智能汽车环境感知与规划决策一体化仿真测试平台

doi:10.16182/j.issn1004731x.joss.18-0102

系统仿真学报 ›› 2020, Vol. 32 ›› Issue (2): 236-246.doi: 10.16182/j.issn1004731x.joss.18-0102

• 物理效应/模拟器仿真技术 • 上一篇下一篇

智能汽车环境感知与规划决策一体化仿真测试平台

孙剑¹, 黄润涵^1*, 李霖², 刘启远¹, 李宇迪¹

1. 同济大学道路与交通工程教育部重点实验室,上海 201804;
2. 上海国际汽车城(集团)有限公司,上海 201804

收稿日期:2018-03-01 修回日期:2018-12-25 出版日期:2020-02-18 发布日期:2020-02-19
作者简介:孙剑(1979-),男,山东齐河,博士,教授,博导,研究方向为交通仿真、交通流理论、交通大数据、智能网联汽车测试与评估。
基金资助:
国家自然科学基金(51422812),上海市科委国际科技合作项目(16510711400)

Integrated Simulation Test Platform for Environment Perception and Planning Decision of Intelligent Vehicle

Sun Jian¹, Huang Runhan^1*, Li Lin², Liu Qiyuan¹, Li Yudi¹

1. Key Laboratory of Road and Traffic Engineering of Ministry of Education, Tongji University, Shanghai 201804, China;
2. Shanghai International Automobile City, Shanghai 201804, China

Received:2018-03-01 Revised:2018-12-25 Online:2020-02-18 Published:2020-02-19

摘要/Abstract

摘要： 为了解决智能汽车在虚拟仿真测试过程中存在的测试模块单一化、较难提供高密度高逼真交通流场景等问题,利用智能汽车仿真软件PreScan的环境感知仿真与规划决策开发工具箱MATLAB/Simulink,以及交通仿真软件Vissim快速生成高逼真环境车流的功能,搭建了智能汽车“软件在环”一体化测试平台。该平台可快速搭建智能汽车高逼真仿真场景,可快速有效地对智能汽车的环境感知与规划决策模块进行一体化仿真测试,还能综合评估智能汽车对交通流的影响。通过快速路汇入区仿真案例,验证了本仿真测试平台的有效性。

关键词: 智能汽车, 一体化仿真测试, PreScan, Vissim, 环境感知, 规划决策

Abstract: The simplicity of testing modules and the lack of high-fidelity and high-density traffic scenes are the primary issues in the intelligent vehicle' simulation test. To solve these problems, a "software in the loop" integration test platform is built. The environmental perception module is integrated on the basis of the PreScan, the planning decision-making module designed by MATLAB/Simulink and the virtual traffic flow environment from Vissim. Based on this platform, high-fidelity traffic flow scenes can be generated rapidly to support the test of environment perception and decision-making integratedly and effectively. Moreover, the intelligent vehicle's influence on the traffic flow can be evaluated comprehensively. A case study of an expressway on-ramp proves the feasibility of the simulation platform.

Key words: intelligent vehicle, integrated simulation test, PreScan, Vissim, environment perception, decision-making

中图分类号:

U491.2

孙剑, 黄润涵, 李霖, 刘启远, 李宇迪. 智能汽车环境感知与规划决策一体化仿真测试平台[J]. 系统仿真学报, 2020, 32(2): 236-246.

Sun Jian, Huang Runhan, Li Lin, Liu Qiyuan, Li Yudi. Integrated Simulation Test Platform for Environment Perception and Planning Decision of Intelligent Vehicle[J]. Journal of System Simulation, 2020, 32(2): 236-246.

参考文献

[1] 中华人民共和国国务院. 中国制造2025[R]. China Manufacturing 2025. 2015.
[2] Kalra N, Paddock S M.Driving to safety: How many miles of driving would it take to demonstrate autonomous vehicle reliability[J]. Transportation Research Part A (S0965-8564), 2016, 94: 182-193.
[3] 孙剑, 张娟. 城市快速路瓶颈交通流失效生存分析[J]. 同济大学学报(自然科学版), 2013, 41(4): 530-535.
Sun Jian, Zhang Juan.Survival analyses of traffic flow breakdown at urban expressway bottlenecks[J]. Journal of Tongji University(Natural Science), 2013, 41(4): 530-535.
[4] Ehlert P A M, Rothkrantz L J M. Microscopic traffic simulation with reactive driving agents[C]// ITSC 2001. 2001 IEEE Intelligent Transportation Systems. Proceedings (Cat. No. 01TH8585). IEEE, 2001: 860-865.
[5] Wymann B, Dimitrakakis C, Sumner A, et al. TORCS, the open racing car simulator, v1.3.5[J/OL].2013. https://sourceforge.net/projects/torcs/.
[6] Scott P, Hans A, Xinxin D, et al.Perception, Planning, Control, and Coordination for Autonomous Vehicles[J]. Machines, 2017, 5(1): 6.
[7] Johnson-Roberson M, Barto C, Mehta R, et al.Driving in the matrix: Can virtual worlds replace human-generated annotations for real world tasks?[J]. IEEE International Conference on Robotics and Automation (ICRA), 2017, 746-753.
[8] Dosovitskiy A, Ros G, Codevilla F, et al. CARLA: An Open Urban Driving Simulator[J/OL]. arXiv preprint, 2017. https://arxiv.org/abs/1711.03938.
[9] He H W, Lu Y M, Lou Y.Virtual reality based intelligent vehicle modeling in driving SIMULATION system[C]// International Conference on Computer-Aided Industrial Design and Conceptual Design. IEEE, 2006: 1-5.
[10] 胡生远. 车道保持硬件在环仿真系统设计[D]. 长沙: 湖南大学, 2013.
Hu Shengyuan.Design of Hardware-in-the-Loop Simulation System for Lane keeping System[D]. Changsha: Hunan University, 2013.
[11] 臧志刚, 陆锋, 李海峰, 等. 7种微观交通仿真系统的性能评价与比较研究[J]. 交通信息与安全, 2007, 25(1): 66-70.
Zang Zhigang, Lu Feng, Li Haifeng, et al.Performance Evaluation and Comparison of Seven Microscopic Transportation Simulation Systems[J]. Computer and Communications, 2007, 25(1): 66-70.
[12] Sun J, Zhao L, Zhang M, et al.Mechanism of Early-Onset Breakdown at On-Ramp Bottlenecks on Shanghai, China, Expressways[J]. Transportation Research Record Journal of the Transportation Research Board (S0361-1981), 2014, 2421: 64-73.
[13] Helbing D, Hennecke A, Shvetsov V, et al.Micro- and macro-simulation of freeway traffic[J]. Mathematical & Computer Modelling An International Journal (S0895-717), 2002, 35(5/6): 517-547.
[14] Sun J, Ouyang J, Yang J.Modeling and Analysis of Merging Behavior at Expressway On-Ramp Bottlenecks[J]. Transportation Research Record Journal of the Transportation Research Board (S0361-1981), 2014, 2421(1): 74-81.

智能汽车环境感知与规划决策一体化仿真测试平台

Integrated Simulation Test Platform for Environment Perception and Planning Decision of Intelligent Vehicle

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