-
Notifications
You must be signed in to change notification settings - Fork 1
/
Copy pathindex.html
2748 lines (1625 loc) · 145 KB
/
index.html
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
402
403
404
405
406
407
408
409
410
411
412
413
414
415
416
417
418
419
420
421
422
423
424
425
426
427
428
429
430
431
432
433
434
435
436
437
438
439
440
441
442
443
444
445
446
447
448
449
450
451
452
453
454
455
456
457
458
459
460
461
462
463
464
465
466
467
468
469
470
471
472
473
474
475
476
477
478
479
480
481
482
483
484
485
486
487
488
489
490
491
492
493
494
495
496
497
498
499
500
501
502
503
504
505
506
507
508
509
510
511
512
513
514
515
516
517
518
519
520
521
522
523
524
525
526
527
528
529
530
531
532
533
534
535
536
537
538
539
540
541
542
543
544
545
546
547
548
549
550
551
552
553
554
555
556
557
558
559
560
561
562
563
564
565
566
567
568
569
570
571
572
573
574
575
576
577
578
579
580
581
582
583
584
585
586
587
588
589
590
591
592
593
594
595
596
597
598
599
600
601
602
603
604
605
606
607
608
609
610
611
612
613
614
615
616
617
618
619
620
621
622
623
624
625
626
627
628
629
630
631
632
633
634
635
636
637
638
639
640
641
642
643
644
645
646
647
648
649
650
651
652
653
654
655
656
657
658
659
660
661
662
663
664
665
666
667
668
669
670
671
672
673
674
675
676
677
678
679
680
681
682
683
684
685
686
687
688
689
690
691
692
693
694
695
696
697
698
699
700
701
702
703
704
705
706
707
708
709
710
711
712
713
714
715
716
717
718
719
720
721
722
723
724
725
726
727
728
729
730
731
732
733
734
735
736
737
738
739
740
741
742
743
744
745
746
747
748
749
750
751
752
753
754
755
756
757
758
759
760
761
762
763
764
765
766
767
768
769
770
771
772
773
774
775
776
777
778
779
780
781
782
783
784
785
786
787
788
789
790
791
792
793
794
795
796
797
798
799
800
801
802
803
804
805
806
807
808
809
810
811
812
813
814
815
816
817
818
819
820
821
822
823
824
825
826
827
828
829
830
831
832
833
834
835
836
837
838
839
840
841
842
843
844
845
846
847
848
849
850
851
852
853
854
855
856
857
858
859
860
861
862
863
864
865
866
867
868
869
870
871
872
873
874
875
876
877
878
879
880
881
882
883
884
885
886
887
888
889
890
891
892
893
894
895
896
897
898
899
900
901
902
903
904
905
906
907
908
909
910
911
912
913
914
915
916
917
918
919
920
921
922
923
924
925
926
927
928
929
930
931
932
933
934
935
936
937
938
939
940
941
942
943
944
945
946
947
948
949
950
951
952
953
954
955
956
957
958
959
960
961
962
963
964
965
966
967
968
969
970
971
972
973
974
975
976
977
978
979
980
981
982
983
984
985
986
987
988
989
990
991
992
993
994
995
996
997
998
999
1000
<!DOCTYPE html>
<html class="theme-next muse use-motion" lang="en">
<head>
<meta charset="UTF-8"/>
<meta http-equiv="X-UA-Compatible" content="IE=edge" />
<meta name="viewport" content="width=device-width, initial-scale=1, maximum-scale=1"/>
<meta http-equiv="Cache-Control" content="no-transform" />
<meta http-equiv="Cache-Control" content="no-siteapp" />
<link href="/lib/fancybox/source/jquery.fancybox.css?v=2.1.5" rel="stylesheet" type="text/css" />
<link href="//fonts.googleapis.com/css?family=Lato:300,300italic,400,400italic,700,700italic&subset=latin,latin-ext" rel="stylesheet" type="text/css">
<link href="/lib/font-awesome/css/font-awesome.min.css?v=4.6.2" rel="stylesheet" type="text/css" />
<link href="/css/main.css?v=5.1.1" rel="stylesheet" type="text/css" />
<meta name="keywords" content="Hexo, NexT" />
<link rel="shortcut icon" type="image/x-icon" href="/favicon.ico?v=5.1.1" />
<meta name="description" content="what I don't know">
<meta property="og:type" content="website">
<meta property="og:title" content="Serious Autonomous Vehicles">
<meta property="og:url" content="http://yoursite.com/index.html">
<meta property="og:site_name" content="Serious Autonomous Vehicles">
<meta property="og:description" content="what I don't know">
<meta property="og:locale" content="en">
<meta name="twitter:card" content="summary">
<meta name="twitter:title" content="Serious Autonomous Vehicles">
<meta name="twitter:description" content="what I don't know">
<script type="text/javascript" id="hexo.configurations">
var NexT = window.NexT || {};
var CONFIG = {
root: '/',
scheme: 'Muse',
sidebar: {"position":"left","display":"post","offset":12,"offset_float":0,"b2t":false,"scrollpercent":false,"onmobile":false},
fancybox: true,
motion: true,
duoshuo: {
userId: '0',
author: 'Author'
},
algolia: {
applicationID: '',
apiKey: '',
indexName: '',
hits: {"per_page":10},
labels: {"input_placeholder":"Search for Posts","hits_empty":"We didn't find any results for the search: ${query}","hits_stats":"${hits} results found in ${time} ms"}
}
};
</script>
<link rel="canonical" href="http://yoursite.com/"/>
<title>Serious Autonomous Vehicles</title>
</head>
<body itemscope itemtype="http://schema.org/WebPage" lang="en">
<div class="container sidebar-position-left
page-home
">
<div class="headband"></div>
<header id="header" class="header" itemscope itemtype="http://schema.org/WPHeader">
<div class="header-inner"><div class="site-brand-wrapper">
<div class="site-meta ">
<div class="custom-logo-site-title">
<a href="/" class="brand" rel="start">
<span class="logo-line-before"><i></i></span>
<span class="site-title">Serious Autonomous Vehicles</span>
<span class="logo-line-after"><i></i></span>
</a>
</div>
<p class="site-subtitle"></p>
</div>
<div class="site-nav-toggle">
<button>
<span class="btn-bar"></span>
<span class="btn-bar"></span>
<span class="btn-bar"></span>
</button>
</div>
</div>
<nav class="site-nav">
<ul id="menu" class="menu">
<li class="menu-item menu-item-home">
<a href="/" rel="section">
<i class="menu-item-icon fa fa-fw fa-home"></i> <br />
Home
</a>
</li>
<li class="menu-item menu-item-archives">
<a href="/archives/" rel="section">
<i class="menu-item-icon fa fa-fw fa-archive"></i> <br />
Archives
</a>
</li>
<li class="menu-item menu-item-tags">
<a href="/tags/" rel="section">
<i class="menu-item-icon fa fa-fw fa-tags"></i> <br />
Tags
</a>
</li>
<li class="menu-item menu-item-search">
<a href="javascript:;" class="popup-trigger">
<i class="menu-item-icon fa fa-search fa-fw"></i> <br />
Search
</a>
</li>
</ul>
<div class="site-search">
<div class="popup search-popup local-search-popup">
<div class="local-search-header clearfix">
<span class="search-icon">
<i class="fa fa-search"></i>
</span>
<span class="popup-btn-close">
<i class="fa fa-times-circle"></i>
</span>
<div class="local-search-input-wrapper">
<input autocomplete="off"
placeholder="Searching..." spellcheck="false"
type="text" id="local-search-input">
</div>
</div>
<div id="local-search-result"></div>
</div>
</div>
</nav>
</div>
</header>
<main id="main" class="main">
<div class="main-inner">
<div class="content-wrap">
<div id="content" class="content">
<section id="posts" class="posts-expand">
<article class="post post-type-normal " itemscope itemtype="http://schema.org/Article">
<link itemprop="mainEntityOfPage" href="http://yoursite.com/2020/11/22/one-picture-of-ADS-today/">
<span hidden itemprop="author" itemscope itemtype="http://schema.org/Person">
<meta itemprop="name" content="David Z.J. Lee">
<meta itemprop="description" content="">
<meta itemprop="image" content="/images/avatar.jpg">
</span>
<span hidden itemprop="publisher" itemscope itemtype="http://schema.org/Organization">
<meta itemprop="name" content="Serious Autonomous Vehicles">
</span>
<header class="post-header">
<h1 class="post-title" itemprop="name headline">
<a class="post-title-link" href="/2020/11/22/one-picture-of-ADS-today/" itemprop="url">one picture of ADS today</a></h1>
<div class="post-meta">
<span class="post-time">
<span class="post-meta-item-icon">
<i class="fa fa-calendar-o"></i>
</span>
<span class="post-meta-item-text">Posted on</span>
<time title="Post created" itemprop="dateCreated datePublished" datetime="2020-11-22T21:07:55-05:00">
2020-11-22
</time>
</span>
<span class="post-comments-count">
<span class="post-meta-divider">|</span>
<span class="post-meta-item-icon">
<i class="fa fa-comment-o"></i>
</span>
<a href="/2020/11/22/one-picture-of-ADS-today/#comments" itemprop="discussionUrl">
<span class="post-comments-count disqus-comment-count"
data-disqus-identifier="2020/11/22/one-picture-of-ADS-today/" itemprop="commentCount"></span>
</a>
</span>
</div>
</header>
<div class="post-body" itemprop="articleBody">
<p><img src="/images/full-pic-of-ads-full-stack.png" alt="image"></p>
</div>
<div>
</div>
<div>
</div>
<div>
</div>
<footer class="post-footer">
<div class="post-eof"></div>
</footer>
</article>
<article class="post post-type-normal " itemscope itemtype="http://schema.org/Article">
<link itemprop="mainEntityOfPage" href="http://yoursite.com/2020/11/22/mobility-data-center-in-ADAS-ADS/">
<span hidden itemprop="author" itemscope itemtype="http://schema.org/Person">
<meta itemprop="name" content="David Z.J. Lee">
<meta itemprop="description" content="">
<meta itemprop="image" content="/images/avatar.jpg">
</span>
<span hidden itemprop="publisher" itemscope itemtype="http://schema.org/Organization">
<meta itemprop="name" content="Serious Autonomous Vehicles">
</span>
<header class="post-header">
<h1 class="post-title" itemprop="name headline">
<a class="post-title-link" href="/2020/11/22/mobility-data-center-in-ADAS-ADS/" itemprop="url">mobility data center in ADAS/ADS</a></h1>
<div class="post-meta">
<span class="post-time">
<span class="post-meta-item-icon">
<i class="fa fa-calendar-o"></i>
</span>
<span class="post-meta-item-text">Posted on</span>
<time title="Post created" itemprop="dateCreated datePublished" datetime="2020-11-22T04:10:33-05:00">
2020-11-22
</time>
</span>
<span class="post-comments-count">
<span class="post-meta-divider">|</span>
<span class="post-meta-item-icon">
<i class="fa fa-comment-o"></i>
</span>
<a href="/2020/11/22/mobility-data-center-in-ADAS-ADS/#comments" itemprop="discussionUrl">
<span class="post-comments-count disqus-comment-count"
data-disqus-identifier="2020/11/22/mobility-data-center-in-ADAS-ADS/" itemprop="commentCount"></span>
</a>
</span>
</div>
</header>
<div class="post-body" itemprop="articleBody">
<p><strong>keywords</strong>: autosar, data factory, AI training, simulation, v&v, DevOps, IoT, adas applications</p>
<p>2~3 years ago, the top teams focus on perception, planning kinds of AI algorithms, which is benefited from the bursting of DNN, and lots invest goes there, and the optimism think once the best training model is founded, self-driving is ready to go. </p>
<p>then there was a famous talk about “long tail problems in AV” from Waymo team in 2018, the people realize to solve this problem, they need as many data as possible and as cheap as possible, which gives a new bussiness about data factory, data pipeline. </p>
<p>the investors realize the most cuting-edge AI model is just a small piece of done, there should be a data factory, which comes from MaaS serivces providers or traditional OEMs. </p>
<p>as data collector doesn’t exist common in traditional vehicles, so OEMs have to first make a new vehicle networking arch to make ADAS/ADS data collecting possible. which by the end, the game is back to OEMs. </p>
<p>at this point, IoT providers see their cake in AD market, OEMs may have a little understanding about in-vehicle gateway, t-box, but edge computing, cloud data pipeline are mostly owned by IoT providers, e.g. HuaWei and public data service providers, e.g. China Mobility. and the emerging of 5G infrastructure nationally also acc their share. </p>
<p>pipeline is one thing, the other is in-vehicle SoC, which has a few matured choices, such as Renasas, NXP, Mobileye, Nvidia Drive PX2/Xavier/Orin, and a bunch of new teams, such as horizon robotics, HuaWei MDC e.t.c </p>
<p>the traditionally definition of in-vehicle SoC has a minor underline about data pipeline and the dev tools around. but nowadays, taking a look at HuwWei MDC, the eco is so closed, from hardware to software, from in-vehicle to cloud. of course, the pioneer Nvidia has expand the arch from vehicle to cloud, from dev to validation already. </p>
<p>SoC is the source of ADS/ADAS data, which give the role of SoC as mobility data center(MDC), we see the totally mindset transfer from software define vehicle to data defined vehicle. </p>
<p>the mechanical part of the vehicle is kind of de-valued when thought vehicle just as another source of data on-line. </p>
<p>to maximize the value of data, the data serivces(software) is better decoupled from vehicle hardwares(ecu, controller), which is another trend in OEMs, e.g. autosar. </p>
<p>till now, we see the AI models, simulation, data services are just the tip of the iceberg. and this is the time we see self dirving as the integrated application for AI, 5G, cloud computing infra and future manufacturing. and the market is so large, no one can eat it all. </p>
<h2 id="refer"><a href="#refer" class="headerlink" title="refer"></a>refer</h2><p><a href="https://bbs.huaweicloud.com/blogs/142759" target="_blank" rel="external">AutoSAR Classic from Huawei</a></p>
<p>Mobileye赖以成名的EyeQ系列芯片同样内嵌了感知算法，但其在出售产品时候，往往都是软硬件打包出售，并不会根据客户情况进行针对性修改，或是让客户的算法运行在自己的感知芯片上。但地平线则采用完全开放的理念，即可提供硬件、也可提供包括算法的整体方案，还给客户提供了名为天工开物的完整工具链，让客户自己对芯片上的算法进行调整优化。</p>
<ul>
<li><p>Matrix2 (地平线）</p>
</li>
<li><p>mdc (huawei)</p>
</li>
<li><p>Drive PX 2 (nvidia)</p>
</li>
<li><p>DRIVE AGX Xavier （nvidia) </p>
</li>
<li><p>Orin (Nvidia)</p>
</li>
</ul>
<p><a href="https://www.sohu.com/a/321995543_391994" target="_blank" rel="external">车载智能计算基础平台 参考架构 1.0</a></p>
<p><a href="https://blogs.nvidia.cn/category/auto/" target="_blank" rel="external">nvidia self driving form</a></p>
<p><a href="https://blogs.nvidia.cn/2019/07/01/higher-standard-lead-industry-safety-group/" target="_blank" rel="external">nvidia lead the most safe standard</a></p>
<p>凭借我们自身在安全和工程方面的经验，NVIDIA已致力于领导欧洲汽车供应商协会（CLEPA）互联自动驾驶车辆工作组。NVIDIA在仿真技术和功能安全方面，拥有丰富的发展历史。我们的自动驾驶汽车团队在汽车安全和工程方面拥有宝贵的经验。</p>
<p>通过NVIDIA DRIVE Constellation这样的平台，制造商可以通过该平台对他们的技术进行长距离的驾驶测试，还可以设定在现实世界中很少遇到的罕见或危险测试场景</p>
<p>NVIDIA还与自动化与测量系统标准化协会（ASAM）合作。我们正在领导其中一个工作组，以定义创建仿真场景的开放标准，描述道路拓扑表示、传感器模型、世界模型，以及行业标准和关键性能指标，从而推进自动驾驶车辆部署的验证方法。</p>
<p>业界正在开发一套新标准——ISO 21448，被称为预期功能安全（SOTIF）。它旨在避免即使所有车辆部件都处于正常运行的状态，但依然有可能会引发风险的情况。例如，如果运行在车辆中的深度神经网络错误地识别了道路中的交通标志或物体，则即使软件没有发生故障也可能产生不安全的情况。</p>
<p><a href="https://www.nvidia.com/content/dam/en-zz/Solutions/self-driving-cars/safety-report/NVIDIA-Self-Driving-Safety-Report-2018.pdf" target="_blank" rel="external">nvidia drive</a></p>
<ul>
<li><p>Drive OS </p>
</li>
<li><p>Drive AV(a variety of DNNs)</p>
</li>
<li><p>Drive Hyperion(AGX Pegasus, and sensors)</p>
</li>
<li><p>Drive IX</p>
</li>
<li><p>Drive Mapping </p>
</li>
</ul>
<ul>
<li>Drive Constellation, a data center solution to test and validate the actual hardware/software in an AV car</li>
</ul>
<p>data factory -> AI training -> </p>
<p> We also expand the use of our DNNs to support features like automatic emergency steering and autonomous emergency braking, providing redundancy to these functionalities</p>
<p> We also define key performance metrics to measure the collected data quality and add synthetic data into our training datasets</p>
<p> we incorporate actual sensor data from automatic emergency braking scenarios using re-simulation to help eliminate false positives.</p>
<p> NVIDIA created the DRIVE Road Test Operating Handbook to ensure a safe, standardized on-road testing process.</p>
</div>
<div>
</div>
<div>
</div>
<div>
</div>
<footer class="post-footer">
<div class="post-eof"></div>
</footer>
</article>
<article class="post post-type-normal " itemscope itemtype="http://schema.org/Article">
<link itemprop="mainEntityOfPage" href="http://yoursite.com/2020/11/21/leetCode-swap-pairs/">
<span hidden itemprop="author" itemscope itemtype="http://schema.org/Person">
<meta itemprop="name" content="David Z.J. Lee">
<meta itemprop="description" content="">
<meta itemprop="image" content="/images/avatar.jpg">
</span>
<span hidden itemprop="publisher" itemscope itemtype="http://schema.org/Organization">
<meta itemprop="name" content="Serious Autonomous Vehicles">
</span>
<header class="post-header">
<h1 class="post-title" itemprop="name headline">
<a class="post-title-link" href="/2020/11/21/leetCode-swap-pairs/" itemprop="url">leetCode_swap_pairs</a></h1>
<div class="post-meta">
<span class="post-time">
<span class="post-meta-item-icon">
<i class="fa fa-calendar-o"></i>
</span>
<span class="post-meta-item-text">Posted on</span>
<time title="Post created" itemprop="dateCreated datePublished" datetime="2020-11-21T08:22:01-05:00">
2020-11-21
</time>
</span>
<span class="post-comments-count">
<span class="post-meta-divider">|</span>
<span class="post-meta-item-icon">
<i class="fa fa-comment-o"></i>
</span>
<a href="/2020/11/21/leetCode-swap-pairs/#comments" itemprop="discussionUrl">
<span class="post-comments-count disqus-comment-count"
data-disqus-identifier="2020/11/21/leetCode-swap-pairs/" itemprop="commentCount"></span>
</a>
</span>
</div>
</header>
<div class="post-body" itemprop="articleBody">
<h2 id="background"><a href="#background" class="headerlink" title="background"></a>background</h2><p><a href="https://leetcode-cn.com/problems/swap-nodes-in-pairs/" target="_blank" rel="external">LeetCode24: swap pairs</a></p>
<h2 id="intuitive-sol"><a href="#intuitive-sol" class="headerlink" title="intuitive sol"></a>intuitive sol</h2><figure class="highlight"><table><tr><td class="gutter"><pre><div class="line">1</div><div class="line">2</div><div class="line">3</div><div class="line">4</div><div class="line">5</div><div class="line">6</div><div class="line">7</div><div class="line">8</div><div class="line">9</div><div class="line">10</div><div class="line">11</div><div class="line">12</div><div class="line">13</div><div class="line">14</div><div class="line">15</div><div class="line">16</div><div class="line">17</div><div class="line">18</div><div class="line">19</div><div class="line">20</div><div class="line">21</div><div class="line">22</div><div class="line">23</div><div class="line">24</div><div class="line">25</div><div class="line">26</div><div class="line">27</div><div class="line">28</div><div class="line">29</div><div class="line">30</div><div class="line">31</div><div class="line">32</div><div class="line">33</div><div class="line">34</div><div class="line">35</div><div class="line">36</div><div class="line">37</div><div class="line">38</div><div class="line">39</div><div class="line">40</div><div class="line">41</div><div class="line">42</div><div class="line">43</div><div class="line">44</div><div class="line">45</div><div class="line">46</div><div class="line">47</div><div class="line">48</div><div class="line">49</div><div class="line">50</div><div class="line">51</div><div class="line">52</div><div class="line">53</div><div class="line">54</div><div class="line">55</div><div class="line">56</div><div class="line">57</div><div class="line">58</div><div class="line">59</div><div class="line">60</div><div class="line">61</div><div class="line">62</div><div class="line">63</div><div class="line">64</div><div class="line">65</div><div class="line">66</div><div class="line">67</div><div class="line">68</div><div class="line">69</div><div class="line">70</div><div class="line">71</div><div class="line">72</div><div class="line">73</div><div class="line">74</div><div class="line">75</div><div class="line">76</div><div class="line">77</div><div class="line">78</div><div class="line">79</div><div class="line">80</div><div class="line">81</div><div class="line">82</div><div class="line">83</div><div class="line">84</div><div class="line">85</div><div class="line">86</div><div class="line">87</div><div class="line">88</div><div class="line">89</div><div class="line">90</div><div class="line">91</div><div class="line">92</div><div class="line">93</div><div class="line">94</div><div class="line">95</div><div class="line">96</div><div class="line">97</div><div class="line">98</div><div class="line">99</div></pre></td><td class="code"><pre><div class="line"> struct ListNode {</div><div class="line"> int val;</div><div class="line"> ListNode *next;</div><div class="line"> ListNode() : val(0), next(nullptr) {}</div><div class="line"> ListNode(int x) : val(x), next(nullptr) {}</div><div class="line"> ListNode(int x, ListNode *next) : val(x), next(next) {}</div><div class="line"> };</div><div class="line"></div><div class="line">#include <iostream></div><div class="line"></div><div class="line">class Solution {</div><div class="line">public:</div><div class="line"> ListNode* swapPairs(ListNode* head) {</div><div class="line"> ListNode *dummy = new ListNode(-1);</div><div class="line"> ListNode *prev = dummy ;</div><div class="line"> prev->next = head ;</div><div class="line"> ListNode *p1=head, *p2=p1->next, *p3=p2->next, *p4=p3->next, *pn, *tmp ;</div><div class="line"></div><div class="line"> if(p1 == nullptr)</div><div class="line"> {</div><div class="line"> return nullptr ;</div><div class="line"> }else if(p2 == nullptr){</div><div class="line"> return p1 ;</div><div class="line"> }else if(p3 == nullptr)</div><div class="line"> {</div><div class="line"> p2->next = p1 ;</div><div class="line"> p1->next = nullptr ;</div><div class="line"> head = p2 ;</div><div class="line"> return head ;</div><div class="line"> }else if(p4 == nullptr)</div><div class="line"> {</div><div class="line"> head->next = p2 ;</div><div class="line"> p2->next = p1 ;</div><div class="line"> p1 ->next = p3;</div><div class="line"> return head ;</div><div class="line"> }</div><div class="line"></div><div class="line"> for(p1=head, p2=p1->next, p3=p2->next, p4=p3->next ; p4 && p3 && p2 && p1; prev=p3, p1=prev->next, p2=p1->next, p3=p2->next, p4=p3->next )</div><div class="line">{</div><div class="line"></div><div class="line"> pn = p4->next ;</div><div class="line"> p2->next = p1 ;</div><div class="line"> p4->next = p3 ;</div><div class="line"> p1->next = p4;</div><div class="line"> p3->next = pn ;</div><div class="line"> prev->next = p2 ;</div><div class="line"></div><div class="line"> if (pn == nullptr)</div><div class="line"> {</div><div class="line"> break;</div><div class="line"> }else if(pn->next == nullptr)</div><div class="line"> {</div><div class="line"> break;</div><div class="line"> }else if (pn->next->next == nullptr)</div><div class="line"> {</div><div class="line"> break;</div><div class="line"> }else if(pn->next->next->next == nullptr)</div><div class="line"> {</div><div class="line"> break;</div><div class="line"> }</div><div class="line"></div><div class="line">}</div><div class="line"></div><div class="line"> if(pn == nullptr || pn->next == nullptr){</div><div class="line"> return prev->next;</div><div class="line"> }</div><div class="line"> if(pn->next->next == nullptr )</div><div class="line"> {</div><div class="line"> tmp = pn->next ;</div><div class="line"> prev->next = pn->next ;</div><div class="line"> tmp->next = pn ;</div><div class="line"> pn->next = nullptr;</div><div class="line"> }else if(pn->next->next->next == nullptr){</div><div class="line"> tmp = pn->next ;</div><div class="line"> ListNode *last = tmp->next ;</div><div class="line"> prev->next = tmp ;</div><div class="line"> pn->next = last ;</div><div class="line"></div><div class="line"> }</div><div class="line"> return prev->next;</div><div class="line"> }</div><div class="line">};</div><div class="line"></div><div class="line">int main()</div><div class="line">{</div><div class="line"> ListNode *head = new ListNode(1);</div><div class="line"> ListNode *sec = new ListNode(2);</div><div class="line"> ListNode *thd = new ListNode(3);</div><div class="line"> ListNode *fth = new ListNode(4);</div><div class="line"> head->next = sec ;</div><div class="line"> sec->next = thd ;</div><div class="line"> thd->next = fth ;</div><div class="line"></div><div class="line"> Solution *sol = new Solution();</div><div class="line"></div><div class="line"> ListNode *res = sol->swapPairs(head) ;</div><div class="line"> std::cout << res->val << ', ' << res->next->val << ', ' << res->next->next->val << std::endl;</div><div class="line"> return 0;</div><div class="line">}</div></pre></td></tr></table></figure>
</div>
<div>
</div>
<div>
</div>
<div>
</div>
<footer class="post-footer">
<div class="post-eof"></div>
</footer>
</article>
<article class="post post-type-normal " itemscope itemtype="http://schema.org/Article">
<link itemprop="mainEntityOfPage" href="http://yoursite.com/2020/10/12/why-Hil-MiL-SiL-and-ViL/">
<span hidden itemprop="author" itemscope itemtype="http://schema.org/Person">
<meta itemprop="name" content="David Z.J. Lee">
<meta itemprop="description" content="">
<meta itemprop="image" content="/images/avatar.jpg">
</span>
<span hidden itemprop="publisher" itemscope itemtype="http://schema.org/Organization">
<meta itemprop="name" content="Serious Autonomous Vehicles">
</span>
<header class="post-header">
<h1 class="post-title" itemprop="name headline">
<a class="post-title-link" href="/2020/10/12/why-Hil-MiL-SiL-and-ViL/" itemprop="url">why Hil MiL SiL and ViL</a></h1>
<div class="post-meta">
<span class="post-time">
<span class="post-meta-item-icon">
<i class="fa fa-calendar-o"></i>
</span>
<span class="post-meta-item-text">Posted on</span>
<time title="Post created" itemprop="dateCreated datePublished" datetime="2020-10-12T19:10:50-04:00">
2020-10-12
</time>
</span>
<span class="post-comments-count">
<span class="post-meta-divider">|</span>
<span class="post-meta-item-icon">
<i class="fa fa-comment-o"></i>
</span>
<a href="/2020/10/12/why-Hil-MiL-SiL-and-ViL/#comments" itemprop="discussionUrl">
<span class="post-comments-count disqus-comment-count"
data-disqus-identifier="2020/10/12/why-Hil-MiL-SiL-and-ViL/" itemprop="commentCount"></span>
</a>
</span>
</div>
</header>
<div class="post-body" itemprop="articleBody">
<h2 id="background"><a href="#background" class="headerlink" title="background"></a>background</h2><p>there are two very different teams in AD. one kind is people from top Tier1 and popular OEMs, the benefit of these guys is they are very matured at the product process management, e.g. V&V and the corresponding R&D process, the other pons of these guys, they have lots of engineering know-how/experience to make things work. mostly we know how the system/tool work, but compared to build the sytem/tool to work, the first knowledge is about 10%. </p>
<p>the mature R&D process is, as I see, is very valuable in a long time, which we’d say <strong>engineers getting richer as they getting older</strong>. till now, German and Janpanese top companies still have strong atmosphere to respect engineers, which keeps their engineers and their industry process management growing more and more mature. that’s a very good starting point for fresh young men, if they can join these top companies in early time. </p>
<p>the other team is from Internet companies, they are the kind of people with philosophy: as you can image out, I can build it up. while the philosophy always become true in IT and Internet service companies, and looks promising in industry fields, as the IT infra, like nowadays, service to cloud, office work in cloud, which derives lots of cloud infra, but the core like robot operation, making vehicle driving automatically, or computer aided engineering e.t.c. requires lots of know-how, far beyond the infra. </p>
<p>Internet teams are popular in China and US, but US still have strong engieer atmosphere like Germany, which is not in China. basically I want to say, there is no apprentice process to train fresh men to matured engineers in either companies or training organizations in China, which makes engineers here show low credit. </p>
<p>even Internet knowledge and skills in China, often we’d say <strong>programming work are youth meals, as programmer getting older they getting poor</strong></p>
<p>that’s the tough situation for many young people, if the men got neither good engineering training, nor got smart and young enough to coding, he get doomed in his career. but that’s not a problem for the country neither for the companies, still Chinese workers are cheap, there are always lots of young people need bread beyond a promising career. </p>
<h2 id="physical-or-virtual"><a href="#physical-or-virtual" class="headerlink" title="physical or virtual"></a>physical or virtual</h2><p>the first-principal of writing a program:</p>
<ul>
<li>make it run ok </li>
<li>make it run correct</li>
<li>make it run performance-well</li>
<li>make it extensible </li>
</ul>
<p>the following is to understand why we need HiL, mil, sil, to ViL during verification and validation of an ADS product, from the physical or virtual viewpoint. </p>
<h3 id="physical-or-virtual-world"><a href="#physical-or-virtual-world" class="headerlink" title="physical or virtual world"></a>physical or virtual world</h3><h5 id="case-1-from-physical-world-to-physical-sensor"><a href="#case-1-from-physical-world-to-physical-sensor" class="headerlink" title="case 1) from physical world to physical sensor"></a>case 1) from physical world to physical sensor</h5><p>namely, physical road test, either in closed-field, or open roads. </p>
<p>this is the case when we need ground truth(G.T.) system to validate the device under test(DUT) sensor, to evaluate or test the DUT’s performance boundary, failure mode e.t.c. </p>
<p>the people can come from sensor evaluation teams, or system integration teams. </p>
<h5 id="case-2-from-virtual-world-to-physical-sensor"><a href="#case-2-from-virtual-world-to-physical-sensor" class="headerlink" title="case 2) from virtual world to physical sensor"></a>case 2) from virtual world to physical sensor</h5><p>the virtual world come either from digital twins, or replay from a data collector. this is hardware in loop(HiL) process, which used a lot in validate either sensor, or MCUs. when using HiL to validate MCUs, the virtual world is mimic signals e.t.c</p>
<h3 id="virtual-sensor"><a href="#virtual-sensor" class="headerlink" title="virtual sensor"></a>virtual sensor</h3><h5 id="case-3-from-virtual-world-to-virtual-sensor"><a href="#case-3-from-virtual-world-to-virtual-sensor" class="headerlink" title="case 3) from virtual world to virtual sensor"></a>case 3) from virtual world to virtual sensor</h5><p>virtual sensor has three kinds basically:</p>
<ul>
<li><p>ideal (with noise) sensor model</p>
</li>
<li><p>statisticsly satisfied sensor model</p>
</li>
<li><p>physical sensor model </p>
</li>
</ul>
<p>of course, the costing is increasing from ideal to physical sensor model. </p>
<p>ideally, the downside fusion module should be no senstive to sensors, either phyiscal sensors or virtual sensors(sensor models). the benefits of capturing virtual world by virtual sensor is so cheap, which makes it very good to training perception algorithms, when physical sensor data is expensive, which is often the reality for most companies now.</p>
<p>there is <strong>local maximum</strong> issues with virtual sensor data to train AIs, so in reality, most team used to mix 10% real-world sensor data to improve or jump out from these local maximums.</p>
<p>of course, virtual sensor is one fundamental element to close loop from virtual world to vehicle moving, in a sim env. </p>
<h3 id="physical-or-virutal-perception-to-fusion"><a href="#physical-or-virutal-perception-to-fusion" class="headerlink" title="physical or virutal perception to fusion"></a>physical or virutal perception to fusion</h3><p>here is how to test fusion, does it work correctly, performance well, how to handle abnormal(failure) case.</p>
<h5 id="case-4-from-physical-sensor-perception-data-to-fusion"><a href="#case-4-from-physical-sensor-perception-data-to-fusion" class="headerlink" title="case 4) from physical sensor perception data to fusion"></a>case 4) from physical sensor perception data to fusion</h5><p>physical perception data comes in two ways:</p>
<ul>
<li>the sensor system in vehicle</li>
<li>ground truth system(G.T.)</li>
</ul>
<p>during RD stage, the sensor system in vehicle is treated as device under test(DUT), whose result can compare with the labeling outputs from G.T. system, which help to validate DUT performance, as well as to evaluate fusion performance.</p>
<p>in phyiscal world, ground truth sytem is usually equipped with a few higher precision Lidars, of course the cost is more expensive.</p>
<p>another pro of physical perception data is extract edge cases, which used to enrich the scenario libs, especially for sensor perception, and fusion. </p>
<p>during massive production stage, when the data pipeline from data collector in each running vehicle to cloud data platform is closed-loop, which means the back-end system can extract and aggregate highly volume edge case easily, then these large mount of physical perception data can drive fusion logsim.</p>
<p>question here, edge case scenarios are these abnormal perception/fusion cases, but how to detect edge cases from highly volume data in cloud(back-end), or to design the trigger mechanism in vehicle(front end) to only find out the edge cases, is not an matured work for most teams.</p>
<p>another question here, to evaluate fusion, requires objective ground truth, which is not avaiable in massive production stage. an alternative option is using a better performance and stable sensor as <strong>semi ground truth</strong>, such as Mobileye sensor.</p>
<h5 id="case-5-from-virtual-sensor-perception-data-to-fusion"><a href="#case-5-from-virtual-sensor-perception-data-to-fusion" class="headerlink" title="case 5) from virtual sensor perception data to fusion"></a>case 5) from virtual sensor perception data to fusion</h5><p>when in sim world, it’s easily to create a <strong>ground truth sensor</strong>, then it’s easily to check fusion output with the g.t. sensor, which is great, the only assuming here, is the sim world is highly vivid of the physical world. if not, the <strong>ground truth sensor</strong> is not useful, while obviously to build a digital twin as phyiscal as possible is not easy than create the ADS system. </p>
<p>on the other hand, if the sim world is not used to evaluate fusion, for example, used to generate synthetic images, point cloud to train perception AI modules, which is one benefit. </p>
<p><strong>in summary</strong>, when evaluate and validate fusion, it requires ground truth labelling, either from physical g.t. system, or virtual g.t. sensor. 1) the g.t. system is only used for during R&D stage, with a small volumn of g.t. data; for massive release stage, there is no good g.t. source yet; 2) g.t. sensor in virtual world is easy to create, but requires the virtual worls is almost physical level. </p>
<p>second opnion, fusion evaluation is deterministic and objective. so if the fusion can validated well during RD stage, considering its performance robost, stable, there is no need to validate fusion module in massive lease. when perception/fusion edge case happens, we can study them case by case.</p>
<p>third opinon, for anormal case, e.g. sensor failure, sensor occupied cases, also need validate during RD. </p>
<h3 id="planning"><a href="#planning" class="headerlink" title="planning"></a>planning</h3><p>the evaluation of planning good or not is very subjective, while in fusion, ground truth is the criteria. so there are two sols:</p>
<ul>
<li>to make subjective goals as much quanlity as possible </li>
<li>define RSS criterias to bound the planning results</li>
</ul>
<p>ideally, planning should be not sensitive to fusion output from physical world, or virtual world. and when come to planning verification, we asumme the fusion component is stable and verified-well, namely should not delay find fusion bugs till planning stage. </p>
<h5 id="case6-from-sim-fusion-output-to-planning"><a href="#case6-from-sim-fusion-output-to-planning" class="headerlink" title="case6) from sim fusion output to planning"></a>case6) from sim fusion output to planning</h5><p>SiL is a good way to verify planning model. previously, planning engineers create test scenarios in vtd, prescan, and check does the planning algorithms work.</p>
<p>for a matured team, there are maybe hundreds and thousands of planning related scenarios, the should-be verification process requires to regress on all these scenarios, so to automatically and accelerate this verification loop, gives the second solution: cloud SiL with DevOps, like TAD Sim from Tencent, Octopus from Huawei e.t.c.</p>
<p>another benefits of SiL in cloud is for complex driving behavior, real vehicle/pedestrains to vehicle interactions, and especially when the scenario lib is aggregating as the ADS lifecycle continues.</p>
<p>if the planning algorithm is AI based, then to mimic the real-human drivers driving behaivor and assign these driving behaviors to the agents in the virtual world, will be very helpful to train the ego’s planning AI model.</p>
<p>here are two models: imitation learning and reinforcement learning. firstly we train the agent/ego driving behaivor using physical world driving data by imitation learning in a training gym; and transfer these trained model to agents and ego in the sim world, they continue driving and interaction with each other, and keep training itself to do better planning. </p>
<p>for corner/edge cases, as planning is very subjective, and lots of long-tail scenarios are there, so physical world situations collection is very valuable. </p>
<h5 id="case-7-from-physical-fusion-output-to-planning"><a href="#case-7-from-physical-fusion-output-to-planning" class="headerlink" title="case 7) from physical fusion output to planning"></a>case 7) from physical fusion output to planning</h5><p>Tesla looks be the only one, who deployed the shadow mode trigging mechanism to get planning corner cases from physical driving, and the data close loop.</p>
<p>the large volumn of physical driving data is very useful for verification and iteration of planning: </p>
<ul>
<li><p>aggregate more real planning scenarios, by detecting edge cases</p>
</li>
<li><p>train better driving behavior, as close as possible to humans</p>
</li>
</ul>
<h3 id="control"><a href="#control" class="headerlink" title="control"></a>control</h3><p>control is the process from planning output, e.g. acc, decel, turning-angle to physical actuator response, brake force, engine torque e.t.c</p>
<p>there are a few common issues :</p>
<ul>
<li><p>nonlinear characteristic, mostly we don’t get a perfect control output as expect. e.g. from decel to brake force. </p>
</li>
<li><p>the actuator has response delay, which need professional engineers train to get a good balance, but still doesn’t work as expect at all the scenarios </p>
</li>
<li><p>the actuators as a whole is very complex, tuning requires.</p>
</li>
</ul>
<h5 id="case-8-from-planning-to-virtual-vehicle-model"><a href="#case-8-from-planning-to-virtual-vehicle-model" class="headerlink" title="case 8) from planning to virtual vehicle model"></a>case 8) from planning to virtual vehicle model</h5><p>this is where sim requires a high-precise vehicle dynamic model, which affects the performance. but a simple vehicle dynamic does work for planing, if not requires to cosist with the physical performance. </p>
<h4 id="case-9-from-planning-to-physical-vehicle"><a href="#case-9-from-planning-to-physical-vehicle" class="headerlink" title="case 9) from planning to physical vehicle"></a>case 9) from planning to physical vehicle</h4><p>ViL, which is another big topic </p>
</div>
<div>
</div>
<div>
</div>
<div>
</div>
<footer class="post-footer">
<div class="post-eof"></div>
</footer>
</article>
<article class="post post-type-normal " itemscope itemtype="http://schema.org/Article">
<link itemprop="mainEntityOfPage" href="http://yoursite.com/2020/10/07/find-out-ADS-simulation-trend-from-top-teams/">
<span hidden itemprop="author" itemscope itemtype="http://schema.org/Person">
<meta itemprop="name" content="David Z.J. Lee">
<meta itemprop="description" content="">
<meta itemprop="image" content="/images/avatar.jpg">
</span>
<span hidden itemprop="publisher" itemscope itemtype="http://schema.org/Organization">
<meta itemprop="name" content="Serious Autonomous Vehicles">
</span>
<header class="post-header">
<h1 class="post-title" itemprop="name headline">
<a class="post-title-link" href="/2020/10/07/find-out-ADS-simulation-trend-from-top-teams/" itemprop="url">find out ADS simulation trend from top teams</a></h1>
<div class="post-meta">
<span class="post-time">
<span class="post-meta-item-icon">
<i class="fa fa-calendar-o"></i>
</span>
<span class="post-meta-item-text">Posted on</span>
<time title="Post created" itemprop="dateCreated datePublished" datetime="2020-10-07T01:13:43-04:00">
2020-10-07
</time>
</span>
<span class="post-comments-count">
<span class="post-meta-divider">|</span>
<span class="post-meta-item-icon">
<i class="fa fa-comment-o"></i>
</span>
<a href="/2020/10/07/find-out-ADS-simulation-trend-from-top-teams/#comments" itemprop="discussionUrl">
<span class="post-comments-count disqus-comment-count"
data-disqus-identifier="2020/10/07/find-out-ADS-simulation-trend-from-top-teams/" itemprop="commentCount"></span>
</a>
</span>
</div>
</header>
<div class="post-body" itemprop="articleBody">
<h2 id="background"><a href="#background" class="headerlink" title="background"></a>background</h2><p>what’s the basic logic behind simulation in autonomous driving system(ADS) ? or why we need simulation in ADS, during AD development and even after massively produced ? how to integrate simulation in the AD closed-loop platform, namely from fleet/test data collection to valuable new features?</p>
<p>before I can answer these questions, a few steps has went through:</p>
<ul>