-
Notifications
You must be signed in to change notification settings - Fork 3
/
index.html
2543 lines (2453 loc) · 124 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>
<!-- jquery and bootstrap scripts -->
<script type="text/javascript" src="https://code.jquery.com/jquery-3.3.1.min.js"></script>
<script src="https://ajax.googleapis.com/ajax/libs/jquery/2.1.1/jquery.min.js"></script>
<script src="https://maxcdn.bootstrapcdn.com/bootstrap/3.3.7/js/bootstrap.min.js"></script>
<html lang="en" dir="ltr">
<head>
<meta charset="utf-8">
<meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no">
</meta>
<title> CMAP ABM</title>
<link href="css/chordStyles.css" rel="stylesheet">
</link>
<link rel="stylesheet" href="css/mapstyle.css">
</link>
<link rel="stylesheet" href="css/intromapstyle.css">
</link>
<link rel="stylesheet" href="https://unpkg.com/[email protected]/dist/leaflet.css" integrity="sha512-puBpdR0798OZvTTbP4A8Ix/l+A4dHDD0DGqYW6RQ+9jxkRFclaxxQb/SJAWZfWAkuyeQUytO7+7N4QKrDh+drA==" crossorigin="">
</link>
<link rel="stylesheet" type="text/css" href="css/style.css" />
<link href="https://maxcdn.bootstrapcdn.com/bootstrap/3.3.7/css/bootstrap.min.css" rel="stylesheet" />
<link rel="stylesheet" href="https://stackpath.bootstrapcdn.com/font-awesome/4.7.0/css/font-awesome.min.css">
</head>
<body style="height:100%">
<div>
<div>
<div>
<!-- Header -->
<nav class="navbar navbar-default navbar-fixed-top" id="header" style="padding-top:10px; padding-right:10px; padding-bottom:5px; z-index:9999">
<div class="container-fluid">
<a class="navbar-brand" href="https://www.cmap.illinois.gov/" target="_blank">
<img src='data/images/cmap_shortid_margins_RGB-01-01.png' height="30px">
</a>
<h3 class="navbar-text">Activity-Based Model (ABM) Calibration and Validation Report</h3>
<p class="navbar-text navbar-right">September 2019 Release </p>
</div>
</nav>
<nav class="navbar navbar-inverse navbar-fixed-top" style="margin-bottom:0px">
<div class="container-fluid" style="margin-top: 70px">
<ul class="nav navbar-nav">
<li class="active">
<a href="#1" role="tab" data-toggle="tab">
Introduction
</a>
</li>
</ul>
<ul class="nav navbar-nav">
<li class="dropdown">
<a class="dropdown-toggle" data-toggle="dropdown" role="button" aria-haspopup="true" aria-expanded="false">
Calibration
<span class="caret"></span>
</a>
<ul class="dropdown-menu">
<li>
<a class="calibration" href="#2" role="tab" data-toggle="tab">
Population Synthesis
</a>
</li>
<li>
<a class="calibration" href="#3" role="tab" data-toggle="tab">
Vehicle Ownership
</a>
</li>
<li>
<a class="calibration" href="#10" role="tab" data-toggle="tab">
Tours
</a>
</li>
<li>
<a class="calibration" href="#5" role="tab" data-toggle="tab">
Trip Mode
</a>
</li>
<li>
<a class="calibration" href="#6" role="tab" data-toggle="tab">
Trip Activities
</a>
</li>
<li>
<a class="calibration" href="#4" role="tab" data-toggle="tab">
Work Flows
</a>
</li>
<li>
<a class="calibration" href="#7" role="tab" data-toggle="tab">
Transit Trips
</a>
</li>
</ul>
</li>
<li class="dropdown">
<a class="dropdown-toggle" data-toggle="dropdown" role="button" aria-haspopup="true" aria-expanded="false">
Validation
<span class="caret"></span>
</a>
<ul class="dropdown-menu">
<li>
<a class="validation" href="#11" role="tab" data-toggle="tab">
Household Attributes
</a>
</li>
<li>
<a class="validation" href="#12" role="tab" data-toggle="tab">
Commute Trips
</a>
</li>
<li>
<a class="validation" href="#8" role="tab" data-toggle="tab">
Highway Assignment
</a>
</li>
<li>
<a class="validation" href="#9" role="tab" data-toggle="tab">
Transit Assignment
</a>
</li>
</ul>
</li>
</ul>
<ul class="nav navbar-nav navbar-right">
<li>
<a id="recall" style="display:none">
About
</a>
</li>
</ul>
</div>
</nav>
</div>
<div class="tab-content">
<div class="alert alert-info alert" role="alert" id="about">
<button type="button" class="close" id="close" aria-label="Close"><span aria-hidden="true">×</span></button>
<p style="margin-bottom:10px">
<strong>Model calibration</strong> ensures that the various components of the overall model replicate observed data for a base year. Calibration requires adjusting parameters for individual sub-models to ensure that they each produce realistic results. Calibration is complete once model results match the observed patterns found in the Census, regional household travel surveys and transit origin-destination surveys. CMAP's ABM is calibrated to a base year of 2010 because the regional household travel survey data available were collected in 2007-08.
<strong>Model validation</strong> is focused on comparing the final results of a calibrated model to other data sources such as daily traffic counts, daily transit boardings, and more recent Census data. A best practice within travel demand modeling is to use different datasets for model calibration and validation activities to double-check that the results replicate observed travel patterns. The CMAP ABM is run to reflect travel conditions for the year 2015. Validation demonstrates that the sub-models calibrated to 2010 conditions are able to represent the conditions in 2015.
<em>Data source information for each page can be found in the footer. </em>
</p>
</div>
<div id="1" class="tab-pane active container-fluid">
<div class="row">
<div class="col-md-1"></div> <!-- end -->
<div class="col-md-7">
<h2>Introduction</h2>
<p>
Activity-based models (ABMs) are founded on the idea that people’s travel behavior is a result of their daily activities; i.e., the things people need to accomplish dictate where, when, and how they travel, and with whom.
These models are
more advanced than standard travel demand models because they seek to represent the choices made by individual travelers. In order to do this, the models must generate a schedule of daily activities for members of every
household in the
region, and then transform that information into sequences of trips that occur throughout the day. To accomplish this, ABMs use detailed information about the factors that affect travel decisions, including:</p>
<ul>
<li>Households – the number of adults, children, and workers; household income; the number of vehicles available</li>
<li>People – age; work and school status; occupation</li>
<li>Trips – purpose; destination; who is taking the trip; is it part of a sequence of trips that must be completed in a specific order</li>
</ul>
Having all of this data available for individual travelers allows for a finer level of analysis than standard travel demand models. ABMs were developed as a way to better analyze the impacts of policy decisions like managed lanes, congestion pricing and alternative transit fare structures. For more information, visit
<a href="https://www.cmap.illinois.gov/data/transportation/modeling#CMAPs_Activity_Based_Models" target="_blank">CMAP's Activity-Based Models.</a> </p>
CMAP's ABM platform is CT-RAMP (Coordinated Travel and Regional Activity-Based Modeling Platform), which was developed open source by a consultant under contract to CMAP. Activity-based modeling is increasingly viewed as a superior method to better understand the socioeconomic determinants of travel choice and for evaluating modern transportation solutions. CMAP's ABM has been developed to demonstrate sensitivity to highway pricing scenarios based on each traveler's individual value of time and to improve model sensitivity to a wider range of nontraditional transit attributes, i.e., attributes such as service reliability, personal safety, station and vehicle cleanliness, and crowding that do not typically inform transit Level of Service calculations. Subsequent work on the ABM has focused on the calibration of selected sub-models and the overall validation of the model results. This report represents the results of model calibration and validation activities completed over the last several years by CMAP staff and their consultants.
</p>
</div><!-- end -->
</div> <!-- end row-->
<br>
<div class="row">
<div class="col-md-1"></div>
<div class="col-md-8">
<div class="colborder"></div><!-- end -->
</div>
</div>
<div class="row">
<div class="col-md-1"></div>
<div class="col-md-2">
<h3>CMAP Modeling Area and Network</h3>
<div id="intromaplegend"></div><br>
<p class="small">The modeling area extends beyond the 7-county CMAP region to include 21 counties. Only portions of Lee, Ogle, and LaSalle counties are included in the modeling area. </p>
<button type="button" class="btn btn-default btn-xs" id="introrecenter" value="Re-center map" onClick="zoomTo(center,regionmap)">Recenter Map</button>
</div><!-- end -->
<div class="col-md-6">
<div id="regionmap"></div><!-- end -->
</div> <!-- end -->
</div> <!-- end row -->
<br>
<br>
<div class="row">
<div class="col-md-1"></div>
<div class="col-md-8">
<div class="colborder"></div><!-- end -->
</div>
</div>
<div class="row">
<div class="col-md-1"></div>
<div class="col-md-2">
<h3>Model Steps</h3>
<p>The following provides a brief outline of the major steps involved in running CMAP’s ABM. Preliminary sets of highway and transit trip assignments are run to generate realistic congested travel times that are used by CT-RAMP when daily activities are scheduled. The model also accounts for the relative ease or difficulty involved in reaching destinations using various modes of transportation, including driving, walking and using transit.</p>
<br>
</div> <!-- end -->
<div class="col-md-6">
<br>
<div class="panel-group" id="accordion" role="tablist" aria-multiselectable="true">
<div class="panel panel-default">
<div class="panel-heading" role="tab" id="headingOne">
<h4 class="panel-title">
<a class="collapsed" role="button" data-toggle="collapse" href="#collapseOne" aria-expanded="false" aria-controls="collapseOne">
<tabstyle>1 - Population Synthesis</tabstyle>
</a>
</h4>
</div>
<div id="collapseOne" class="panel-collapse collapse" role="tabpanel" aria-labelledby="headingOne">
<div class="panel-body">
A synthetic population provides the foundation for modeling individuals’ travel behavior within an activity-based model. Using Census data and other socioeconomic information, a complete set of households for the CMAP modeling area is developed.
(see <a href="#2" role="tab" data-toggle="tab">Population Synthesis</a> tab).
This dataset contains all of the relevant attributes about each household and individual that are required by the ABM. Since the Census Bureau does not release detailed information about every household and individual, household and person records are replicated in order to generate a complete set of households for the modeling area. Target totals for various household and population attributes guide this process so the final population is representative of the region. All of the subsequent steps in the ABM rely on the data provided in the synthetic population.
</div>
</div>
</div>
<div class="panel panel-default">
<div class="panel-heading" role="tab" id="headingTwo">
<h4 class="panel-title">
<a class="collapsed" role="button" data-toggle="collapse" href="#collapseTwo" aria-expanded="false" aria-controls="collapseTwo">
<tabstyle>2 - Long Term Location Choices</tabstyle>
</a>
</h4>
</div>
<div id="collapseTwo" class="panel-collapse collapse" role="tabpanel" aria-labelledby="headingTwo">
<div class="panel-body">
Two sub-models are included in this step: one that models the usual workplace locations for workers and one that models the usual school location for students. The workplace location model accounts for the worker’s occupation, as identified by the industry category they are employed in within the synthetic person file. This information is paired with jobs within the employment categories summarized at a fine geographic level to ensure that workers are sent to locations where they could be employed in their field. Similarly, enrollment figures are provided for elementary schools, high schools and colleges to ensure students are sent to realistic school locations.
</div>
</div>
</div>
<div class="panel panel-default">
<div class="panel-heading" role="tab" id="headingThree">
<h4 class="panel-title">
<a class="collapsed" role="button" data-toggle="collapse" href="#collapseThree" aria-expanded="false" aria-controls="collapseThree">
<tabstyle>3 - Individual Mobility Attributes</tabstyle>
</a>
</h4>
</div>
<div id="collapseThree" class="panel-collapse collapse" role="tabpanel" aria-labelledby="headingThree">
<div class="panel-body">
These models simulate four mobility attributes that affect individual transport mode decisions: 1) free parking eligibility for workers in the Central Business District, i.e., a determination of whether workers will pay to park; 2) household vehicle ownership; 3) whether or not individuals hold transit passes; and 4) whether or not individuals have toll transponders.
</div>
</div>
</div>
<div class="panel panel-default">
<div class="panel-heading" role="tab" id="headingFour">
<h4 class="panel-title">
<a class="collapsed" role="button" data-toggle="collapse" href="#collapseFour" aria-expanded="false" aria-controls="collapseFour">
<tabstyle>4 - Daily Activity and Travel Pattern</tabstyle>
</a>
</h4>
</div>
<div id="collapseFour" class="panel-collapse collapse" role="tabpanel" aria-labelledby="headingFour">
<div class="panel-body">
These models schedule activities and travel tours for all household members (see <a href="#10" role="tab" data-toggle="tab">Tours</a> tab). The first sub-model classifies daily travel patterns into three types: </li>
<ul>
<li>Mandatory (work and school) – includes at least one out of home mandatory activity; </li>
<li>Non-mandatory (other purposes) – includes at least one out of home non-mandatory activity but no out of home mandatory activities; </li>
<li>Home – in home activities only, so no travel is involved. </li>
</ul>
<p>These activities are modeled as joint choices so that decisions made by household members affect the decisions of other members of the household. The next sub-models estimate the frequency and time of day for mandatory activities. These are given a higher priority for scheduling than non-mandatory and home activities. Following the scheduling of mandatory activities, individuals have “residual time windows” which can be used to schedule other activities including joint travel with other household members.
</p>
<p>The next sub-model estimates joint travel for household members. All characteristics of joint travel (travel purpose, individual household members traveling, destination and time of day) are simulated. Joint travel is conditional upon the available time window for each household member following the scheduling of mandatory activities.
</p>
<p>
The next sub-model generates maintenance tours, which cover shopping and other household errands. These tasks are allocated to a single household member to carry out, and the destinations and times of day are generated. These tours are developed sequentially for individuals to ensure consistency in their personal schedule.
</p>
<p>
The next sub-model simulates discretionary tours which are modeled for individual, not joint, travel. These are also modeled sequentially so that they could all realistically occur during an individual’s day.
</p>
<p>
The final sub-model simulates at-work tours – those tours that occur during the day with the workplace as the starting and ending location.
</p>
<center><img src="data/images/daily.JPG"></center>
</div>
</div>
</div>
<div class="panel panel-default">
<div class="panel-heading" role="tab" id="headingFive">
<h4 class="panel-title">
<a class="collapsed" role="button" data-toggle="collapse" href="#collapseFive" aria-expanded="false" aria-controls="collapseFive">
<tabstyle>5 - Tour Level Details</tabstyle>
</a>
</h4>
</div>
<div id="collapseFive" class="panel-collapse collapse" role="tabpanel" aria-labelledby="headingFive">
<div class="panel-body">
These sub-models determine the transport mode used on tours, the locations of intermediate stops made on the tours and the purpose of each stop.
</div>
</div>
</div>
<div class="panel panel-default">
<div class="panel-heading" role="tab" id="headingSix">
<h4 class="panel-title">
<a class="collapsed" role="button" data-toggle="collapse" href="#collapseSix" aria-expanded="false" aria-controls="collapseSix">
<tabstyle>6 - Trip Level Details</tabstyle>
</a>
</h4>
</div>
<div id="collapseSix" class="collapse" aria-labelledby="headingSix">
<div class="panel-body">
These sub-models add details about the trips occurring within the tours including the mode of travel, the departure time from each location and the parking location for auto trips. See <a href="#5" role="tab" data-toggle="tab">Trip Mode</a> tab and
<a href="#6" role="tab" data-toggle="tab">Trip Activities</a> tab.
<center><img src="data/images/triplevel.JPG"></center>
</div>
</div>
</div>
<div class="panel panel-default">
<div class="panel-heading" role="tab" id="headingSeven">
<h4 class="panel-title">
<a class="collapsed" role="button" data-toggle="collapse" href="#collapseSeven" aria-expanded="false" aria-controls="collapseSeven">
<tabstyle>7 - Network Simulations</tabstyle>
</a>
</h4>
</div>
<div id="collapseSeven" class="collapse" aria-labelledby="headingSeven">
<div class="panel-body">
Following development of the complete set of daily activities, trips are assigned to the travel networks. Motor vehicle trips developed by the ABM are routed along the model transportation network from origin to destination in order to estimate traffic flows and network conditions. Transit trips are assigned to a network that includes all available bus and rail options between their origins and destinations.
See <a href="#8" role="tab" data-toggle="tab">Highway Assignment</a> tab and
<a href="#9" role="tab" data-toggle="tab">Transit Assignment</a> tab.
</div>
</div>
</div>
</div>
</div><!-- end -->
</div><br><br>
<!--end row-->
</div>
<!--end tab-->
<div id="2" class="tab-pane container-fluid">
<div class="row">
<div class="col-md-1"></div>
<div class="col-md-7">
<h2>Population Synthesis</h2>
<p>
Using Census data and other socioeconomic information, a complete set of households for the CMAP modeling area is developed. This dataset contains all of the relevant attributes about each household and for each individual living in those households, which is required to run the ABM. While this population is statistically representative of the Census data, the actual households and individuals are “synthetic” in that they do not represent identifiable people and an individual household in the Census data may be replicated numerous times in order to generate a complete distribution of households in the modeling inputs.
</p>
<p>
The current population synthesis software used by CMAP is PopSynIII. The socioeconomic data developed from CMAP’s regional forecasting and Local Area Allocation procedures provide the subzone-level control values for all <dfn
data-info="ON TO 2050 is the region's long-range comprehensive plan, adopted in October 2018">ON TO 2050</dfn>
model scenarios. CMAP has greatly enhanced the functionality of PopSyn to enforce these controls and generate a distribution of enumerated households that account for the distribution of adults, workers and children within the
agency’s
forecasting procedures.
</p>
<p> Individuals are classified into one of eight mutually exclusive categories:</p>
<ul>
<li>Full-time worker: Age 16+ working at least 35 hours per week for more than 30 weeks out of the year.</li>
<li>Part-time worker: Age 16+ and a non-student employed less than full time.</li>
<li>Non-working adult: Age 16-64, non-working and a non-student.</li>
<li>Non-working senior: Age 65+, non-working and a non-student.</li>
<li>Pre-school: Age under 6.</li>
<li>Non-driving student: Age 6-15.</li>
<li>Driving age student: Age 16-19, not a full-time worker or college student.</li>
<li>University student: Age 18+ and school enrollment is college undergraduate or graduate school.</li>
</ul>
Data note: The observed data used Public Use Microdata Areas (PUMAs). PUMAs are statistical geographic areas defined by the U.S.
Census Bureau for the dissemination of Public Use Microdata Sample (PUMS) data. Two of the PUMAs used to gather observed
data include counties outside the CMAP modeling area (Stephenson County in Illinois, and Jefferson County in Wisconsin).
Data for these PUMAs is weighted by the percentage of population or households – depending on the analysis – for counties
within the CMAP modeling area. As a result, the total number of observed persons or households is not always identical for
each summary analysis.
</div><!-- end -->
</div><!-- row end -->
<br>
<div class="row">
<div class="col-md-1"></div>
<div class="col-md-8">
<div class="colborder"></div>
</div>
</div>
<div class="row">
<div class="col-md-1"></div>
<div class="col col-md-2">
<h3>Population by Person Type</h3>
<div id="hlegend"></div><!-- end -->
<p class="small">
Note on "Full-time workers": The model defines full-time workers as persons working 30+ weeks in the year and
35+ hours per week. Full-time workers in the observed data are persons working 27+ weeks in the year and 35+ hours per week.
</p><br>
<img src="data/images/Cursor-Click-2-icon.png" width="20px">
<span class="small">Hover over population categories to reveal details.</span>
</div> <!-- end -->
<div class="col-md-6">
<div id="PopPersonType"></div><!-- end -->
</div> <!-- end -->
<div class="col col-md-2">
<div class="container">
<br />
<br />
<br />
<br />
<img src="data/images/icons8-add-50.png" class="image">
<div class="overlay">
<p>
The model closely represents the number of full-time workers in the region (the largest person type by percentage).
The model slightly overestimates the number of part-time workers and non-working adults. The largest disparities
between the modeled and observed populations in terms of percentage points are for university students and
non-working seniors. In both instances, the model is underrepresenting the population of these person types.
</p>
</div>
</div>
</div>
</div> <!-- end -->
<br>
<div class="row">
<div class="col-md-1"></div> <!-- end -->
<div class="col-md-8">
<div class="colborder"></div>
</div>
</div>
<div class="row">
<div class="col col-md-1">
</div>
<div class="col col-md-2">
<h3>Households by Size</h3>
<br>
<div id="hhlegend"></div><!-- end -->
<img src="data/images/Cursor-Click-2-icon.png" width="20px">
<span class="small">Hover over household size categories to reveal details.</span>
</div> <!-- end -->
<div class="col-md-6">
<div id="HouseholdSize" width="100%"></div><!-- end -->
</div> <!-- end -->
<div class="col col-md-2">
<div class="container">
<br />
<br />
<br />
<br />
<img src="data/images/icons8-add-50.png" class="image">
<div class="overlay">
<p>
In terms of the percentage of total households, the model slightly underrepresents
one-person households in the region. The model also underrepresents the number of two-person households.
However, three and four-person households
are considerably overrepresented in the model. The largest disparity between modeled and observed
households in terms of percentage is for large households (5+ people). </p>
</div>
</div>
</div>
</div> <!-- end row-->
<div class="row">
<div class="col-md-1"></div> <!-- end -->
<div class="col-md-8">
<div class="colborder"></div>
</div>
</div>
<div class="row">
<div class="col col-md-1">
</div>
<div class="col-md-2">
<h3>Household Characteristics</h3>
<h5>Households by <span id="hhtitle"></span>
</h5>
<br><br>
<select id="catPopSyn">
<option value="age">Head of Household Age</option>
<option value="workers">Household Workers</option>
<option value="income">Household Income</option>
<option value="size">Household Size</option>
<option value="veh">Vehicles in Household</option>
</select><!-- end -->
<br><br>
<div id="pumsLegend"></div>
<br>
<br>
<p class="small">
Income is in 1999 dollars.
</p>
</div><!-- end -->
<div class="col-md-6">
</h4><!-- end -->
<div id="PurposeChartpums"></div><!-- end -->
</div><!-- end -->
<div class="col col-md-2">
<div class="container">
<br />
<br />
<br />
<br />
<img src="data/images/icons8-add-50.png" class="image">
<div class="overlay">
<p>
The model does a reasonably well job of representing the various household characteristics.
For instance, the number of 0-worker households is almost identical in the modeled and observed data,
and the number of vehicles by household are very similar for modeled and observed households.
The model slightly overestimates the number of lower income households and underestimates the number of high income households. </p>
</div>
</div>
</div>
</div> <!-- end -->
<br>
<div class="row">
<div class="col-md-1"></div> <!-- end -->
<div class="col-md-8">
<div class="colborder"></div>
</div>
</div>
<div class="row">
<div class="col col-md-1">
</div>
<div class="col-md-2">
<h3>Household Detail</h3>
<h5>Distribution of Adults Per Household by <div id="popcttitle"></div>
</h5>
<br>
<select id="popsyn_ct">
<option value="children">Children</option>
<option value="workers">Workers</option>
</select>
<br>
<br>
<div id="stackedAdultLegend"></div>
<br>
</div>
<div class="col col-md-6">
<div id="popsyncrosstab"></div>
</div>
<div class="col col-md-2">
<div class="container">
<br />
<br />
<br />
<br />
<img src="data/images/icons8-add-50.png" class="image">
<div class="overlay">
<p>
There is a discrepancy in the number of workers in households with one adult,
and the model overestimates the total number of households with three adults.
Similarly, when examining households by the number of children, the model overestimates
the number of households with two adults and one child and underestimates the number of
households with two children, regardless of the number of adults in the household.</p>
</div>
</div>
</div>
</div>
</div>
<!--end tab-->
<!-- Auto Counts -->
<div id="3" class="tab-pane container-fluid">
<div class="row">
<!--Auto Counts-->
<div class="col-md-1"></div>
<!--end-->
<div class="col-md-7">
<h2>Vehicle Ownership</h2>
<p>
Vehicle ownership plays an important role in individuals’ travel behavior decisions and helps define the set of travel mode options available to them. For example, households that own no vehicles may be dependent on transit to make their trips. Note that vehicle ownership refers to motor vehicles owned or leased by a household, including autos, pickup trucks, SUVs and motorcycles.
</p>
<br>
</div>
</div> <!-- end row -->
<div class="row">
<div class="col-md-1"></div>
<!-- <div class="col-md-2"></div> end -->
<div class="col-md-8">
<div class="colborder"></div>
</div>
</div>
<div class="row">
<div class="col-md-1"></div>
<div class="col-md-2">
<h3>Number of Households by Vehicles Owned</h3>
Total Households: <span class="modtotal"></span> Model, <span class="surveytotal"></span> Survey
<div id="autoLegend"></div>
</div>
<div class="col-md-6">
<br>
<svg id="aoCountBar" width="700" height="375" preserveAspectRatio="xMidYMid meet"></svg>
</div>
<div class="col col-md-2">
<div class="container">
<br />
<br />
<br />
<br />
<img src="data/images/icons8-add-50.png" class="image">
<div class="overlay">
<p>
The model does a good job predicting the number of vehicles owned by households. It is just slightly under-estimating the number of households with zero or 1 vehicle, and is just slightly over-estimating that number of households that own at least 2 vehicles. </p>
</div>
</div>
</div>
</div>
<div class="row">
<div class="col-md-1"></div>
<!-- <div class="col-md-2"></div> end -->
<div class="col-md-8">
<div class="colborder"></div>
</div>
</div>
<div class="row">
<br>
<div class="col-md-1"></div>
<div class="col-md-2">
<!-- <h3>Auto Sufficiency</h3> -->
<h3>Distribution of Vehicle Ownership by <div id="dtitle"></div>
</h3>
Total Households: <span class="modtotal"></span> Model, <span class="surveytotal"></span> Survey
<br><br>
<select id="aoCat">
<option value="size">Household Size</option>
<option value="income">Household Income</option>
<option value="workers">Household Workers</option>
</select>
<br>
<div id="stackedAutoLegend"></div>
<br>
<br>
<p class="small">
Income is in 1999 dollars.
</p>
</div>
<div class="col col-md-6">
<div id="stackedbar"></div>
</div>
<div class="col col-md-2">
<div class="container">
<br />
<br />
<br />
<br />
<img src="data/images/icons8-add-50.png" class="image">
<div class="overlay">
<p>
The model accurately predicts the distribution of vehicle ownership by household size, household income, and household workers. However, the model tends to under-estimate the number of households with at least 3 vehicles for larger households and high income households. It is also over-estimating the number of zero-worker households that own at least 2 vehicles. </p>
</div>
</div>
</div>
</div>
</div>
<!-- Work Flows -->
<div id="4" class="tab-pane container-fluid">
<div class="row">
<div class="col-md-1"></div> <!-- end -->
<div class="col-md-6">
<h2>Work Flows</h2>
<p>
Commute trips are an important part of a region’s overall travel pattern and are a key component of
congestion experienced on the transportation system, especially during the morning and evening hours.
Ensuring that commuters are traveling between the appropriate home and work locations is one important way
to verify that travel demand models reflect actual travel patterns. <br><br>
Note there are two sources for observed data on this page. The first three tables use data from journey-to-work flows from the Census
Transportation Planning Package (CTPP). The remaining two charts use data from household travel surveys. CTPP data is generally used to
estimate models that address work flows due to the large sample of data included. Data from household travel surveys can be used to supplement
the journey-to-work information from the CTPP, as travel surveys offer more detailed information about the trips than the Census provides.
</p>
<br>
</div>
</div>
<div class="row">
<div class="col-md-1"></div>
<div class="col-md-8 colborder"> </div>
</div>
<div class="row">
<div class="col-md-1"></div>
<div class="col-md-3">
<h3>Modeled Journey to Work Flows</h3>
<br>
</div>
<div class="col-md-6">
<br />
<table id="modelcountyflow_cal"> </table>
</div>
</div>
<div class="row">
<div class="col-md-1"></div>
<div class="col-md-8 colborder"> </div>
</div>
<div class="row">
<div class="col-md-1"></div>
<div class="col-md-3">
<h3>Observed Journey to Work Flows</h3>
<br>
</div>
<div class="col-md-6">
<br />
<table id="ctppcountyflow_cal"> </table>
</div>
</div>
<div class="row">
<div class="col-md-1"></div>
<div class="col-md-8 colborder"> </div>
</div>
<div class="row">
<div class="col-md-1"></div>
<div class="col-md-3">
<h3>Difference Model and Observed Journey to Work Flows</h3>
<br>
</div>
<div class="col-md-5">
<br />
<table id="caldiffcountyflow"> </table>
</div>
<div class="col col-md-2">
<div class="container">
<br />
<br />
<br />
<br />
<img src="data/images/icons8-add-50.png" class="image">
<div class="overlay">
<p>
The model does a good job of replicating the number of commute trips being made within and between the counties in the CMAP region. For instance, the model matches the Census data in showing that the top three work locations in northeastern Illinois are Cook, DuPage and Lake counties, in that order. Both the modeled and observed data show that close to 45% of the total work trips made in the extended modeling area occur entirely within Cook County. The model is underestimating the number of Cook and DuPage residents that live in one county and work in the other. It is also underestimating the number of Cook residents that work in Lake and Will counties.
</p>
</div>
</div>
</div>
</div>
<div class="row">
<div class="col-md-1"></div>
<div class="col-md-8 colborder"> </div>
</div>
<div class="row">
<div class="col-md-1"></div> <!-- end -->
<div class="col-md-2" style="text-align:center">
<br />
<h3>Origin and Destination Work Flows</h3>
From
<!-- Split button -->
<div class="btn-group" id="workfrom" style="margin:auto;width:auto">
<button type="button" id="WorkFrom" class="btn btn-danger" style="color: rgb(171, 171, 171); font-size: 18px;">Chicago (CBD)</button>
<button type="button" class="btn btn-info dropdown-toggle" style="background-color: rgb(207, 207, 207) !important; border-color: rgb(207, 207, 207) !important" data-toggle="dropdown" aria-haspopup="true" aria-expanded="false">
<span class="caret"></span>
<span class="sr-only">Toggle Dropdown</span>
</button>
<ul class="dropdown-menu">
<li><a>All</a></li>
<li><a>Chicago (CBD)</a></li>
<li><a>Chicago (North)</a></li>
<li><a>Chicago (South)</a></li>
<li><a>Chicago (West)</a></li>
<li><a>Cook (North)</a></li>
<li><a>Cook (South)</a></li>
<li><a>Cook (West)</a></li>
<li><a>DuPage</a></li>
<li><a>Kane</a></li>
<li><a>Kendall</a></li>
<li><a>Lake</a></li>
<li><a>McHenry</a></li>
<li><a>Will</a></li>
</ul>
</div>
<br>
To
<!-- Split button -->
<div class="btn-group" id="workto">
<button type="button" id="WorkTo" class="btn btn-danger" style="color: rgb(171, 171, 171); font-size: 18px;">Chicago (CBD)</button>
<button type="button" class="btn btn-info dropdown-toggle" style="background-color: rgb(207, 207, 207) !important; border-color: rgb(207, 207, 207) !important" data-toggle="dropdown" aria-haspopup="true" aria-expanded="false">
<span class="caret"></span>
<span class="sr-only">Toggle Dropdown</span>
</button>
<ul class="dropdown-menu">
<li><a>All</a></li>
<li><a>Chicago (CBD)</a></li>
<li><a>Chicago (North)</a></li>
<li><a>Chicago (South)</a></li>
<li><a>Chicago (West)</a></li>
<li><a>Cook (North)</a></li>
<li><a>Cook (South)</a></li>
<li><a>Cook (West)</a></li>
<li><a>DuPage</a></li>
<li><a>Kane</a></li>
<li><a>Kendall</a></li>
<li><a>Lake</a></li>
<li><a>McHenry</a></li>
<li><a>Will</a></li>
</ul>
</div>
<br>
<div id="wflowinfocontainer" style="display:inline-block">
<div id="wflowinfo" style="margin-left:20px;"></div>
<div id="wflowinfo2" style="margin-left:20px;"></div>
</div><br><br>
<div id="wflowmap"></div>
<br>
<div style="text-align:left">
<button type="button" class="btn btn-default btn-xs" id="wrecenter" value="Re-center map" onClick="zoomTo(center,wflowmap)">Recenter Map</button>
<img src="data/images/Cursor-Click-2-icon.png" width="20px">
<span class="small" style="text-align:left">Hover over the chord diagram to see area boundaries on the map. Click on the map to see area name. Choose work flow geographies in the drop down menu to view numerical values for work
trips.</span>
</div>
</div>
<div class="col col-md-6">
<div class="col col-md-6" align="center">
<br />
<h3>Modeled</h3>
<br />
<br />
<div id="modelChord"></div>
</div>
<div class="col col-md-6" align="center">
<br />
<h3>Observed</h3>
<br />
<br />
<div id="obsChord"></div>
</div>
</div>
<div class="col col-md-2">
</div>
</div>
<!--- Row End -->
<div class="row">
<div class="col-md-1"></div>
<div class="col-md-8 colborder"> </div>
</div>
<div class="row">
<div class="col-md-1"></div>
<div class="col-md-8 colborder"> </div>
</div>
<div class="row">
<div class="col-md-1"></div>
<div class="col col-md-2">
<h3>Work Trips by Mode and Distance</h3>
<br>
<p>
<span id="worktripsmodedistance_p"></span>
of all work trips</p>
<select id="catModeDist">
<option value="all">All Modes</option>
<option value="sovfree">Drive Alone (non-toll)</option>
<option value="sovpay">Drive Alone (toll)</option>
<option value="hov2free">Shared ride 2 (non-toll)</option>
<option value="hov2pay">Shared ride 2 (toll)</option>
<option value="hov3">Shared ride 3+</option>
<option value="transit">Transit</option>
<option value="walk">Walk</option>
<option value="bike">Bike</option>
<option value="taxi">Taxi</option>
</select>
<br><br>
<div id="worktripsdistanceLegend"></div>
<div class="small" style="margin-top: 20px;">
Shared ride 3+ toll and non-toll trips are combined due to the small sample of these trips captured by the Travel Tracker Survey.
<br><br>
</div>
</div>
<div class="col col-md-6">
<div id="ModeByDistance"></div>
</div>
<div class="col col-md-2">
<div class="container">
<br />
<br />
<br />
<br />
<img src="data/images/icons8-add-50.png" class="image">
<div class="overlay">
<p>
Driving is the most frequently used mode for traveling to work in the region and the model does a reasonable job replicating the number of people driving different distances to work. Nearly two-thirds of the commute trips in the region are people driving alone on trips that do not involve paying a toll and the modeled trips match the distance pattern for this group well, somewhat overestimating the extremely short trips (under 2.5 miles) and underestimating the trips longer than 30 miles. A similar pattern is seen in the transit trips – the longer trips are underrepresented in the model and the shorter trips are overrepresented. </p>
</div>
</div>
</div>
</div>
<div class="row">
<div class="col-md-1"></div>
<div class="col-md-8 colborder"> </div>
</div>
</div>
<div id="5" class="tab-pane container-fluid">
<div class="row">
<div class="col-md-1"></div>
<div class="col-md-7">
<h2>Trips by Mode</h2>
<p>
The CT-RAMP model includes eleven options for travel modes. These include the non-motorized options of walking or cycling, as well as transit, taxis and school bus. There are six options for auto trips, which are categorized by the number of vehicle occupants and whether or not the trip includes a toll. Vehicle occupancy categories include single occupants, two people sharing a vehicle, or more than two people sharing a vehicle.
</p>
<br>
</div>
</div>
<br>
<div class="row">
<div class="col-md-1"></div>
<!-- <div class="col-md-2"></div> end -->
<div class="col-md-8">
<div class="colborder"></div>
</div>
</div>
<div class="row">
<div class="col-md-1"></div>
<div class="col col-md-2">
<h3>Trips by Mode</h3>
<svg id="modelegend" style="height:300px"></svg>
<br />
<div class="small">
See more about transit in the <a href="#7" role="tab" data-toggle="tab">Transit</a> tab. <br>
<img src="data/images/Cursor-Click-2-icon.png" width="20px">
<span>Hover over bars to compare trips by mode.</span>
<br><br>
</div>
</div>
<div class="col col-md-6">
<div id="stackedmode"></div>
</div>
<div class="col col-md-2">
<div class="container">
<br />
<br />
<br />
<br />
<img src="data/images/icons8-add-50.png" class="image">
<div class="overlay">
<p>
While the model tends to overestimate walk trips,
all other modes match observed trips fairly well. The model maintains relative shares among mode categories.
</p>
</div>
</div>
</div>
<!-- <div class="col col-md-4" align = "center">
<div class="colborder"></div>
<h5><b>Modeled Mode Share</b></h5>
<p style="font-size:small;">CMAP ABM - 2010 Scenario</p>
<div id="pieMode2"></div>
</div> -->
</div>
<div class="row">
<div class="col-md-1"></div> <!-- end -->
<div class="col-md-8">
<div class="colborder"></div>
</div>
</div>
<div class="row">
<div class="col col-md-1">
</div>
<div class="col col-md-2">
<!-- <div class="colborder"></div>end -->
<h3>Trips by Person Type and Mode</h3>
<br>
<p>
<span id="tripspersonmode_p"></span>
of all trips</p>
<select id="catModePer">
<option value="All">All</option>
<option value="Full-time worker">Full-time Worker</option>
<option value="Part-time worker">Part-time Worker</option>
<option value="Non-worker">Non worker</option>
<option value="Retired">Non-working senior</option>
<option value="Child too young for school">Preschool</option>
<option value="Student of driving age">Student 16+</option>
<option value="Student of non-driving age">Student under 16 years</option>
<option value="University student">University Student</option>
</select>
<div id="tripspersonLegend"></div>
<div class="small" style="margin-top: 20px;">
Individual trips only. <br>
</div><br>
</div>
<div class="col col-md-6">
<!-- <div class="colborder"></div>end -->
<div id="ModebyPerson"></div>
</div>
<div class="col col-md-2">
<div class="container">
<br />
<br />
<br />
<br />
<img src="data/images/icons8-add-50.png" class="image">
<div class="overlay">
<p>
Modeled trip modes for non-student person types are close to observed trips modes. Though student trips are not reflected as accurately,
they make up a small fraction
of all trips. In many cases, modeled student trips are closer to the