ADAS system based on passive optical network and multi-sensor signal synchronization method

Abstract

The invention discloses an ADAS system based on a passive optical network and a multi-sensor signal synchronization method, and belongs to the technical field of intelligent driving system multi-sensor data fusion, and the method comprises the steps that after the passive optical network is constructed based on an OLT MAC chip and an ONU MAC chip, a central processor sends control information to a sensor, and the sensor collects and feeds back sensing data after receiving the control information; the OLT MAC chip distributes bandwidth and time slot for uplink sensing data, and the ONU MAC chip uploads the sensing data according to the distributed bandwidth and time slot; the central processing unit receives a first clock signal sent by an external clock source, performs time synchronization and then sends a second clock signal to the sensor, and the sensor performs time synchronization acquisition and feeds back sensing data; each of the first clock signal and the second clock signal includes time information and a PPS pulse. The ADAS system is constructed based on the optical network, the transmission performance and stability of the system are improved, and the fusion efficiency and precision of the multi-source sensing data are improved through time synchronization of the sensing units.

Description

Technical Field

[0001] The present application relates to the technical field of multi-sensor data fusion of intelligent driving systems, and in particular to an ADAS system based on a passive optical network and a multi-sensor signal synchronization method. Background Art

[0002] The current camera transmission solution uses LVDS (Low-Voltage Differential Signaling) technology, which is widely used in ADAS (Advanced Driving Assistance System). However, with the increasing intelligence of automobiles and the growing demand for high resolution and low transmission delay of sensors, the LVDS solution has gradually exposed its shortcomings:

[0003] 1. It is difficult to support high-resolution and high-frame-rate video data transmission due to bandwidth limitations;

[0004] 2. The improvement of sensor resolution has doubled the data transmission bandwidth, but the transmission distance of high-speed data is limited due to signal attenuation and distortion in copper cable transmission;

[0005] 3. Existing ADAS systems are highly sensitive to electromagnetic interference;

[0006] 4. The wiring harness connection between sensors and domain control / central processing units in existing ADAS systems is mostly point-to-point, which is highly complex, costly, and has insufficient system scalability;

[0007] 5. For the entire ADAS system, there are many types of sensors and the communication protocols are highly complex. For example, camera video data is serialized through SerDes and then transmitted point-to-point through LVDS; LiDAR usually communicates based on Ethernet interface; The complexity of signals and protocols leads to poor synchronization and difficulty in fusion when the ADAS system processes data fusion of multiple sensors. Summary of the invention

[0008] The present application provides an ADAS system based on a passive optical network and a multi-sensor signal synchronization method, which can solve the technical problems of poor synchronization and difficult fusion of multi-sensors in the ADAS system existing in the prior art.

[0009] In a first aspect, an embodiment of the present application provides an ADAS system based on a passive optical network, the system comprising a central processing unit, the central processing unit connected to a plurality of optical splitters via optical fibers, each optical splitter connected to a plurality of sensor units via optical fibers, the central processing unit comprising a central processing unit and an OLT MAC chip connected to each other, the sensor unit comprising a sensor and an ONU MAC chip connected in sequence, and a passive optical network is formed based on the OLT MAC chip and the ONU MAC chip;

[0010] The central processor is used to send control information to the sensor through the passive optical network downlink. After receiving the control information, the sensor collects sensor data and sends the sensor data to the central processor through the passive optical network uplink. The OLT MAC chip is used to allocate bandwidth and time slots for the uplink sensor data, and the ONU MAC chip uploads the sensor data according to the allocated bandwidth and time slot.

[0011] The central processor is also used to receive a first clock signal sent by an external clock source, and after synchronizing itself, send a second clock signal to the sensor, and the sensor synchronizes itself according to the second clock signal; both the first clock signal and the second clock signal include time information and PPS pulses.

[0012] In combination with the first aspect, in one implementation, each of the optical splitters corresponds to a vehicle body area and is used to connect all sensor units in the vehicle body area.

[0013] In combination with the first aspect, in one implementation, the types of the sensing units include cameras and lidars.

[0014] In combination with the first aspect, in one implementation, the OLT MAC chip is further used to encapsulate and decapsulate data frames for uplink and downlink data;

[0015] The ONU MAC chip is also used to encapsulate and decapsulate data frames for uplink and downlink data.

[0016] In combination with the first aspect, in one implementation, the sensor embeds a timestamp in the sensing data and feeds it back to the central processing unit;

[0017] The central processing unit performs data fusion based on the time stamps of each sensor data.

[0018] In combination with the first aspect, in one embodiment, the central processor includes a central processing module and a first FPGA connected to each other, the first FPGA is connected to the OLT MAC chip, the central processing module is used to receive the first clock signal, and output control information and time information in the second clock signal, and the FPGA is used to perform protocol conversion and encapsulation and decapsulation of uplink and downlink data.

[0019] In combination with the first aspect, in one implementation, the OLT MAC chip is further configured to receive a PPS pulse in the first clock signal, and send the PPS pulse as a PPS pulse in the second clock signal to the sensor unit.

[0020] In combination with the first aspect, in one embodiment, the sensor includes a sensing module and a second FPGA connected to each other, the second FPGA is connected to the ONU MAC chip, the sensing module is used to receive control information, and collect and feedback sensing data according to the control information, the ONU MAC chip is used to extract the PPS signal in the second clock signal, the second FPGA is used to extract the time information in the second clock signal, and synchronize the sensor itself according to the time information in the second clock signal and the PPS signal.

[0021] In combination with the first aspect, in one implementation, the central processing unit further includes connecting the OLT MAC chip and a first optical transceiver, the first optical transceiver being used to receive and receive optical signals;

[0022] The sensing unit also includes a second optical transceiver connected to the ONU MAC chip, and the second optical transceiver is used for transmitting and receiving optical signals.

[0023] In a second aspect, an embodiment of the present application provides a multi-sensor signal synchronization method for an ADAS system based on a passive optical network, based on the ADAS system based on the passive optical network; the multi-sensor signal synchronization method includes:

[0024] The central processor receives a first clock signal sent by an external clock source, and after synchronizing itself, sends a second clock signal to the sensor through a passive optical network downlink, and the sensor synchronizes itself according to the second clock signal;

[0025] The central processor sends control information to the sensor through the passive optical network downlink. After receiving the control information, the sensor collects sensing data and sends the sensing data to the central processor through the passive optical network uplink.

[0026] The beneficial effects brought by the technical solution provided in the embodiments of the present application include:

[0027] Build an ADAS system based on optical network to improve system transmission performance and stability, and improve the fusion efficiency and accuracy of multi-source sensor data through time synchronization of each sensor unit. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] Figure 1 This is a schematic diagram of the architecture of an embodiment of an ADAS system based on a passive optical network of the present application;

[0029] Figure 2This is a schematic diagram of the time synchronization process of the ADAS system based on the passive optical network of this application;

[0030] Figure 3 This is a functional module diagram of an embodiment of a central processing unit of the present application;

[0031] Figure 4 This is a schematic diagram of the functional modules of an embodiment of a sensor unit of the present application;

[0032] Figure 5 This is a flow chart of an embodiment of a multi-sensor signal synchronization method for an ADAS system based on a passive optical network of the present application;

[0033] Figure 6 It is a schematic diagram comparing the time synchronization principle of the existing ADAS system and the time synchronization principle of the ADAS system of the present application. DETAILED DESCRIPTION

[0034] In order to enable those skilled in the art to better understand the solution of the present application, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0035] First, some technical terms in the present application are explained to facilitate those skilled in the art to understand the present application.

[0036] PON: Passive Optical Network, translated into Chinese as Passive Optical Network, is an efficient point-to-multipoint fiber access technology that uses a passive optical splitter to split a fiber into multiple paths to achieve point-to-multipoint data transmission. PON is mainly composed of OLT (Optical Line Terminal), ONU (Optical Network Unit), and optical splitter.

[0037] PON network time synchronization: OLT discovers and registers ONUs during the initialization phase, performs initial ranging (distance measurement) to measure the distance between ONUs and OLT, and then OLT continuously embeds accurate timestamps in downstream frames. ONUs receive timestamps and perform delay compensation based on ranging results, while using phase-locked loop technology to recover clock information from data streams. To maintain synchronization accuracy, the system periodically performs ranging and continuously updates timestamps.

[0038] ADAS system: uses multiple sensors, advanced processors and artificial intelligence algorithms to perceive the vehicle's surrounding environment and provide various driving assistance functions such as adaptive cruise control, lane keeping, and automatic emergency braking, aiming to improve driving safety, comfort and efficiency.

[0039] Multi-sensor synchronization: Coordinate and integrate data from multiple different sensors (such as cameras, lidar, and radar) in the ADAS system to keep the data consistent in time for accurate environmental perception and decision-making.

[0040] In order to make the objectives, technical solutions and advantages of the present application clearer, the implementation methods of the present application will be further described in detail below with reference to the accompanying drawings.

[0041] In a first aspect, an embodiment of the present application provides an ADAS system based on a passive optical network.

[0042] In one embodiment, referring to Figure 1 , Figure 1 FIG. 1 is a schematic diagram of the architecture of an embodiment of an ADAS system based on a passive optical network of the present application. Figure 1 As shown, the ADAS system based on the passive optical network includes a central processing unit, which is connected to multiple splitters through optical fibers, and each splitter is connected to multiple sensor units through optical fibers. The central processing unit includes a central processing unit and an OLT MAC chip connected to each other, and the sensor unit includes a sensor and an ONU MAC chip connected in sequence. A passive optical network is formed based on the OLT MAC chip, the ONU MAC chip, the optical transceiver, the splitter, the optical fiber, etc. The passive optical network has significant advantages over the active optical network in terms of cost, certainty, and wiring harness complexity.

[0043] The central processor is used to send control information to the sensor through the passive optical network downlink. After receiving the control information, the sensor collects sensor data and sends the sensor data to the central processor through the passive optical network uplink. The OLTMAC chip is used to allocate bandwidth and time slots for uplink sensor data. The ONU MAC chip uploads sensor data according to the allocated bandwidth and time slots.

[0044] The central processor is also used to receive a first clock signal sent by an external clock source, and after time synchronization is performed on itself, send a second clock signal to the sensor, and the sensor performs time synchronization on itself according to the second clock signal. Both the first clock signal and the second clock signal include time information and PPS pulses.

[0045] Compared with the prior art in which each sensor data acquisition device is connected to the central processing unit in a point-to-point manner, and the connection line between each sensor data acquisition device and the central processing unit transmits traditional electrical signals, in this embodiment, an optical network architecture is constructed by setting an OLT MAC chip in the central processing unit and an ONU MAC chip in the sensor unit. The central processing unit with an added OLT MAC chip can be regarded as the OLT end in the optical network, and the sensor unit with an added ONU MAC chip can be regarded as the ONU end in the optical network. After connecting multiple sensor units to an optical splitter, they are connected to the central processing unit through the optical splitter, which can greatly reduce the number and length of lines, reduce the weight of the wiring harness, simplify wiring, and reduce system complexity and cost. In addition, compared with traditional copper cable transmission, optical fiber transmission has stronger anti-electromagnetic interference ability, thereby improving the stability and reliability of the system.

[0046] Furthermore, the OLT MAC chip allocates bandwidth and time slots for uplink sensor data. The sensor data output by multiple sensor units is converted into optical signals by the ONU MAC chip and the first optical transceiver, and then combined by the optical splitter and transmitted to the second optical transceiver and the OLT MAC chip through optical fiber. The OLT MAC chip converts the sensor data into electrical signals and transmits them to the central processor. The central processor performs data fusion on each sensor data, perceives the environment and makes decisions based on the fusion results. The optical network architecture provides higher transmission bandwidth, can support high-resolution and high-frame-rate video data transmission, and at the same time ensures extremely low transmission delay, meeting the real-time requirements of the ADAS system. Improve system transmission performance and stability.

[0047] Furthermore, after the CPU synchronizes itself with the first clock signal sent by the external clock source, it sends the second clock signal to the sensor, and the sensor synchronizes itself with the second clock signal, thus achieving high-precision time synchronization of the entire ADAS system and providing a basis for multi-sensor data fusion. Due to the precise time synchronization, data from different sensors can be sampled at the same time, greatly improving the efficiency and accuracy of data fusion.

[0048] In summary, through the time synchronization of each sensor unit, the fusion efficiency and accuracy of multi-source sensor data can be improved, a series of technical problems in signal transmission and control existing in the current ADAS system can be solved, and unified management of communications between different sensors in the ADAS system can be achieved. While improving communication performance, the system complexity and sensor fusion difficulties caused by multiple communication protocols can be solved.

[0049] Furthermore, in one embodiment, each optical splitter corresponds to a vehicle body area and is used to connect all sensor units in the vehicle body area.

[0050] Types of sensing units include cameras and lidar.

[0051] The OLT MAC chip and the ONU MAC chip are also used to encapsulate and decapsulate data frames for uplink and downlink data.

[0052] After the sensor embeds the timestamp in the sensing data, it feeds it back to the central processing unit, which combines the timestamps of each sensing data to perform data fusion.

[0053] In this embodiment, the ADAS system architecture is based on the "central processing + regional" automotive electronic and electrical architecture design. The main components include a central processing unit, a splitter, an optical fiber, a camera (including front view, rear view, and surround view) and a laser radar, which form four optical networks according to the left front, left rear, right front, and right rear areas of the vehicle body. Among them, the central processing unit is the core of the system, responsible for processing data streams from all sensors for road condition analysis and decision making. At the same time, as the OLT node of each optical network, it is responsible for managing the optical networks in each region. The splitter is a key node of the system, responsible for the distribution and convergence of optical signals. As the environmental perception components of the ADAS system and the ONU nodes of the optical network, the camera and the laser radar are responsible for uploading the video and 3D point cloud data to the central processing unit. After the central processing unit combines the timestamp for data fusion, it makes analysis decisions based on the fusion results.

[0054] When the system is running, each sensor continuously collects data about the vehicle's surrounding environment and transmits it to the central processing unit in real time through the optical network. The central processing unit processes this data in real time for environmental perception and decision-making. The bandwidth required for each sensor transmission is allocated by the central processing unit. The uplink data of different sensors in an optical network is transmitted in a time-division multiplexing manner through the splitter, and the downlink control data of the central processing unit is transmitted to each ONU node in a broadcast manner through the splitter.

[0055] This physical architecture provides ultra-high transmission bandwidth and extremely low transmission delay for the ADAS system by introducing optical fiber, which greatly reduces the weight of the wiring harness. At the same time, with the help of the characteristics of the optical network, it ensures the determinism of data transmission, simplifies wiring, and improves the scalability of the system.

[0056] In a specific embodiment, referring to Figure 2 , Figure 2This is a schematic diagram of the time synchronization process of the ADAS system based on the passive optical network of this application. Time synchronization is a prerequisite for realizing the synchronization of multi-sensor data of the ADAS system. In this embodiment, the time synchronization of the entire ADAS system is completed by the network protocol time + PPS calibration method. The specific implementation method is to use the combined navigation system as the main clock source of the entire ADAS system, and provide the system with high-precision time information through the GPRMC navigation message + PPS pulse signal. Then the central processing unit distributes the accurate time after its own synchronization to each sensor of the ADAS system, including cameras, laser radars, etc., through the optical network through the NTP network protocol. At the same time, the PPS pulse signal from the combined navigation system will be synchronously input to the OLT MAC chip at the OLT end, and the optical network will restore the PPS pulse signal to the output at the ONU end using the ONUMAC chip through the internal time synchronization mechanism. After each sensor receives the time information, it will calibrate and compensate its own processing delay according to the PPS pulse signal of the ONU MAC chip, thereby completing the time synchronization with the main clock source. In this system, time synchronization adjustment will be performed periodically (1s) to ensure the accuracy of long-term operation. This precise time synchronization mechanism ensures that data from different sensors can be accurately fused and analyzed, providing reliable environmental perception and decision support for ADAS systems.

[0057] Further, in one embodiment, referring to Figure 3 , Figure 3 This is a functional module diagram of an embodiment of the central processing unit of the present application. The central processor includes a central processing module and a first FPGA connected to each other, the first FPGA is connected to the OLT MAC chip, the central processing module is used to receive the first clock signal, and output control information and time information in the second clock signal, and the FPGA is used to perform protocol conversion and encapsulation and decapsulation of uplink and downlink data.

[0058] In this embodiment, in order to help the existing central processing unit access the vehicle optical network architecture, four OLT MAC chips and four optical transceivers are added to the existing central processing unit to achieve Figure 1 The central processing module has a PCIe peripheral interface for data interaction. The uplink and downlink data are converted into protocols and encapsulated / decapsulated via the data processing module and Ethernet module in the first FPGA. In addition to being input into the central processing module, the GNSS PPS pulse signal is also synchronized to the four OLT MAC chips to help the OLT MAC achieve time synchronization management of the optical network.

[0059] Furthermore, in one embodiment, the OLT MAC chip is further configured to receive a PPS pulse in the first clock signal, and send the PPS pulse as a PPS pulse in the second clock signal to the sensor unit.

[0060] Further, in one embodiment, referring to Figure 4 , Figure 4 This is a functional module diagram of an embodiment of a sensor unit of the present application. The above-mentioned sensor includes a sensor module and a second FPGA connected to each other, the second FPGA is connected to the ONU MAC chip, the sensor module is used to receive control information, and collect and feedback sensor data according to the control information, the ONU MAC chip is used to extract the PPS signal in the second clock signal, the second FPGA is used to extract the time information in the second clock signal, and synchronize the sensor itself according to the time information in the second clock signal and the PPS signal.

[0061] In this embodiment, the camera consists of a lens and an image processor. The sensor module is responsible for capturing environmental data and converting it into high-quality digital images. Functions such as video signal serial processing, protocol encapsulation / decapsulation, time synchronization, and camera control are implemented by the second FPGA. The ONU MAC chip is responsible for the encapsulation / decapsulation of link layer data frames, and the second optical transceiver is responsible for the conversion of physical layer photoelectric signals.

[0062] After the camera is turned on, the ONU MAC chip will continuously receive time synchronization information and control information from the central computing unit. The network time protocol is parsed by the Ethernet module and the data processing module to submit the time information to the clock module. The clock module also receives the 1PPS pulse signal to complete the time calibration and synchronize the local time with the system time. The control information contains configuration requirements for camera pixels, frame rate, etc. After parsing, the control module completes the configuration of related parameters through I2C and periodically triggers the camera exposure through the SYNC signal.

[0063] When the camera is exposed, frame image data is collected and input into the second FPGA through the MIPI-CSI2 interface. The second FPGA is responsible for serial processing of the signal, embedding timestamps, encapsulating Ethernet protocol, and then transmitting the image data to the central computing unit through the ONU MAC chip and the second optical transceiver device.

[0064] The camera can achieve high-precision time synchronization with the car's ADAS system, and a timestamp can be embedded in the image data when the exposure is triggered. Compared with traditional on-board cameras that cannot synchronize time, the central computing unit must unify the hardware to trigger the exposure and calculate the exposure accuracy based on the delay, which has better time synchronization and greatly improves the time accuracy of the ADAS system image fusion.

[0065] Furthermore, in one embodiment, the central processing unit further includes a first optical transceiver connected to the OLT MAC chip and the optical splitter, and the first optical transceiver is used for transmitting and receiving optical signals.

[0066] The sensing unit also includes a second optical transceiver connected to the ONU MAC chip and the optical splitter, and the second optical transceiver is used for transmitting and receiving optical signals.

[0067] In this embodiment, the optical transceiver is used to combine or split the beams, thereby reducing the length of the optical fiber line.

[0068] When the system is running, the ONU MAC chip of each sensor continuously collects data about the vehicle's surrounding environment and transmits it to the central computing unit in real time through the optical fiber network. The central computing unit processes this data in real time for environmental perception and decision-making. The bandwidth required for each sensor transmission is allocated by the central computing unit. The uplink data of different sensors in an optical network is transmitted in a time-division multiplexing manner through the splitter, and the downlink control data of the central computing unit is transmitted to each ONU node in a broadcast manner through the splitter.

[0069] This physical architecture provides ultra-high transmission bandwidth and extremely low transmission delay for the ADAS system by introducing optical fiber, which greatly reduces the weight of the wiring harness. At the same time, with the help of the characteristics of the optical network, it ensures the determinism of data transmission, simplifies wiring, and improves the scalability of the system.

[0070] In a second aspect, an embodiment of the present application also provides a multi-sensor signal synchronization method for an ADAS system based on a passive optical network.

[0071] In one embodiment, referring to Figure 5 , Figure 5 FIG. 1 is a flow chart of an embodiment of a multi-sensor signal synchronization method for an ADAS system based on a passive optical network of the present application. Figure 5 As shown, the multi-sensor signal synchronization method of the ADAS system based on the passive optical network includes:

[0072] Step S1, the central processing unit receives a first clock signal sent by an external clock source, and after performing time synchronization on itself, sends a second clock signal to the sensor, and the sensor performs time synchronization on itself according to the second clock signal.

[0073] Step S2: The central processor sends control information to the sensor through the passive optical network downlink. After receiving the control information, the sensor collects sensing data and sends the sensing data to the central processor through the passive optical network uplink.

[0074] Compared with the prior art in which each sensor data acquisition device is connected to the central processing unit in a point-to-point manner, and the connection line between each sensor data acquisition device and the central processing unit transmits traditional electrical signals, in this embodiment, an optical network architecture is constructed by setting an OLT MAC chip in the central processing unit and an ONU MAC chip in the sensor unit. The central processing unit with an added OLT MAC chip can be regarded as the OLT end in the optical network, and the sensor unit with an added ONU MAC chip can be regarded as the ONU end in the optical network. After connecting multiple sensor units to an optical splitter, they are connected to the central processing unit through the optical splitter, which can greatly reduce the number and length of lines, reduce the weight of the wiring harness, simplify wiring, and reduce system complexity and cost. In addition, compared with traditional copper cable transmission, optical fiber transmission has stronger anti-electromagnetic interference ability, thereby improving the stability and reliability of the system.

[0075] Furthermore, the OLT MAC chip allocates bandwidth and time slots for uplink sensor data. The sensor data output by multiple sensor units is converted into optical signals by the ONU MAC chip, combined by the optical splitter, and transmitted to the OLT MAC chip through optical fiber. The OLT MAC chip converts the sensor data into electrical signals and transmits them to the central processor. The central processor performs data fusion on each sensor data, perceives the environment and makes decisions based on the fusion results. The optical network architecture provides higher transmission bandwidth, can support high-resolution and high-frame-rate video data transmission, and at the same time ensures extremely low transmission delay, meeting the real-time requirements of the ADAS system. Improve system transmission performance and stability.

[0076] Furthermore, after the CPU synchronizes itself with the first clock signal sent by the external clock source, it sends the second clock signal to the sensor, and the sensor synchronizes itself with the second clock signal, thus achieving high-precision time synchronization of the entire ADAS system and providing a basis for multi-sensor data fusion. Due to the precise time synchronization, data from different sensors can be sampled at the same time, greatly improving the efficiency and accuracy of data fusion.

[0077] In summary, through the time synchronization of each sensor unit, the fusion efficiency and accuracy of multi-source sensor data can be improved, a series of technical problems in signal transmission and control existing in the current ADAS system can be solved, and unified management of communications between different sensors in the ADAS system can be achieved. While improving communication performance, the system complexity and sensor fusion difficulties caused by multiple communication protocols can be solved.

[0078] In a specific embodiment, referring to Figure 6 , Figure 6The figure is a comparison diagram of the time synchronization principle of the existing ADAS system and the time synchronization principle of the ADAS system of the present application. In the traditional ADAS system, the sampling frequency of the lidar is generally 10Hz, and the sampling frequency of the camera is generally 30Hz. Due to the different triggering methods of the two sensors: the former is periodic trigger + timestamp, and the latter is hardware synchronization trigger, the different sensors in the ADAS system have large synchronization errors at the same / adjacent sampling nodes, which makes it difficult for the later data fusion. In the ADAS system based on passive optical network, multiple sensors are synchronized to a time reference, so the sampling of environmental data can be completed at the same time, which is convenient for the ADAS system data fusion and decision-making, and greatly improves the performance of high-level intelligent assisted driving.

[0079] Taking the case where the optical splitter uses passive components as an example, the beneficial effects of the present invention include:

[0080] High bandwidth and low latency: PON technology provides higher transmission bandwidth, which can support high-resolution, high-frame-rate video data transmission, while ensuring extremely low transmission latency, meeting the real-time requirements of the ADAS system.

[0081] Anti-electromagnetic interference: Compared with traditional copper cable transmission, optical fiber transmission has stronger anti-electromagnetic interference ability, which improves the stability and reliability of the system.

[0082] Simplified wiring harness: The use of PON technology greatly reduces the weight of the wiring harness, simplifies wiring, and reduces system complexity and cost.

[0083] Improve system scalability: The point-to-multipoint structure of the PON network makes the system more scalable, making it easier to add or replace sensors in the future.

[0084] Precise time synchronization: Through the network protocol time + PPS calibration method, high-precision time synchronization of the entire ADAS system is achieved, providing a basis for multi-sensor data fusion.

[0085] Improve data fusion efficiency: Due to the precise time synchronization, data from different sensors can be sampled at the same time, greatly improving the efficiency and accuracy of data fusion.

[0086] It should be noted that the serial numbers of the above-mentioned embodiments of the present application are only for description and do not represent the advantages or disadvantages of the embodiments.

[0087] The terms "including" and "having" and any variations thereof in the specification and claims of this application and the above-mentioned drawings are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device that includes a series of steps or units is not limited to the listed steps or units, but optionally includes steps or units that are not listed, or optionally includes other steps or units inherent to these processes, methods, products or devices. The terms "first", "second" and "third" are used to distinguish different objects, etc., and do not represent a sequence, nor do they limit "first", "second" and "third" to different types.

[0088] In the description of the embodiments of the present application, "exemplary", "for example" or "for example" are used to indicate examples, illustrations or descriptions. Any embodiment or design described as "exemplary", "for example" or "for example" in the embodiments of the present application should not be interpreted as being more preferred or more advantageous than other embodiments or designs. Specifically, the use of words such as "exemplary", "for example" or "for example" is intended to present related concepts in a specific way.

[0089] In the description of the embodiments of the present application, unless otherwise specified, “ / ” means or, for example, A / B can mean A or B; the “and / or” in the text is merely a description of the association relationship of associated objects, indicating that three relationships may exist, for example, A and / or B can mean: A exists alone, A and B exist at the same time, and B exists alone. In addition, in the description of the embodiments of the present application, “multiple” refers to two or more than two.

[0090] In some processes described in the embodiments of the present application, multiple operations or steps that appear in a specific order are included, but it should be understood that these operations or steps may not be executed in the order in which they appear in the embodiments of the present application or in parallel, and the sequence number of the operation is only used to distinguish the different operations, and the sequence number itself does not represent any execution order. In addition, these processes may include more or fewer operations, and these operations or steps may be executed in sequence or in parallel, and these operations or steps may be combined.

[0091] Through the description of the above implementation methods, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus a necessary general hardware platform, and of course by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present application is essentially or the part that contributes to the prior art can be embodied in the form of a software product, which is stored in a storage medium (such as ROM / RAM, disk, CD) as described above, and includes a number of instructions for a terminal device to execute the methods described in each embodiment of the present application.

[0092] The above are only preferred embodiments of the present application, and are not intended to limit the patent scope of the present application. Any equivalent structure or equivalent process transformation made using the contents of the present application specification and drawings, or directly or indirectly applied in other related technical fields, are also included in the patent protection scope of the present application.

Claims

1. An ADAS system based on a passive optical network, characterized in that: The system includes a central processing unit, the central processing unit is connected to a plurality of optical splitters through optical fibers, each optical splitter is connected to a plurality of sensor units through optical fibers, the central processing unit includes a central processing unit and an OLT MAC chip connected to each other, the sensor unit includes a sensor and an ONU MAC chip connected in sequence, and a passive optical network is formed based on the OLT MAC chip and the ONU MAC chip; The central processor is used to send control information to the sensor through the passive optical network downlink. After receiving the control information, the sensor collects sensor data and sends the sensor data to the central processor through the passive optical network uplink. The OLT MAC chip is used to allocate bandwidth and time slots for the uplink sensor data, and the ONU MAC chip uploads the sensor data according to the allocated bandwidth and time slot. The central processor is also used to receive a first clock signal sent by an external clock source, and after synchronizing itself, send a second clock signal to the sensor, and the sensor synchronizes itself according to the second clock signal; both the first clock signal and the second clock signal include time information and PPS pulses.

2. The ADAS system based on passive optical network as claimed in claim 1, characterized in that: Each of the optical splitters corresponds to a vehicle body area and is used to connect all sensor units in the vehicle body area.

3. The ADAS system based on passive optical network as claimed in claim 1, characterized in that: The types of sensor units include cameras and lidars.

4. The ADAS system based on passive optical network as claimed in claim 1, characterized in that: The OLT MAC chip is also used to encapsulate and decapsulate data frames for uplink and downlink data; The ONU MAC chip is also used to encapsulate and decapsulate data frames for uplink and downlink data.

5. The ADAS system based on passive optical network as claimed in claim 1, characterized in that: The sensor embeds a timestamp in the sensing data and feeds it back to the central processing unit; The central processing unit performs data fusion based on the time stamps of each sensor data.

6. The ADAS system based on passive optical network as claimed in claim 1, characterized in that: The central processor includes a central processing module and a first FPGA connected to each other. The first FPGA is connected to the OLT MAC chip. The central processing module is used to receive the first clock signal and output control information and time information in the second clock signal. The FPGA is used to perform protocol conversion and encapsulation and decapsulation on uplink and downlink data.

7. The ADAS system based on passive optical network as claimed in claim 1, characterized in that: The OLT MAC chip is further configured to receive a PPS pulse in the first clock signal, and send the PPS pulse as a PPS pulse in the second clock signal to the sensor unit.

8. The ADAS system based on passive optical network as claimed in claim 1, characterized in that: The sensor includes a sensing module and a second FPGA connected to each other, the second FPGA is connected to the ONU MAC chip, the sensing module is used to receive control information, and collect and feed back sensing data according to the control information, the ONU MAC chip is used to extract the PPS signal in the second clock signal, the second FPGA is used to extract the time information in the second clock signal, and synchronize the sensor itself according to the time information in the second clock signal and the PPS signal.

9. The ADAS system based on passive optical network as claimed in claim 1, characterized in that: The central processing unit also includes a first optical transceiver connected to the OLT MAC chip, and the first optical transceiver is used to receive and receive optical signals; The sensing unit also includes a second optical transceiver connected to the ONU MAC chip, and the second optical transceiver is used for transmitting and receiving optical signals.

10. A multi-sensor signal synchronization method for an ADAS system based on a passive optical network, characterized in that: An ADAS system based on a passive optical network according to any one of claims 1 to 8; the multi-sensor signal synchronization method comprises: The central processor receives a first clock signal sent by an external clock source, and after synchronizing itself, sends a second clock signal to the sensor through a passive optical network downlink, and the sensor synchronizes itself according to the second clock signal; The central processor sends control information to the sensor through the passive optical network downlink. After receiving the control information, the sensor collects sensing data and sends the sensing data to the central processor through the passive optical network uplink.

Images