行车服务推送平台及其关键算法的设计与测试*

doi:10.19562/j.chinasae.qcgc.2020.06.001

汽车工程 ›› 2020, Vol. 42 ›› Issue (6): 709-717.doi: 10.19562/j.chinasae.qcgc.2020.06.001

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行车服务推送平台及其关键算法的设计与测试^*

梁军, 丛森森, 王军, 蔡英凤, 江浩斌, 陈龙

江苏大学汽车工程研究院,镇江 212013

收稿日期:2019-05-16 出版日期:2020-06-25 发布日期:2020-07-16
通讯作者: 梁军,教授,工学博士,E-mail:liangjun@ujs.edu.cn
基金资助:
国家重点研发计划(2018YFB1600503)、国家自然科学基金(U1664258,51875255,61601203)、江苏省六大人才高峰项目(2015-DZXX-048)、江苏省高等学校自然科学研究重大项目(18KJA580002)和高邮市科技计划项目(GY201801)资助。

Design and Test of Driving Push Service Platform and Its Key Algorithm

Liang Jun, Cong Sensen, Wang Jun, Cai Yingfeng, Jiang Haobin, Chen Long

Automobile Engineering Research Institute, Jiangsu University, Zhenjiang 212013

Received:2019-05-16 Online:2020-06-25 Published:2020-07-16

摘要/Abstract

摘要： 针对行车主动服务“主动感知自动生成主动推送”过程中忽视推送与行车用户的相互影响,设计了基于行车用户操作行为的行车主动服务推送平台(DPSP),包括存储层、应用层和评价层。存储层用来分类和存储用户行为的历史和实时数据;在应用层基于用户操作行为设计了B-Num.BT算法,提高了DPSP的服务推送用户接受度;而评价层则利用操作数据对推送服务进行评价和监控。通过驾驶员在环(DIL)试验验证典型推送场景的及时性、安全性和准确性,结果表明,DPSP满足推送系统性能要求,所设计B-Num.BT算法的各项性能皆优于对比算法Hybrid.BT和CAR.BT;另外发现,及时性同时具有对行车用户分类的功能。本研究对完善DASS、加强行车安全,乃至无人驾驶技术的推广具有重要意义。

关键词: 行车主动服务, 操作行为预测, 行车服务推送平台, 典型服务场景

Abstract: In view of the neglect of the interaction between push service and users during the process of “active perception-automatic generation-active push” in driving active service system (DASS), a driving push service platform (DPSP), which covers storage layer, application layer and evaluation layer, is designed based on the operation behavior of driving users. The storage layer is used to classify and store the pervious and current data of user behavior. In application layer, B-Num/BT algorithm is designed based on user's operation behavior, for improving the user acceptance of DPSP, while the evaluation layer utilizes operation data to evaluate and monitor the performance of push service. A driver-in-the-loop test is conducted to verify the timeliness, safety and accuracy of typical push service scenarios. The results show that DPSP meets the performance requirements of push system. In addition, it is found that the timeliness also has the function of classifying driving users. The research has great significance for the perfection of DASS system, the strengthening of driving safety and even the popularization of autonomous driving technology

Key words: driving active service, operation behavior prediction, driving push service platform, typical service scenarios

梁军, 丛森森, 王军, 蔡英凤, 江浩斌, 陈龙. 行车服务推送平台及其关键算法的设计与测试^*[J]. 汽车工程, 2020, 42(6): 709-717.

Liang Jun, Cong Sensen, Wang Jun, Cai Yingfeng, Jiang Haobin, Chen Long. Design and Test of Driving Push Service Platform and Its Key Algorithm[J]. Automotive Engineering, 2020, 42(6): 709-717.

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行车服务推送平台及其关键算法的设计与测试^*

Design and Test of Driving Push Service Platform and Its Key Algorithm

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