性与主动性不足而引起交通进一步的拥堵，甚至会影响自车的行车安全。
由此可以看出传统的行车服务系统有着很大的局限性，迫切需要设计一种适应性广、保障行车安全，实时性与主动性兼备的行车服务系统。
发明内容
本发明针对上述传统的行车服务系统存在的适用范围小、行车安全性保障不足、提供的行车服务缺乏实时性与主动性的缺点，提出一种在车联网环境下的行车服务主动感知系统及方法，可以解决传统的行车服务系统的缺点，为驾驶员提供实时、主动的行车服务，保障行车安全。
为了达到上述目的，本发明一种车联网环境下行车服务主动感知系统采用的技术方 案如下：车联网环境下行车服务主动感知系统包括布置在车辆上的相互连接的传感器设备和智能车载终端智能车载终端经4G和DSRC方式与路侧设备通信、经4G方式与行车服务信息处理中心通信，路侧设备与行车服务信息处理中心之间采用4G方式通信；传感器设备包括摄像头、OBD模块、雷达传感器、GPS差分模块、方向盘转角传感器和档位信息传感器；智能车载终端包含电子控制单元、视频处理模块、蓝牙模块和车辆控制模块；路侧设备设置在道路的两侧，包含存储模块和ECU；行车服务信息处理中心包含行车服务云计算平台、行车信息状态库和行车服务目录库；传感器设备将获取到的车辆行驶信息输给智能车载终端，智能车载终端将接收到的车辆行驶信息先初步处理，再进行信息融合后传递到路侧设备与行车服务信息处理中心；行车服务云计算平台对融合信息处理，输出行车服务信息，传递到路侧设备和智能车载终端。
本发明一种车联网环境下行车服务主动感知系统的主动感知方法采用的技术方案包含以下步骤：
A、所述传感器设备将实时采集的信息传送到电子控制单元，电子控制单元对所有信息进行融合处理；
B、所述路侧设备监测区域内的车辆行驶，当检测到车辆异常行驶时，发出警示信息，生成危险信息代码传送到所述行车服务信息处理中心；
C、行车服务信息处理中心优先处理危险信息代码，同时所述行车信息状态库与接收到的融合信息进行匹配，采用服务需求状态匹配算法确定车辆当前是否处于行车服务需求状态，若是，所述行车服务目录库与有行车服务需求状态的融合信息进行匹配，采用行车服务目录生成匹配算法生成行车服务目录，将行车服务目录推送给需求车辆。
本发明采用上述技术方案后的优点在于：
1、本发明系统的使用范围更广。在车联网环境下，对于一切安装了本发明系统的车辆，行车服务信息处理中心都可以为其提供行车服务，不再局限于客车还是货运车辆等类型，行车服务信息处理中心能够根据接收到的路侧设备、传感器采集信息主动为车主提供安全预警、路径规划等服务。
2、本发明系统更加注重车辆行驶安全。由于本系统的传感器布置更多，不仅可以采集被服务车辆自身的车辆运行参数，而且可以采集被服务车辆前方车辆的行驶参数，依赖于车联网环境下信息的高速传输和行车服务信息处理中心数据库及强大的后台云计算平台，最大限度地保证车辆的行驶安全，在保障车辆安全的前提下为车辆提供更多的行车服务。
3、本发明系统实现行车服务由“请求-响应式”传统行车服务转化为“自动识别-主动推送”模式，被服务车辆不像传统的行车服务系统那样只对自车的车辆运行参数进行监控，通过对车辆安装传感器与智能车载终端，借助成熟的无线通信技术，实现传感设备实时采集信息的实时传递，路侧设备及行车服务信息处理中心接收到经过特征提取的行驶信息，快速、自动判断行车服务的需求，使行车服务的感知过程自动化，以便发生交通事故等意外时有更加充足的时间应对，及时自动识别，保障车辆行驶安全、减缓交通拥堵。
4、本发明系统通过行车服务信息处理中心的行车服务构件库自主生成服务，最终实现向用户主动推送相应的服务并对服务质量提供有效的保障。被服务车辆的传感器采集到的信息经过智能车载终端的处理提取特征信息，在行车信息状态库的支持下确定当前车辆行驶有无行车服务需求状态，在确定有行车服务的需求时，特征信息在行车服务目录库的支持下进行搜索匹配，最终生成行车服务的目录。
附图说明
以下结合附图和具体实施方式对本发明作进一步详细描述。
图1为本发明所述车联网环境下行车服务主动感知系统的整体硬件连接框图；
图2为本发明所述车联网环境下行车服务主动感知方法的整体流程图。
具体实施方式
如图1所示，车联网环境下行车服务主动感知系统由传感器设备1、智能车载终端2、路侧设备3和行车服务信息处理中心4四部分组成。其中，传感器设备1和智能车载终端2布置在车辆上，传感器设备1和智能车载终端2在每辆应用本系统的车辆都进行安装。路侧设备3布置在智能路网上，后台的行车服务信息处理中心4包含行车信息状态库、行车服务目录库及强大的行车服务云计算平台。
车内的传感器设备1和智能车载终端2都采用CAN总线和专用硬线连接的方式获得自车运行数据。智能车载终端2与路侧设备3之间的通信采用4G方式和DSRC(专用短程无线通信802.11p)通信，以满足高速移动下的通信要求。智能车载终端2与行车服务信息处理中心4采用4G方式直接通信，或是经路侧设备3转发到行车服务信息处理中心4；路侧设备3与行车服务信息处理中心4之间采用4G方式进行通信。
传感器设备1包括摄像头、OBD模块(车载自诊断系统)、雷达传感器、GPS差分模块以及方向盘转角传感器、档位信息传感器。其中，摄像头提供前方车辆的视频与图像信息。OBD模块用于获取本车(行车主动服务车辆)的车速v1、加速度a1、发动机转 速n以及排气系统运行参数、车辆故障代码X。雷达传感器在车辆行驶过程中实时检测前车(前方行驶车辆)的速度v2和加速度a2、本车与前车的相对速度vrel、本车与前车之间距离s、前车ID、前车相对本车的方位角θ信息。GPS差分模块用于获取经过差分的车辆精确地理位置信息：经度、纬度、高度的坐标信息。方向盘转角传感器用于获取方向盘转角
Figure PCTCN2016099511-appb-000001
档位信息传感器用于获取车辆当前档位信息N。
传感器设备1中的所有部件获得的车辆行驶参数信息都实时输出给智能车载终端2。OBD模块和智能车载终端2之间采用蓝牙连接进行通信。
智能车载终端2包括电子控制单元、视频处理模块、蓝牙模块、通信模块一和车辆控制模块。其中，通信模块一包含DSRC(专用短程无线通信)通信模块与4G通信模块。传感器设备1中的摄像头获得的前方车辆的视频与图像信息输入视频处理模块，经过视频处理模块转化为数字信息，传输给电子控制单元处理。传感器设备1中的OBD模块所获取的本车的车速v1、加速度a1、发动机转速n、排气系统运行参数和车辆故障代码X信息经过智能车载终端2中的蓝牙模块实时传递到电子控制单元，电子控制单元将这些信息经处理后再传送到路侧设备3。传感器设备1中的雷达传感器、GPS差分模块、方向盘转角传感器和档位信息传感器分别通过串口直接传输给电子控制单元。电子控制单元将GPS差分模块获得的经度、纬度、高度的GPS坐标信息解算为空间直角坐标系下的xyz坐标，同时将GPS坐标、xyz坐标打包发送给路侧设备3。通信模块一中的DSRC通信模块用于在车辆行驶过程中与路侧设备3进行通信，接收路侧设备3的决策指令信号，4G通信模块用于与行车服务信息处理中心4进行通信，接收行车服务信息处理中心4的行车服务决策指令信号。电子控制单元将接收到的车辆行驶信息先进行初步处理，再进行信息融合后传递到路侧设备3与行车服务信息处理中心4。
电子控制单元的输出端与车辆控制模块相连，用于执行路侧设备3、行车服务信息处理中心4传来的服务决策指令，对车辆进行提示甚至控制车辆进行制动、转向等操作，保障车辆行驶安全。
路侧设备3包含存储模块、ECU和通信模块二，ECU分别连接存储模块和通信模块二，通信模块二由DSRC通信模块与4G/光纤通信模块组成。路侧设备3通过其通信模块二与智能车载终端2中的通信模块一互连。路侧设备3安装在道路的两侧，考虑到障碍物对信号的干扰，路侧设备3尽量布置在较高的位置，可以分别与智能车载终端2和行车服务信息处理中心4进行通信，并具有一定的区域决策能力。
路侧设备3接收智能车载终端2传送来的本路段上的所有车辆GPS坐标、空间直角 坐标系坐标(x1，y1，z1),…,(xn，yn，zn)及本车速度v1,v2,…,vn，实时监测当前路段的交通流量、车辆平均行驶速度、交通密度这些宏观交通数据，其中1～n为本路段的车辆编号。
路侧设备3中的存储模块中存储有本路段设定的限速vx和坐标信息，经通信模块二的4G/光纤通信方式传送到行车服务信息处理中心4中。
路侧设备3中的ECU对接收到的信息进行区域性的决策处理，ECU重点监测本路段逆行、超速、异常停车等异常行驶行为。路侧设备3具体监测车辆异常行驶的方法是：ECU根据智能车载终端2发来的空间直角坐标(x,y,z)及其变化趋势可判断当前车辆的行驶车道与行驶方向，本路段车辆在当前正常行驶时坐标为正向变化，坐标反向变化时为逆行，若逆行时，则ECU向本路段内车辆发出警报信息并通过光纤通信将危险信息代码传递给行车服务信息处理中心4。如果正常行驶车道上的车辆速度vn>vx且超速持续时间t>4s时，ECU判定有车辆超速，经通信模块二的DSRC通信方式向在该车行驶方向前方的车辆发送警示信息，经光纤和4G通信向行车服务信息处理中心4发送感知到的危险信息代码，行车服务信息处理中心4再做进一步的计算处理，其中，vn为车辆n的当前行驶速度，vx为当前路段设定的限速值。同时，当路侧设备3监测到异常行驶行为时，给本区域的车辆推送警示信息代码，经通信模块二的DSRC通信方式传送给智能车载终端2的通信模块一，智能车载终端2接收到路侧设备3传送的警示信息代码后，解析代码并将其具体预警消息在智能车载终端2进行显示。
行车服务信息处理中心4包括行车服务云计算平台、行车信息状态库、行车服务目录库、通信模块三。其中，通信模块三由DSRC通信模块与4G/光纤通信模块组成，分别与通信模块一和通信模块二以DSRC或4G/光纤的形式通信。行车信息状态库中储存行车需求发生时间窗内的经过信息融合的传感器设备采集信息，传感器设备1中的电子控制单元将信息融合后传递到行车服务信息处理中心4，储存在行车信息状态库中。行车服务目录库中储存本系统可以直接提供的行车服务目录描述。行车信息状态库与行车服务目录库通过外码链接，以保证行车信息状态库匹配到有行车服务需求时，可以快速提供行车服务目录库中已有的服务。
路侧设备3的危险信息代码和在智能车载终端2经过初步处理、信息融合的传感器设备采集信息分别输入到行车服务云计算平台。行车服务云计算平台优先处理路侧设备3的危险信息代码和智能车载终端2中的车辆故障代码X，并立即触发这些代码对应的行车服务目录库中的行车服务。
行车服务云计算平台4对智能车载终端2传来的融合信息进行如下处理：首先，将融合信息与行车信息状态库中的服务需求状态匹配算法进行匹配，判断当前是否有行车服务的需求；在确定有行车服务需求后，将融合信息与行车服务目录库中的行车服务目录生成匹配算法进行匹配，得到当前车辆所需的行车服务。行车服务云计算平台4的输出为系统自动感知到的行车服务信息，经通信模块三传递到路侧设备3和智能车载终端2，通过智能车载终端2显示预警信息或是在紧急情况下智能车载终端2对车辆控制模块发出指令，控制车辆减速、停车。当导航行驶路线上发生交通事故时，行车服务信息处理中心4接收到信息并计算当前最佳行驶路线，能够及时推送消息提示驾驶员，避免车辆行驶进入事故影响路段，耽误自车行程。
行车信息状态库和行车服务目录库的构建流程如下：第一，为了便于后续的数据处理，对行车服务按照服务的紧急程度进行总体分类，依次为：安全类服务(包括危险警示、极度危险情况下控制车辆)、高效类服务(实时导航、车辆维修保养提醒等)、便捷类服务(通过第三方实现预定餐厅、酒店等服务)。第二，数据库结构设计为分类树形式，形成3大类行车服务、道路交通场景下的车辆行驶采集数据、通过外码链接的行车服务三级数据表格，并分别建立“人-车-路-环境”的静态表和动态表；其中静态表主要存放一些不常变化的参数，如：人(车主性别，年龄，驾龄)、车(车型，长、宽、高，最大加速度等)、路(道路类型、车道数量等)、路侧设备3的危险信息代码及其对应的含义；动态表用于存放数据采集过程中随时间变化的动态数据，如：人(眼睛注视方向，眨眼频率等)、车(ID，时间，速度，加速度等)、路(起点GPS定位信息，止点GPS定位信息，事件描述信息等)、环境(温度，路面附着系数等)。
行车服务云计算平台所用的匹配算法如下：
1、所述服务需求状态匹配算法。采用适用于高速网络环境下的数据流比较算法。该算法的输入为传感器实时采集并经过特征提取的数据集合A＝{x1,x2,…,xi}；行车信息状态数据集合B＝{y1,y2,…,yj}。算法给定一个相似半径r和滑动窗口值k，则A和B的相似度计算公式如下：
Figure PCTCN2016099511-appb-000002
其中，d(xI,yJ)为相似距离测度函数，
Figure PCTCN2016099511-appb-000003
表示xi与yj之间的汉明距离，ωij为数据段xi与yj的欧氏距离，rAB表示数据集合A与数据集合B的相似度，k/rAB表示数据 集合A与数据集合B的同类数据加权匹配斜率的倒数，当d(xI,yJ)>r时，则系统判断有行车服务的需求。
2、所述行车服务目录生成匹配算法。行车信息状态库和行车服务目录库是以分类树的形式设计的数据库，行车服务目录生成匹配算法就是根据分类树中的节点(p,q)之间的语义距离dis(p,q)计算出节点代表的概念(Cp,Cq)之间的相似度，用sim(Cp,Cq)表示，并将相似度做归一化处理，即sim(Cp,Cq)∈(0,1)，
Figure PCTCN2016099511-appb-000004
其中，当分类树中的节点p,q为树中相同节点时，dis(p,q)＝0；p,q有路径到达时，dis(p,q)≠0；p,q之间在分类树中没有路径到达时，dis(p,q)＝∞；当相似度sim(Cp,Cq)计算结果为1时，表示生成的服务目录为精确匹配，此时生成的行车服务目录与需求服务目录相同或是需求服务目录的子类；相似度在(0.5,1)时，表示生成的服务目录为可替代匹配，此时形成的行车服务目录包含需求服务，但不是其直接父类；相似度在(0,0.5]时，表示生成的服务目录为包含匹配，此时的行车服务目录为需求服务目录的子集；相似度为0时，表示服务目录匹配失败。
如图2所示，为本发明所述车联网环境下行车服务主动感知系统实现行车服务主动感知的整体流程图，行车服务的主动感知流程如下：
步骤一：交通信息采集：传感器设备1实时采集自车车辆运行信息，包括自车车速v1、加速度a1、方向盘转角
Figure PCTCN2016099511-appb-000005
发动机转速n、前车行驶信息及前方道路信息(道路图像及视频信息)，传递到智能车载终端。其中前车行驶信息包括前车的车辆ID、车辆行驶的速度v2、加速度a2、自车与前车距离s。
步骤二：多元/多源信息融合：智能车载终端2中的视频处理模块将视频和图像信息进行特征提取，处理成为可识别的车辆、车道线信息；智能车载终端2的蓝牙模块将OBD模块采集到的信息传输给电子控制单元，电子控制单元将GPS差分模块获取的坐标信息解算为空间直角坐标系xyz下的(x，y，z)坐标，其它传感器采集到的信息通过串口传输给电子控制单元，对所有传感器采集到的信息采用成熟且适用于计算机实时处理和运算的卡尔曼滤波方法进行滤波，将传感器采集到的信号去掉白噪声，然后进行多元/多源 信息融合。多元/多源信息融合的输入是经过特征提取后的图像数据(数字信息)、GPS坐标解算后的xyz坐标以及传感器传来的电子控制单元可直接处理的(v1，a1，n，
Figure PCTCN2016099511-appb-000006
N，v2，a2，vrel，s，ID，θ)信息。多元/多源信息融合的输出为经过标准化的且便于异常事件检测的数据组，如{(x,y,z),(x,y,z,vn),(v1,a1,s,v2,a2,vrel),…}。其中，vn为ID为n的车辆当前行驶速度。智能车载终端2将融合的信息通过DSRC发送给路侧设备3，路侧设备3根据采集到的区域内车辆的运行信息，监控区域内的车辆行驶安全，当检测到车辆行驶异常时，生成本区域的行车策略并推送给本区域车辆，通过智能车载终端2向驾驶员发出警示信息；当路侧设备3检测到车辆有异常行驶的趋势(例如驾驶员任意变道但未对周围车辆造成影响，xyz坐标与道路坐标对比判断有频繁的横向位移)时，生成危险信息代码，通过通信模块二的4G/光纤通信向行车服务信息中心4报告，行车服务信息处理中心4进行分析、计算和处理；同时，智能车载终端2通过4G通信将采集的信息直接发送给行车服务信息处理中心4。
步骤三：融合信息与状态信息匹配：行车服务信息处理中心4优先处理路侧设备3发送的危险信息代码，调用静态表即可得到危险信息的具体内容，必要时发送给路侧设备3广播范围之外的车辆；行车服务信息处理中心4根据自身储存的行车信息状态库(动态表)与接收到的融合信息进行匹配，采用服务需求状态匹配算法，确定车辆当前是否处于行车服务需求状态。若匹配不成功(d(xI,yJ)≤r)，则系统认为无行车服务需求，转步骤一；若匹配成功(d(xI,yJ)>r)，则系统认为车辆有行车服务的需求，继续下一步。
步骤四：行车服务信息处理中心4中的行车服务目录库与有行车服务需求状态的融合信息进行匹配，采用行车服务目录生成匹配算法：
1.若匹配成功，即0.5<sim()≤1时，则行车服务自动感知成功，行车服务自动感知系统生成服务目录，本系统的功能完成。
2.若匹配失败，sim()≤0.5时，则行车服务自动感知失败。在确定行车服务需求的条件下，行车服务目录库匹配失败时，通过构件技术对行车服务重组形成新的服务，并用行车服务目录生成匹配算法重新匹配，当相似度sim()>0.5时，在行车服务目录库中添加新的服务；若sim()<0.5，再对行车服务进行重新组装、匹配，直到组装出需要的行车服务(构件技术就是通过把行车服务细分成最基础的服务动作程序，通过接口可进行重组、生成，当匹配不出已存在的行车服务时，将这些基础服务动作重新组装出新的行车服务)，生成行车服务目录，进一步生成具体的行车服务后，将行车服务推送给需求车辆，调用静态表，根据车辆ID将匹配度最高的行车服务推送至该车辆的智能车载终端2进行警示。 在情况危急时，智能车载终端2可通过车辆控制模块直接控制车辆制动、转向等，及时、主动地防止交通事故的发生，提高道路通行效率。

Claims (9)

  1. 一种车联网环境下行车服务主动感知系统，包括布置在车辆上的相互连接的传感器设备(1)和智能车载终端(2)，其特征是：智能车载终端(2)经4G和DSRC方式与路侧设备(3)通信、经4G方式与行车服务信息处理中心(4)通信，路侧设备(3)与行车服务信息处理中心(4)之间采用4G方式通信；传感器设备(1)包括摄像头、OBD模块、雷达传感器、GPS差分模块、方向盘转角传感器和档位信息传感器；智能车载终端(2)包含电子控制单元、视频处理模块、蓝牙模块和车辆控制模块；路侧设备(3)设置在道路的两侧，包含存储模块和ECU；行车服务信息处理中心(4)包含行车服务云计算平台、行车信息状态库和行车服务目录库；传感器设备(1)将获取到的车辆行驶信息输给智能车载终端(2)，智能车载终端(2)将接收到的车辆行驶信息先初步处理，再进行信息融合后传递到路侧设备(3)与行车服务信息处理中心(4)；行车服务云计算平台(4)对融合信息处理，输出行车服务信息，传递到路侧设备(3)和智能车载终端(2)。
  2. 根据权利要求1所述车联网环境下行车服务主动感知系统，其特征是：所述摄像头获取前方车辆的视频与图像信息，经所述视频处理模块将信息处理后传输给所述电子控制单元；所述OBD模块获取本车的车速、加速度、发动机转速以及排气系统运行参数和车辆故障代码信息，并经所述蓝牙模块传输给所述电子控制单元；所述雷达传感器检测前车的速度和加速度、本车与前车的相对速度、本车与前车之间距离、前车、前车相对本车的方位角信息并输入所述电子控制单元；所述GPS差分模块获取车辆经度、纬度、高度的GPS坐标信息并输入所述电子控制单元；所述方向盘转角传感器获取方向盘转角信息并输入所述电子控制单元，所述档位信息传感器获取车辆当前档位信息并输入所述电子控制单元。
  3. 根据权利要求2所述车联网环境下行车服务主动感知系统，其特征是：所述电子控制单元将GPS坐标信息解算为空间直角坐标系下的xyz坐标，将GPS坐标、xyz坐标信息发送给路侧设备(3)，路侧设备(3)还接收智能车载终端(2)传送来的本路段上的所有车辆的本车速度。
  4. 根据权利要求2所述车联网环境下行车服务主动感知系统，其特征是：所述行车信息状态库中储存有所述融合信息，所述行车信息状态库与所述行车服务目录库通过外码链接。
  5. 一种如权利要求1所述车联网环境下行车服务主动感知系统的主动感知方法，其特征是包含以下步骤：
    A、所述传感器设备(1)将实时采集的信息传送到电子控制单元，电子控制单元对所有信息进行融合处理；
    B、所述路侧设备(3)监测区域内的车辆行驶，当检测到车辆异常行驶时，发出警示信息，生成危险信息代码传送到所述行车服务信息处理中心(4)；
    C、行车服务信息处理中心(4)优先处理危险信息代码，同时所述行车信息状态库与接收到的融合信息进行匹配，采用服务需求状态匹配算法确定车辆当前是否处于行车服务需求状态，若是，所述行车服务目录库与有行车服务需求状态的融合信息进行匹配，采用行车服务目录生成匹配算法生成行车服务目录，将行车服务目录推送给需求车辆。
  6. 根据权利要求5所述车联网环境下行车服务主动感知系统的主动感知方法，其特征是：步骤C中，行车服务推送目录给需求车辆后，智能车载终端(2)能通过所述车辆控制模块直接控制车辆制动、转向。
  7. 根据权利要求5所述车联网环境下行车服务主动感知系统的主动感知方法，其特征是：步骤B中，所述路侧设备(3)监测车辆异常行驶的方法是：本路段车辆在当前正常行驶时坐标为正向变化，坐标反向变化时为逆行；如果正常行驶车道上的车辆速度vn>vx且超速持续时间t>4s，有车辆超速；若逆行或超速时，所述ECU向本路段内车辆发出警报信息并将危险信息代码传递给行车服务信息处理中心(4)；vn为车辆n的当前行驶速度，vx为当前路段设定的限速值。
  8. 根据权利要求5所述车联网环境下行车服务主动感知系统的主动感知方法，其特征是：步骤C中，所述服务需求状态匹配算法是：将传感器采集并经过特征提取的数据集合A＝{x1,x2,…,xi}和行车信息状态数据集合B＝{y1,y2,…,yj}作相似度计算，给定一个相似半径r和滑动窗口值k：
    Figure PCTCN2016099511-appb-100001
    d(xI,yJ)为相似距离测度函数，
    Figure PCTCN2016099511-appb-100002
    表示xi与yj之间的汉明距离，ωij为数据段xi与yj的欧氏距离，rAB表示数据集合A与数据集合B的相似度，当d(xI,yJ)>r时，则判断有行车服务需求。
  9. 根据权利要求5所述车联网环境下行车服务主动感知系统的主动感知方法，其特征是：步骤C中，所述行车服务目录生成匹配算法是：行车信息状态库和行车服务目录库是以分类树的形式设计的数据库，根据分类树中的节点(p,q)之间的语义距离dis(p,q)计算出节点代表的概念(Cp,Cq)之间的相似度sim(Cp,Cq)，当相似度sim(Cp,Cq)为1时，生成的服务目录为精确匹配；相似度在(0.5,1)时，生成的服务目录为可替代匹配；相似度在 (0,0.5]时，生成的服务目录为包含匹配；相似度为0时，服务目录匹配失败。
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