Development Trend of In-Vehicle Networks and Research Progress of In-Vehicle Optical Fiber Transmission

Weijie Sheng; Jinyun Chen; Yasi Wang; Lin Sun; Yi Cai; Gangxiang Shen; Ning Liu

doi:10.3788/LOP220669

Laser & Optoelectronics Progress, Volume. 60, Issue 5, 0500005(2023)

Development Trend of In-Vehicle Networks and Research Progress of In-Vehicle Optical Fiber Transmission

Weijie Sheng¹, Jinyun Chen¹, Yasi Wang¹, Lin Sun^1,2, Yi Cai^1,2, Gangxiang Shen^1,2, and Ning Liu^1,2、*

Author Affiliations

¹1 School of Electronic and Information Engineering, Soochow University, Suzhou 215006, Jiangsu, China

²Key Laboratory of Suzhou Advanced Optical Communication Network Technologies, Suzhou 215006, Jiangsu, China

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Abstract Get PDF(in Chinese)

Figures & Tables(10)

Fig. 1. Evolution of sensor fusion. (a) Transmission after data processing; (b) transmission before data processing^[40]

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Fig. 2. Existing in-vehicle network architecture and its evolution. (a) Gateway architecture; (b) domain architecture; (c) zone architecture^[44]

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Fig. 3. Traditional in-vehicle network bus. (a) CAN bus; (b) FlexRay bus

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Fig. 4. Architecture of in-vehicle Ethernet network^[45]

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Table 1. Existing car cameras installation schemes

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Table 1. Existing car cameras installation schemes

Brand	Vehicle model	Resolution（highest pixel of cameras）	Camera number	Circular camera number	Other camera number
XPeng	P7（XPILOT 3.0）^［10］	2 million	14	4	10（high sensing camera）
XPeng	P5（XPILOT 3.4）^［11］	2 million	13	3	10（high sensing camera）
NIO	ET7^［12］	8 million	11	4	7
NIO	ES8^［13］	2 million	5	4	1
TESLA	Autopilot 2.0^［4］	1.2 million	8	2	3（front facing camera）+3（rear camera）

Table 2. LiDAR numbers and relative data for different car vendors

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Table 2. LiDAR numbers and relative data for different car vendors

Model	LiDAR brand and quantity	Field angle /［（°）×（°）］	Angular resolution /［（°）×（°）］	Remark
MARVEL R7^［17］	A Luninar-Iris rotary scanning LiDAR^［18］	120×26	0.05×0.05	640 line equivalent
ARCFOX α S HI^［19］	3 LiDARs of Huawei 96 line^［20］	120×25	0.25×0.26	Point cloud 96 line
NIO ET7^［21］	Ultra long distance high precision LiDAR with 1 innovusion-Falcon^［22］	120×25	0.06×0.06	300 line equivalent

Table 3. LiDAR transmission speed of main stream manufacturers
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Table 3. LiDAR transmission speed of main stream manufacturers
Product name Data bandwidth /（Mb·s^-1）
RS-Ruby（64）（Robosense）^［24］ 29.72
RS-Ruby（128）（Robosense） 47.55
Alpha Prima（VLS-128）（Velodyne）^［25］ 47.55

Table 4. Millimeter wave radar solutions for some car vendors

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Table 4. Millimeter wave radar solutions for some car vendors

Model	Millimeter wave radar
Audi A8^［29］	Equipped with 5 millimeter wave radars（1 LRR+4 MRR）
Mercedes-Benz S^［30］	Equipped with 6 millimeter wave radars（1 LRR+1 MRR+4 SRR）
Bavarian Motor Work Pro^［31］	Equipped with 5 millimeter wave radars（4 SRR +1 LRR）

Table 5. Millimeter wave radar specifications of different car vendors

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Table 5. Millimeter wave radar specifications of different car vendors

Millimeter Wave Radar

Radar frequency band /GHz

Angle /（°）

Distance /m

Transmission

Continental ARS 404-21 long range millimeter wave radar^［32］

76-77

Azimuth：-9.0-+9.0

Elevation：0-18

0.20-170

1×CAN -high speed 500 kb·s^-1

Delphi ESR millimeter wave radar^［33］

7.7×10^-8

Azimuth：-10-+10

Elevation：0-14

1-175

CAN

Continental ARS 408-21 ultra long range millimeter wave radar^［34］

76-77

Azimuth：-9.0-+9.0

Elevation：0-14

0.20-1200（long distance）

1×CAN-high speed500 kb·s^-1

Table 6. Comparison of sensors in different situations
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Table 6. Comparison of sensors in different situations
Factor Camera LiDAR Radar Fusion
Range - - √ √
Resolution √ - × √
Distance accuracy - √ √ √
Color perception √ × × √
Lane detection √ × × √
Obstacle edge detection √ √ × √
Weather condition × - √ √

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Weijie Sheng, Jinyun Chen, Yasi Wang, Lin Sun, Yi Cai, Gangxiang Shen, Ning Liu. Development Trend of In-Vehicle Networks and Research Progress of In-Vehicle Optical Fiber Transmission[J]. Laser & Optoelectronics Progress, 2023, 60(5): 0500005

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