CN105551284A - Open-type automatic driving system - Google Patents
Open-type automatic driving system Download PDFInfo
- Publication number
- CN105551284A CN105551284A CN201610064921.3A CN201610064921A CN105551284A CN 105551284 A CN105551284 A CN 105551284A CN 201610064921 A CN201610064921 A CN 201610064921A CN 105551284 A CN105551284 A CN 105551284A
- Authority
- CN
- China
- Prior art keywords
- subsystem
- layer
- data
- radar
- driving system
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
Classifications
-
- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/09—Arrangements for giving variable traffic instructions
- G08G1/0962—Arrangements for giving variable traffic instructions having an indicator mounted inside the vehicle, e.g. giving voice messages
- G08G1/0967—Systems involving transmission of highway information, e.g. weather, speed limits
- G08G1/096708—Systems involving transmission of highway information, e.g. weather, speed limits where the received information might be used to generate an automatic action on the vehicle control
- G08G1/096725—Systems involving transmission of highway information, e.g. weather, speed limits where the received information might be used to generate an automatic action on the vehicle control where the received information generates an automatic action on the vehicle control
Landscapes
- Life Sciences & Earth Sciences (AREA)
- Atmospheric Sciences (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Traffic Control Systems (AREA)
Abstract
The present invention provides an open-type automatic driving system. The architecture of the system provided by the invention comprises seven layers from top to bottom: a presentation layer, an application layer, a business layer, a data layer, a communication layer and a perception layer. The open-type automatic driving system is able to obtain more clear solution information which is easier to put into effect in the construction of an automatic driving system.
Description
Technical field
The present invention relates to automatic Pilot technical field, particularly the open automated driving system of one.
Background technology
Daily life is closely bound up with " clothing, food, lodging and transportion--basic necessities of life ", especially " OK " wherein, the development trend of the population high concentration brought along with Development of Urbanization, the present situation of having a large population and a few land and Traffic conflicts upgrading, how society to provide safer to intelligent transportation system, the service of efficient and hommization, proposes more and more higher demand.Vehicular automatic driving wherein, as key components of intelligent transportation system, its original intention is exactly safety, efficient and people-oriented, moves towards practical gradually in recent years by experiment.
But automatic Pilot develop like a raging fire while, relative to the development of indivedual automatic Pilot subsystem such as navigation, image, the research of automated driving system general frame aspect, application and integrated but slightly inadequate.
Prior art Problems existing and shortcoming: the breakthrough emphasizing individual subsystem or technological layer, and the research of system integration aspect is relatively less; Automatic Pilot relates to the many factors such as navigation, communication, map, image, radar simultaneously, due to the difference of the aspects such as adopted sensor, data processing technique, automated driving system and general frame thereof also can vary, if systemic-function is too demanded perfection, easily cause system too huge, be difficult to carry out; And when adopting Partial mature technology to build the system with part Function for Automatic Pilot, owing to lacking the consideration of general frame aspect, also easily cause system frequently to reconstruct and the problem such as scaling difficulty.
Summary of the invention
In order to overcome the deficiencies in the prior art, the invention provides a kind of open automated driving system, this system is divided into seven levels by top-down for the architecture of automated driving system: be respectively presentation layer, application layer, operation layer, data Layer, communication layers and sensing layer, can obtain solution information that is clearer and more definite in automated driving system construction and enforcement of being more convenient for.
The technical solution adopted in the present invention is:
A kind of open automated driving system, this system is divided into seven levels by top-down for the architecture of automated driving system: be respectively presentation layer, application layer, operation layer, data Layer, communication layers and sensing layer; Wherein,
Presentation layer, direct user oriented, sets and corresponding information output for information input, the pattern of carrying out automated driving system according to the actual requirements;
Application layer, comprise in automatic Pilot subsystem, high precision cartography subsystem, wagon flow Optimized Operation subsystem and data mining subsystem one or more, for the user's request received by presentation layer, provide the application of the aspects such as automatic Pilot, high precision cartography, wagon flow Optimized Operation and data mining;
Operation layer, comprise in vehicle location subsystem, navigation subsystem, radar and image real time transfer subsystem, Driving Decision-making and vehicle control subsystems and high precision map rejuvenation subsystem one or more, for supporting the realization of industry application level function and providing related algorithm and data processing business;
Data Layer, for the storage of automated driving system related data, renewal and inquiry, related data comprises locator data, safe driving map datum, radar data, view data and driving daily record data;
Communication layers, disparate modules for automated driving system provides communication interface realization real-time Communication for Power between layers, being integrated with various wireless communication module simultaneously, for realizing system level communications between different user, comprising satellite communication, internet communication and near field car networking network;
Sensing layer, for collection vehicle periphery real time environment information, and provides corresponding data message by communication layers to data Layer, this layer subsystem comprise in navigation elements, active probe unit and passive detection unit one or more.
As preferably, described presentation layer subsystem comprises onboard instruments, hand-held mobile terminal, vehicle intelligent terminal and wearable device.
As preferably, in described application layer, automatic Pilot subsystem is used for realizing automatic cruising, automatically with car, automatic parking and standby car automatically; High precision cartography subsystem, for realizing the making of the making of position feature map, the making of visual signature map and radar signature map; Described wagon flow Optimized Operation subsystem, for realizing Congestion prediction, wagon flow joint optimal operation; Described data mining subsystem, for realizing mankind's driving behavior study, optimizing driving model and consumer's risk assessment.
As preferably, in described operation layer, vehicle location subsystem comprises inertial navigation location, satnav, flight path location, vision location, radar fix and faces car colocated; Automobile navigation subsystem is used for realizing a roading and the inquiry of driving environment priori; Radar and image processing subsystem, for realize floor line detection, Traffic Sign Recognition, detection of obstacles, pedestrian and vehicle detection and tracking, blind spot detect, track weigh detect, adjacent car action learning; Described Driving Decision-making and vehicle control subsystems, for realizing, data fusion, secondary path planning, path matching and wagon control, driver driving action learning and adjacent car are collaborative to be driven; Described map rejuvenation subsystem, upgrades for realizing track characteristic map rejuvenation, visual signature map rejuvenation, radar map renewal, lane information and road signs information.
As preferably, in described sensing layer, navigation subsystem comprises GPS, the Big Dipper, inertial navigation; Active probe subsystem adopts laser radar, millimetre-wave radar, microwave radar or ultrasonic radar.
Compared with prior art, the present invention has the following advantages:
1, structurized overall system framework specifies construction scope and the implementing direction of automated driving system, increases according to the actual requirements or reduces the subsystem in each layer, being conducive to the agile development of automated driving system;
2, by different level, modular system architecture contributes to accelerating system Construction and improving its stability;
3, system implementation plan information can be obtained, be conducive to the step-by-step plan of system Construction and implement step by step;
Accompanying drawing explanation
Fig. 1 is the open automated driving system architectural framework schematic diagram that the embodiment of the present invention provides;
Fig. 2 is that the one that the embodiment of the present invention provides simplifies embodiment schematic diagram;
Embodiment
In order to enable above-mentioned purpose of the present invention, feature and advantage become apparent more, are described in detail the specific embodiment of the present invention below in conjunction with accompanying drawing.
See Fig. 1, this figure is the open automated driving system configuration diagram that the embodiment of the present invention provides.The open automated driving system of the one that this example provides, this system is divided into seven levels by top-down for the architecture of automated driving system: be respectively presentation layer, application layer, operation layer, data Layer, communication layers and sensing layer; Wherein, presentation layer, direct user oriented, comprise in onboard instruments, hand-held mobile terminal, vehicle intelligent terminal and wearable device one or more, export for carrying out the information input of automated driving system, pattern setting and corresponding information according to the actual requirements.
Application layer, comprise in automatic Pilot subsystem, high precision cartography subsystem, wagon flow Optimized Operation subsystem and data mining subsystem one or more, wherein automatic Pilot subsystem is used for realizing automatic cruising, automatically with car, automatic parking and standby car automatically; High precision cartography subsystem, for realizing the making of the making of position feature map, the making of visual signature map and radar signature map; Described wagon flow Optimized Operation subsystem, for realizing Congestion prediction, wagon flow joint optimal operation; Described data mining subsystem, for realizing mankind's driving behavior study, optimizing driving model and consumer's risk assessment;
Operation layer, comprise in vehicle location subsystem, navigation subsystem, radar and image real time transfer subsystem, Driving Decision-making and vehicle control subsystems and high precision map rejuvenation subsystem one or more, for supporting the realization of industry application level function and providing related algorithm and data processing business; Wherein vehicle location subsystem comprises inertial navigation location, satnav, flight path location, vision location, radar fix and faces car colocated; Automobile navigation subsystem is used for realizing a roading and the inquiry of driving environment priori; Radar and image processing subsystem, for realize floor line detection, Traffic Sign Recognition, detection of obstacles, pedestrian and vehicle detection and tracking, blind spot detect, track weigh detect, adjacent car action learning; Described Driving Decision-making and vehicle control subsystems, for realizing, data fusion, secondary path planning, path matching and wagon control, driver driving action learning and adjacent car are collaborative to be driven; Described map rejuvenation subsystem, upgrades for realizing track characteristic map rejuvenation, visual signature map rejuvenation, radar map renewal, lane information and road signs information.
Data Layer, for the storage of automated driving system related data, renewal and inquiry, related data comprises locator data, safe driving map datum, radar data, view data and driving daily record data;
Communication layers, disparate modules for automated driving system provides communication interface realization real-time Communication for Power between layers, being integrated with various wireless communication module simultaneously, for realizing system level communications between different user, comprising satellite communication, internet communication and near field car networking network;
Sensing layer, for collection vehicle periphery real time environment information, and provides corresponding data message by communication layers to data Layer, this layer subsystem comprise in navigation elements, active probe unit and passive detection unit one or more.
See Fig. 2, the one quick implementation of this figure for implementing based on general frame of the present invention.
In this programme, comprise perception unit, communication unit, decision package, control module and display unit, sensing layer, communication layers, operation layer, application layer and presentation layer respectively in corresponding architecture.Because quick implementation structure is simple, because omitted herein the data Layer in architecture.
One, perception unit
Realize the perception to Vehicular automatic driving environment, comprise digital map navigation, Current GPS locating information, camera, laser radar etc., to obtain a relevant path of automatic Pilot (overall situation is with reference to guidance path), the view data of vehicle pose data, roadway environments periphery and barrier data etc., so that carry out automatic Pilot decision-making accordingly.
Two, decision package
Carry out perception data process and realize automatic Pilot decision-making.By based on the lane detection of image, Traffic Sign Recognition, pedestrian and vehicle detection and the detection of obstacles based on radar, AD*/MPC/ antenna scheduling algorithm is adopted to carry out secondary path (i.e. local path, wherein, if the primary system plan path secondary path planning obtains comparatively difficulty, the driving locus data of collection in advance can be adopted as an alternative for the purpose of simple) planning, to generate the quadratic programming path adapting to vehicle-surroundings dynamic environment.
Three, control module
Adopt the control algolithms such as PID/MPC, by regulation speed and vehicle front wheel slip angle, the carrying out to vehicle location and course angle controls, to realize the tracking to quadratic programming path.With vehicle location and course angle be quantity of state, the speed of a motor vehicle and front wheel slip angle for controlled quentity controlled variable, under adopting PID to carry out middle low-speed situations to vehicle, automatic Pilot controls; Or adopt Model Predictive Control (MPC) algorithm, with 40 kilometers for middling speed, adopt during middle low speed when vehicle kinematics model, high speed and adopt vehicle dynamic model, then the constraint condition in conjunction with the aspect such as forecast model, the speed of a motor vehicle, front wheel slip angle and rate of change thereof that objective function is relevant with safe driving carries out optimization to MPC controller, through circulation steps such as model prediction, rolling optimization and feedback corrections, realizing route is followed the tracks of and corresponding wagon control function.
Four, display unit
For showing automatic Pilot environmental information, comprise the testing results of aspect such as lane line, sign board, pedestrian and vehicle and the decision-making of the aspect such as path planning, path trace and control information.
Five, communication unit
Adopt the communication mode of system bus CAN gigabit Ethernet, realize efficient, the concurrent communication between automated driving system disparate modules.
The part do not set forth in instructions is prior art or common practise.The present embodiment only for illustration of this invention, and is not used in and limits the scope of the invention, and the amendment such as the equivalent replacement that those skilled in the art make for the present invention is all thought to fall in this invention claims institute protection domain.
Claims (5)
1. an open automated driving system, is characterized in that: this system is divided into seven levels by top-down for the architecture of automated driving system: be respectively presentation layer, application layer, operation layer, data Layer, communication layers and sensing layer; Wherein,
Presentation layer, direct user oriented, sets and corresponding information output for information input, the pattern of carrying out automated driving system according to the actual requirements;
Application layer, comprise in automatic Pilot subsystem, high precision cartography subsystem, wagon flow Optimized Operation subsystem and data mining subsystem one or more, for the user's request received by presentation layer, provide the application of automatic Pilot, high precision cartography, wagon flow Optimized Operation and data mining aspect;
Operation layer, comprise in vehicle location subsystem, navigation subsystem, radar and image real time transfer subsystem, Driving Decision-making and vehicle control subsystems and high precision map rejuvenation subsystem one or more, for supporting the realization of industry application level function and providing related algorithm and data processing business;
Data Layer, for the storage of automated driving system related data, renewal and inquiry, related data comprises locator data, safe driving map datum, radar data, view data and driving daily record data;
Communication layers, disparate modules for automated driving system provides communication interface realization real-time Communication for Power between layers, being integrated with various wireless communication module simultaneously, for realizing system level communications between different user, comprising satellite communication, internet communication and near field car networking network;
Sensing layer, for collection vehicle periphery real time environment information, and provides corresponding data message by communication layers to data Layer, this layer subsystem comprise in navigation elements, active probe unit and passive detection unit one or more.
2. a kind of open automated driving system according to claim 1, is characterized in that: described presentation layer subsystem comprises onboard instruments, hand-held mobile terminal, vehicle intelligent terminal and wearable device.
3. a kind of open automated driving system according to claim 1, is characterized in that: in described application layer, and automatic Pilot subsystem is used for realizing automatic cruising, automatically with car, automatic parking and standby car automatically; High precision cartography subsystem, for realizing the making of the making of position feature map, the making of visual signature map and radar signature map; Described wagon flow Optimized Operation subsystem, for realizing Congestion prediction, wagon flow joint optimal operation; Described data mining subsystem, for realizing mankind's driving behavior study, optimizing driving model and consumer's risk assessment.
4. a kind of open automated driving system according to claim 1, is characterized in that: in described operation layer, and vehicle location subsystem comprises inertial navigation location, satnav, flight path location, vision location, radar fix and faces car colocated; Automobile navigation subsystem is used for realizing a roading and the inquiry of driving environment priori; Radar and image processing subsystem, for realize floor line detection, Traffic Sign Recognition, detection of obstacles, pedestrian and vehicle detection and tracking, blind spot detect, track weigh detect, adjacent car action learning; Described Driving Decision-making and vehicle control subsystems, for realizing, data fusion, secondary path planning, path matching and wagon control, driver driving action learning and adjacent car are collaborative to be driven; Described map rejuvenation subsystem, upgrades for realizing track characteristic map rejuvenation, visual signature map rejuvenation, radar map renewal, lane information and road signs information.
5. a kind of open automated driving system according to claim 1, it is characterized in that: in described sensing layer, navigation subsystem comprises GPS, the Big Dipper, inertial navigation; Active probe subsystem adopts laser radar, millimetre-wave radar, microwave radar or ultrasonic radar.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201610064921.3A CN105551284A (en) | 2016-01-29 | 2016-01-29 | Open-type automatic driving system |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201610064921.3A CN105551284A (en) | 2016-01-29 | 2016-01-29 | Open-type automatic driving system |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN105551284A true CN105551284A (en) | 2016-05-04 |
Family
ID=55830451
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201610064921.3A Pending CN105551284A (en) | 2016-01-29 | 2016-01-29 | Open-type automatic driving system |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN105551284A (en) |
Cited By (24)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106340205A (en) * | 2016-09-30 | 2017-01-18 | 广东中星微电子有限公司 | Traffic monitoring method and traffic monitoring apparatus |
| CN106485797A (en) * | 2016-09-30 | 2017-03-08 | 广东中星微电子有限公司 | Parking timing method and time parking devices |
| CN106681328A (en) * | 2017-01-13 | 2017-05-17 | 深圳市元征科技股份有限公司 | Automatic driving method based on intelligent wearable device and intelligent wearable device |
| CN107478238A (en) * | 2017-07-31 | 2017-12-15 | 中北智杰科技（北京）有限公司 | A kind of new-energy automobile Unmanned Systems and control method |
| CN107490382A (en) * | 2017-07-31 | 2017-12-19 | 中北智杰科技（北京）有限公司 | A kind of pilotless automobile path planning system and control method |
| CN107580322A (en) * | 2017-08-28 | 2018-01-12 | 驭势科技（北京）有限公司 | Upgrade method, device and the automatic driving vehicle of automatic driving vehicle software systems |
| CN107664502A (en) * | 2016-07-28 | 2018-02-06 | 奥迪股份公司 | The method, apparatus and system of dynamic programming path |
| CN107797534A (en) * | 2017-09-30 | 2018-03-13 | 安徽江淮汽车集团股份有限公司 | A kind of pure electronic automated driving system |
| CN108536148A (en) * | 2018-04-17 | 2018-09-14 | 陈明 | A kind of new Vehicular automatic driving method |
| CN108773373A (en) * | 2016-09-14 | 2018-11-09 | 北京百度网讯科技有限公司 | Method and apparatus for operating automatic driving vehicle |
| CN109146333A (en) * | 2018-09-29 | 2019-01-04 | 百度在线网络技术（北京）有限公司 | Navigation algorithm appraisal procedure and device |
| CN109271147A (en) * | 2018-09-13 | 2019-01-25 | 北京车联天下信息技术有限公司 | A kind of intelligence cockpit system layer design method and intelligent cockpit system |
| CN109521763A (en) * | 2017-09-18 | 2019-03-26 | 百度（美国）有限责任公司 | The path optimization based on constraint smoothing spline for automatic driving vehicle |
| CN109556623A (en) * | 2018-12-04 | 2019-04-02 | 中国兵器装备集团自动化研究所 | Fusion antenna algorithm and the iterative path planning algorithm for cutting line-plot method |
| CN109920246A (en) * | 2019-02-22 | 2019-06-21 | 重庆邮电大学 | It is a kind of that local paths planning method is cooperateed with binocular vision based on V2X communication |
| CN110083149A (en) * | 2018-01-26 | 2019-08-02 | 百度（美国）有限责任公司 | For infeed mechanism after the path of automatic driving vehicle and speed-optimization |
| CN110375751A (en) * | 2019-07-29 | 2019-10-25 | 苏州索亚机器人技术有限公司 | A kind of automatic Pilot real-time navigation system framework |
| CN110716552A (en) * | 2019-11-11 | 2020-01-21 | 朱云 | Novel driving system for automobile, train, subway and airplane |
| CN110869981A (en) * | 2016-12-30 | 2020-03-06 | 迪普迈普有限公司 | Vector data encoding of high definition map data for autonomous vehicles |
| CN111547109A (en) * | 2020-04-23 | 2020-08-18 | 上海桂垚信息科技有限公司 | Computer server for running automatic driving operation system |
| CN111966108A (en) * | 2020-09-02 | 2020-11-20 | 成都信息工程大学 | Extreme weather unmanned control system based on navigation system |
| CN112097781A (en) * | 2019-06-17 | 2020-12-18 | 郑州宇通客车股份有限公司 | Path planning method and device based on multi-stage tentacles |
| CN112530156A (en) * | 2019-09-18 | 2021-03-19 | 中移智行网络科技有限公司 | Intelligent network automobile open road system based on edge calculation and construction method |
| CN112896169A (en) * | 2021-01-29 | 2021-06-04 | 中汽创智科技有限公司 | Intelligent driving multi-mode control system and method |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2012051441A (en) * | 2010-08-31 | 2012-03-15 | Toyota Motor Corp | Automatic operation vehicle control device |
| CN102497393A (en) * | 2011-11-28 | 2012-06-13 | 浙江网新技术有限公司 | High-speed train intelligent system and communication method thereof |
| CN104267721A (en) * | 2014-08-29 | 2015-01-07 | 陈业军 | Unmanned driving system of intelligent automobile |
| CN104269053A (en) * | 2014-08-29 | 2015-01-07 | 陈业军 | Intelligent traffic system and method and intelligent automobile |
| WO2015166721A1 (en) * | 2014-05-02 | 2015-11-05 | エイディシーテクノロジー株式会社 | Vehicle controller |
-
2016
- 2016-01-29 CN CN201610064921.3A patent/CN105551284A/en active Pending
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2012051441A (en) * | 2010-08-31 | 2012-03-15 | Toyota Motor Corp | Automatic operation vehicle control device |
| CN102497393A (en) * | 2011-11-28 | 2012-06-13 | 浙江网新技术有限公司 | High-speed train intelligent system and communication method thereof |
| WO2015166721A1 (en) * | 2014-05-02 | 2015-11-05 | エイディシーテクノロジー株式会社 | Vehicle controller |
| CN104267721A (en) * | 2014-08-29 | 2015-01-07 | 陈业军 | Unmanned driving system of intelligent automobile |
| CN104269053A (en) * | 2014-08-29 | 2015-01-07 | 陈业军 | Intelligent traffic system and method and intelligent automobile |
Non-Patent Citations (1)
| Title |
|---|
| 辛煜: "无人驾驶车辆运动障碍物检测、预测和避撞方法研究", 《中国博士学位论文全文数据库工程科技Ⅱ辑》 * |
Cited By (32)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107664502A (en) * | 2016-07-28 | 2018-02-06 | 奥迪股份公司 | The method, apparatus and system of dynamic programming path |
| CN108773373B (en) * | 2016-09-14 | 2020-04-24 | 北京百度网讯科技有限公司 | Method and device for operating an autonomous vehicle |
| CN108773373A (en) * | 2016-09-14 | 2018-11-09 | 北京百度网讯科技有限公司 | Method and apparatus for operating automatic driving vehicle |
| CN106485797A (en) * | 2016-09-30 | 2017-03-08 | 广东中星微电子有限公司 | Parking timing method and time parking devices |
| CN106340205A (en) * | 2016-09-30 | 2017-01-18 | 广东中星微电子有限公司 | Traffic monitoring method and traffic monitoring apparatus |
| CN110869981A (en) * | 2016-12-30 | 2020-03-06 | 迪普迈普有限公司 | Vector data encoding of high definition map data for autonomous vehicles |
| CN110869981B (en) * | 2016-12-30 | 2023-12-01 | 辉达公司 | Vector data encoding of high definition map data for autonomous vehicles |
| US11754716B2 (en) | 2016-12-30 | 2023-09-12 | Nvidia Corporation | Encoding LiDAR scanned data for generating high definition maps for autonomous vehicles |
| CN106681328A (en) * | 2017-01-13 | 2017-05-17 | 深圳市元征科技股份有限公司 | Automatic driving method based on intelligent wearable device and intelligent wearable device |
| CN107490382A (en) * | 2017-07-31 | 2017-12-19 | 中北智杰科技（北京）有限公司 | A kind of pilotless automobile path planning system and control method |
| CN107478238A (en) * | 2017-07-31 | 2017-12-15 | 中北智杰科技（北京）有限公司 | A kind of new-energy automobile Unmanned Systems and control method |
| CN107580322A (en) * | 2017-08-28 | 2018-01-12 | 驭势科技（北京）有限公司 | Upgrade method, device and the automatic driving vehicle of automatic driving vehicle software systems |
| CN109521763A (en) * | 2017-09-18 | 2019-03-26 | 百度（美国）有限责任公司 | The path optimization based on constraint smoothing spline for automatic driving vehicle |
| CN107797534A (en) * | 2017-09-30 | 2018-03-13 | 安徽江淮汽车集团股份有限公司 | A kind of pure electronic automated driving system |
| CN110083149B (en) * | 2018-01-26 | 2022-05-13 | 百度（美国）有限责任公司 | Path and speed optimized feedback mechanism for autonomous vehicles |
| CN110083149A (en) * | 2018-01-26 | 2019-08-02 | 百度（美国）有限责任公司 | For infeed mechanism after the path of automatic driving vehicle and speed-optimization |
| CN108536148A (en) * | 2018-04-17 | 2018-09-14 | 陈明 | A kind of new Vehicular automatic driving method |
| CN109271147A (en) * | 2018-09-13 | 2019-01-25 | 北京车联天下信息技术有限公司 | A kind of intelligence cockpit system layer design method and intelligent cockpit system |
| CN109271147B (en) * | 2018-09-13 | 2021-09-28 | 无锡车联天下信息技术有限公司 | Intelligent cabin system layered design method and intelligent cabin system |
| CN109146333A (en) * | 2018-09-29 | 2019-01-04 | 百度在线网络技术（北京）有限公司 | Navigation algorithm appraisal procedure and device |
| CN109556623A (en) * | 2018-12-04 | 2019-04-02 | 中国兵器装备集团自动化研究所 | Fusion antenna algorithm and the iterative path planning algorithm for cutting line-plot method |
| CN109556623B (en) * | 2018-12-04 | 2022-07-29 | 中国兵器装备集团自动化研究所 | Iterative path planning algorithm fusing whisker algorithm and tangent graph method |
| CN109920246B (en) * | 2019-02-22 | 2022-02-11 | 重庆邮电大学 | Collaborative local path planning method based on V2X communication and binocular vision |
| CN109920246A (en) * | 2019-02-22 | 2019-06-21 | 重庆邮电大学 | It is a kind of that local paths planning method is cooperateed with binocular vision based on V2X communication |
| CN112097781B (en) * | 2019-06-17 | 2023-05-09 | 宇通客车股份有限公司 | Path planning method and device based on multistage tentacles |
| CN112097781A (en) * | 2019-06-17 | 2020-12-18 | 郑州宇通客车股份有限公司 | Path planning method and device based on multi-stage tentacles |
| CN110375751A (en) * | 2019-07-29 | 2019-10-25 | 苏州索亚机器人技术有限公司 | A kind of automatic Pilot real-time navigation system framework |
| CN112530156A (en) * | 2019-09-18 | 2021-03-19 | 中移智行网络科技有限公司 | Intelligent network automobile open road system based on edge calculation and construction method |
| CN110716552A (en) * | 2019-11-11 | 2020-01-21 | 朱云 | Novel driving system for automobile, train, subway and airplane |
| CN111547109A (en) * | 2020-04-23 | 2020-08-18 | 上海桂垚信息科技有限公司 | Computer server for running automatic driving operation system |
| CN111966108A (en) * | 2020-09-02 | 2020-11-20 | 成都信息工程大学 | Extreme weather unmanned control system based on navigation system |
| CN112896169A (en) * | 2021-01-29 | 2021-06-04 | 中汽创智科技有限公司 | Intelligent driving multi-mode control system and method |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN105551284A (en) | Open-type automatic driving system | |
| US11887032B2 (en) | Fleet utilization efficiency for on-demand transportation services | |
| US10884902B2 (en) | Software version verification for autonomous vehicles | |
| US10262471B2 (en) | Autonomous vehicle degradation level monitoring | |
| US10762447B2 (en) | Vehicle selection for on-demand transportation services | |
| US10789835B2 (en) | Fractional risk performance evaluation for autonomous vehicles | |
| US10501091B2 (en) | Software version and mode switching for autonomous vehicles | |
| US10697789B2 (en) | Individualized risk routing for human drivers | |
| US11080806B2 (en) | Non-trip risk matching and routing for on-demand transportation services | |
| US11288612B2 (en) | Generalized risk routing for human drivers | |
| US11282016B2 (en) | Individualized risk vehicle matching for an on-demand transportation service | |
| US20180342033A1 (en) | Trip classification system for on-demand transportation services | |
| CN110673602B (en) | Reinforced learning model, vehicle automatic driving decision method and vehicle-mounted equipment | |
| EP3631366B1 (en) | Path segment risk regression system for on-demand transportation services | |
| US20180341881A1 (en) | Post-trip optimization for autonomous vehicles | |
| US20180341261A1 (en) | Path segment risk regression system for on-demand transportation services | |
| CN105976606A (en) | Intelligent urban traffic management platform | |
| US11307585B2 (en) | Introspective competence modeling for AV decision making | |
| JP6716792B2 (en) | Generation of solution data for autonomous vehicles to deal with problem situations | |
| CN110568847B (en) | Intelligent control system and method for vehicle, vehicle-mounted equipment and storage medium | |
| CN112562409A (en) | Autonomous parking system and method based on multi-access edge calculation | |
| CN107230372A (en) | A kind of automatic Pilot method, device, entire car controller and automobile | |
| CN116723970A (en) | System, method and computer program product for automated driving topology planning using limit representations | |
| WO2022140251A1 (en) | Systems and methods for error sourcing in autonomous vehicle simulation | |
| CN107395757B (en) | Parallel vehicle networking system based on ACP method and social physical information system |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20160504 |
|
| RJ01 | Rejection of invention patent application after publication |