CA3065617C - Method for predicting car-following behavior under apollo platform - Google Patents
Method for predicting car-following behavior under apollo platform Download PDFInfo
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- CA3065617C CA3065617C CA3065617A CA3065617A CA3065617C CA 3065617 C CA3065617 C CA 3065617C CA 3065617 A CA3065617 A CA 3065617A CA 3065617 A CA3065617 A CA 3065617A CA 3065617 C CA3065617 C CA 3065617C
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N5/00—Computing arrangements using knowledge-based models
- G06N5/04—Inference or reasoning models
- G06N5/048—Fuzzy inferencing
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
- Y02T10/00—Road transport of goods or passengers
- Y02T10/10—Internal combustion engine [ICE] based vehicles
- Y02T10/40—Engine management systems
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Applications Claiming Priority (2)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910924643.8 | 2019-09-27 | ||
| CN201910924643.8A CN110750877B (zh) | 2019-09-27 | 2019-09-27 | 一种Apollo平台下的车辆跟驰行为预测方法 |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CA3065617A1 CA3065617A1 (en) | 2021-03-27 |
| CA3065617C true CA3065617C (en) | 2022-07-19 |
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| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CA3065617A Active CA3065617C (en) | 2019-09-27 | 2019-12-19 | Method for predicting car-following behavior under apollo platform |
Country Status (2)
| Country | Link |
|---|---|
| CN (1) | CN110750877B (zh) |
| CA (1) | CA3065617C (zh) |
Families Citing this family (23)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111476491A (zh) * | 2020-04-10 | 2020-07-31 | 北京工业大学 | 一种城市交通场景中的车辆运动模拟分析方法 |
| CN111674394B (zh) * | 2020-06-09 | 2023-04-11 | 南京工业职业技术学院 | 一种能实现微观调控的自动驾驶跟驰保持方法 |
| CN111907523B (zh) * | 2020-06-30 | 2024-03-12 | 山东小雨汽车科技有限公司 | 一种基于模糊推理的车辆跟驰寻优控制方法 |
| CN111968372B (zh) * | 2020-08-25 | 2022-07-22 | 重庆大学 | 一种考虑主观因素的多车型混合交通跟驰行为仿真方法 |
| CN112193245B (zh) * | 2020-09-24 | 2021-09-03 | 同济大学 | 一种考虑驾驶员模糊感知的深度学习跟驰预测方法 |
| CN112580149B (zh) * | 2020-12-22 | 2023-05-26 | 浙江工业大学 | 基于生成对抗网络和驾驶时长的车辆跟驰模型生成方法 |
| CN113066282B (zh) * | 2021-02-26 | 2022-05-27 | 北京航空航天大学合肥创新研究院(北京航空航天大学合肥研究生院) | 一种面向混行环境下车辆跟驰耦合关系建模方法及系统 |
| CN112793572B (zh) * | 2021-03-19 | 2022-06-03 | 成都安智杰科技有限公司 | 一种自适应巡航控制方法、装置、电子设备和存储介质 |
| CN113112022A (zh) * | 2021-04-06 | 2021-07-13 | 清华大学 | 智能汽车队列人-车-路系统多智能体联合建模方法 |
| CN113325691B (zh) * | 2021-04-29 | 2022-07-12 | 西安交通大学 | 一种无人车双闭环纵向控制方法、系统及设备 |
| CN113779864B (zh) * | 2021-08-06 | 2024-04-26 | 同济大学 | 面向自动驾驶汽车的运行设计区域构建方法和装置 |
| CN113657676B (zh) * | 2021-08-19 | 2024-05-14 | 燕山大学 | 一种考虑多维度驾驶人特性的制动反应时间预测方法 |
| CN114023108B (zh) * | 2021-11-02 | 2023-06-09 | 河北工业大学 | 一种混合交通流变道模型及变道仿真方法 |
| CN113928314B (zh) * | 2021-11-17 | 2023-11-10 | 吉林大学 | 一种冰雪路面条件下考虑前后车的自动驾驶车辆跟驰控制方法 |
| CN114169444B (zh) * | 2021-12-09 | 2024-03-05 | 合肥工业大学 | 车辆跟驰工况下考虑风险势场分布的驾驶风格分类方法 |
| CN114516328B (zh) * | 2022-03-08 | 2024-02-27 | 武汉科技大学 | 一种智能网联环境下基于规则的车队跟驰模型方法 |
| CN115099128B (zh) * | 2022-05-30 | 2023-07-07 | 同济大学 | 一种异常驾驶行为识别与致因分析方法和系统 |
| CN114932552B (zh) * | 2022-05-31 | 2024-03-26 | 西安理工大学 | 协作机器人主动动作决策方法、系统、设备及存储介质 |
| CN115019508B (zh) * | 2022-06-13 | 2023-09-29 | 华南理工大学 | 基于机器学习的道路监控车流仿真方法、装置、设备及介质 |
| CN115195821B (zh) * | 2022-06-14 | 2023-09-26 | 同济大学 | 一种后车跟驰行为控制方法、装置及存储介质 |
| CN115171380B (zh) * | 2022-07-01 | 2023-05-12 | 广西师范大学 | 一种抑制网络攻击造成车联网拥塞的控制模型和方法 |
| CN115440036B (zh) * | 2022-08-26 | 2023-08-29 | 同济大学 | 一种车辆跟驰关系管理与角色实时配置方法 |
| CN117311366B (zh) * | 2023-11-21 | 2024-02-13 | 南京禄口国际机场空港科技有限公司 | 一种应用于机场草坪的割草机的路径控制方法、系统及存储介质 |
Family Cites Families (24)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN1719354A (zh) * | 2005-05-08 | 2006-01-11 | 上海交通大学 | 车辆跟驰运动的加速度控制方法 |
| CN1876461A (zh) * | 2006-07-06 | 2006-12-13 | 上海交通大学 | 车辆跟驰驾驶的速度差－间距控制方法 |
| CN101264762A (zh) * | 2008-03-21 | 2008-09-17 | 东南大学 | 车辆跟驰运动的速度控制方法 |
| CN101694742A (zh) * | 2009-06-16 | 2010-04-14 | 同济大学 | 重大公路交通基础设施运行安全控制方法 |
| CN102991498A (zh) * | 2011-12-19 | 2013-03-27 | 王晓原 | 基于多源信息融合的驾驶员跟驰行为模型 |
| CN102662320A (zh) * | 2012-03-05 | 2012-09-12 | 吴建平 | 一种基于模糊数学的车辆跟驰模拟方法 |
| US10510256B2 (en) * | 2014-10-20 | 2019-12-17 | Robert Brandriff | Vehicle collision avoidance system and method |
| CN105788238B (zh) * | 2016-01-07 | 2018-08-28 | 南京航空航天大学 | 基于量子门和自适应控制的类弹簧车辆跟驰模型建立方法 |
| CN105809106B (zh) * | 2016-02-23 | 2019-02-26 | 北京理工大学 | 基于机器视觉的车辆队形跟驰检测方法 |
| CN106407563B (zh) * | 2016-09-20 | 2020-03-27 | 北京工业大学 | 一种基于驾驶类型和前车加速度信息的跟驰模型生成方法 |
| CN106803226A (zh) * | 2017-01-23 | 2017-06-06 | 长安大学 | 考虑最优速度记忆及后视效应的车辆跟驰建模方法 |
| CN108573600B (zh) * | 2017-03-10 | 2022-02-08 | 重庆邮电大学 | 一种驾驶员行为诱导与局部交通流优化方法 |
| WO2018207199A1 (en) * | 2017-05-06 | 2018-11-15 | Ramana Soothram Venkata | Automatic vehicle & driver tracking system with intelligent traffic management |
| CN107103749B (zh) * | 2017-05-19 | 2020-03-10 | 长安大学 | 车联网环境下跟驰交通流特性建模方法 |
| CN107452201B (zh) * | 2017-07-24 | 2020-05-08 | 重庆大学 | 一种考虑前车换道驶离时后车的跟驰加速度确定方法及跟驰行为建模方法 |
| CN107507408B (zh) * | 2017-07-24 | 2020-07-24 | 重庆大学 | 一种考虑前车换道汇入过程的跟驰加速度及跟驰行为建模方法 |
| CN107507245A (zh) * | 2017-08-18 | 2017-12-22 | 南京阿尔特交通科技有限公司 | 一种车辆跟驰轨迹的动态采集方法及系统 |
| US10902336B2 (en) * | 2017-10-03 | 2021-01-26 | International Business Machines Corporation | Monitoring vehicular operation risk using sensing devices |
| CN107544254B (zh) * | 2017-10-12 | 2020-04-14 | 北京航空航天大学 | 一种期望安全裕度跟驰模型的自适应动态滑模控制方法 |
| CN108495330B (zh) * | 2018-03-09 | 2019-11-08 | 清华大学 | 一种车-车信息交互通信的碰撞预警可靠性测试方法 |
| CN108944943B (zh) * | 2018-07-11 | 2020-04-14 | 北京航空航天大学 | 一种基于风险动态平衡理论的弯道跟驰模型 |
| CN109213148B (zh) * | 2018-08-03 | 2021-05-28 | 东南大学 | 一种基于深度强化学习的车辆低速跟驰决策方法 |
| CN109858738A (zh) * | 2018-12-19 | 2019-06-07 | 青岛科技大学 | 一种车辆跟驰状态驾驶员情感动态特征提取及辨识方法 |
| CN109978260B (zh) * | 2019-03-26 | 2023-02-21 | 重庆邮电大学 | 混合交通流下网联车跟驰行为预测方法 |
-
2019
- 2019-09-27 CN CN201910924643.8A patent/CN110750877B/zh active Active
- 2019-12-19 CA CA3065617A patent/CA3065617C/en active Active
Also Published As
| Publication number | Publication date |
|---|---|
| CN110750877B (zh) | 2024-05-03 |
| CA3065617A1 (en) | 2021-03-27 |
| CN110750877A (zh) | 2020-02-04 |
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