Journal Home Online First Current Issue Archive For Authors Journal Information 中文版

Engineering >> 2018, Volume 4, Issue 4 doi: 10.1016/j.eng.2018.07.015

A Hardware Platform Framework for an Intelligent Vehicle Based on a Driving Brain

a Department of Computer Science and Technology, Tsinghua University, Beijing 100084, China

b State Key Laboratory of Automotive Safety and Energy, Tsinghua University, Beijing 100084, China

c Center for Intelligent Connected Vehicles and Transportation, Tsinghua University, Beijing 100084, China

Received: 2017-06-07 Revised: 2017-10-12 Accepted: 2018-07-13 Available online: 2018-07-20

Next Previous

Abstract

The type, model, quantity, and location of sensors installed on the intelligent vehicle test platform are different, resulting in different sensor information processing modules. The driving map used in intelligent vehicle test platform has no uniform standard, which leads to different granularity of driving map information. The sensor information processing module is directly associated with the driving map information and decision-making module, which leads to the interface of intelligent driving system software module has no uniform standard. Based on the software and hardware architecture of intelligent vehicle, the sensor information and driving map information are processed by using the formal language of driving cognition to form a driving situation graph cluster and output to a decision-making module, and the output result of the decision-making module is shown as a cognitive arrow cluster, so that the whole process of intelligent driving from perception to decision-making is completed. The formalization of driving cognition reduces the influence of sensor type, model, quantity, and location on the whole software architecture, which makes the software architecture portable on different intelligent driving hardware platforms.

Figures

Fig. 1

Fig. 2

Fig. 3

Fig. 4

Fig. 5

Fig. 6

Fig. 7

References

[ 1 ] Gage DW. UGV History 101: a brief history of unmanned ground vehicle (UGV) development efforts. Unmanned Syst Mag 1970;13(3):9–32. link1

[ 2 ] Luo X, Deng J, Wang WP, Wang JH, Zhao WB. A quantized kernel learning algorithm using a minimum kernel risk-sensitive loss criterion and bilateral gradient technique. Entropy 2017;19(7):365. link1

[ 3 ] Kanade T, Thorpe C. CMU strategic computing vision project report: 1984 to 1985. Pittsburgh: Carnegie-Mellon University; 1986. link1

[ 4 ] Williams M. PROMETHEUS-the European research programme for optimising the road transport system in Europe. In: Proceedings of IEE Colloquium International Conference on Driver Information; 1988 Dec 1; London, UK; 1998. p. 1–9. link1

[ 5 ] Wang SL, Zhao YP, Shu Y, Yuan HN, Geng J, Wang SP. Fast search local extremum for maximal information coefficient (MIC). J Comput Appl Math 2018;327:372–87. link1

[ 6 ] Tsugawa S, Aoki M, Hosaka A, Seki K. A survey of present IVHS activities in Japan. Control Eng Pract 1997;5(11):1591–7. link1

[ 7 ] Luo X, Zhang DD, Yang LT, Liu J, Chang XH, Ning HS. A kernel machine-based secure data sensing and fusion scheme in wireless sensor networks for the cyber-physical systems. Future Gener Comput Syst 2016;61:85–96. link1

[ 8 ] Gao HB, Cheng B, Wang JQ, Li KQ, Zhao JH, Li DY. Object classification using CNN-based fusion of vision and LIDAR in autonomous vehicle environment. IEEE Trans Ind Inform 2018;99:1. link1

[ 9 ] Gao HB, Zhang XY, Zhang TL, Liu YC, Li DY. Research of intelligent vehicle variable granularity evaluation based on cloud model. Acta Electron Sin 2016;44(2):365–73.

[10] Bertozzi M, Broggi A, Fascioli A. VisLab and the evolution of vision-based UGVs. Comput 2006;39(12):31–8. link1

[11] Kolski S, Ferguson D, Bellino M, Siegwart R. Autonomous driving in structured and unstructured environments. In: Proceedings of 2006 IEEE Intelligent Vehicles Symposium; 2006 Jun 13–15; Tokyo, Japan; 2006. p. 558–63. link1

[12] Yuan HN, Wang SL, Geng J, Yu Y, Zhong M. Robust clustering with distance and density. Int J Data Wareh Min 2017;13(2):63–74. link1

[13] Guizzo E. How Google’s self-driving car works [Internet]. New York: IEEE Spectrum; c2018 [updated 2011 Oct 18; cited 2017 Jul 30]. link1

[14] Luo X, Luo H, Chang XH. Online optimization of collaborative web service QoS prediction based on approximate dynamic programming. Int J Distrib Sens Netw 2015;11(8):4524921. link1

[15] Bayerl SFX, Luettel T, Wuensche HJ. Following dirt roads at night-time: sensors and features for lane recognition and tracking. In: Proceedings of the 7th Workshop on Planning, Perception and Navigation for Intelligent Vehicles; 2015 Sep 28; Hamburg, Germany; 2015. link1

[16] Luo X, Deng J, Liu J, Wang W, Ban X, Wang JH. A quantized kernel least mean square scheme with entropy-guided learning for intelligent data analysis. China Commun 2017;14(7):127–36. link1

[17] Dissanayake MWMG, Newman P, Clark S, Durrant-Whyte HF, Csorba M. A solution to the simultaneous localization and map building problem. IEEE Trans Robot Autom 2001;17(3):229–41. link1

[18] Zou R, Wang M, Wang SL, Li S, Zhang C, Deng L, et al. Adaptive laser shock micro-forming for MEMS device applications. Opt Express 2017;25 (4):3875–83. link1

[19] Zhang XY, Gao HB, Guo M, Li GP, Liu YC, Li DY. A study on key technologies of unmanned driving. CAAI Trans Intell Technol 2016;1(1):4–13. link1

[20] Luo X, Liu J, Zhang DD, Chang X. A large-scale web QoS prediction scheme for the industrial internet of things based on a kernel machine learning algorithm. Comput Netw 2016;101:81–9. link1

[21] Su MH. BYD SuRei 2013 china intelligent vehicle future challenge. Consum Guide 2013;2013(11):76. Chinese.

[22] Yu ZX, Xue YF, Zhu Y, Sun XS. Army Military Transportation University intelligent vehicle team won the first two places in the Sixth China Intelligent Vehicle Future Challenge. Auto Appl 2015;1:F0002. Chinese.

[23] Tang CJ. Unmanned bus made in Henan is under road test in an endless stream on Zhengkai expressway. Henan Business Daily 2015 Aug 31;Sect. A09. Chinese.

[24] Ma M, Wang L, Zhang K. Whether 3D printing can change the manufacturing industry or not—interview with Academician Bingheng Lu of Chinese Academy of Engineering. High Technol Ind 2013;9(4):38–43. Chinese. link1

Related Research