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i-am-sijiai-am-sijia
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Merge pull request #1 from wsp-sag/asim-v1.3-integration
ActivitySim v1.3 and Sharrow Compatible
2 parents 8e042f8 + 59cd7d3 commit 1951adf

37 files changed

+261
-207
lines changed

‎configs/_dummy_coefficients.csv‎

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coefficient_name,value,constrain
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coef_one,1,T

‎configs/atwork_subtour_destination.csv‎

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@@ -12,14 +12,14 @@ Distance_square_oth,"@np.where((df.tour_type == 'maint'), ((np.minimum(skims[('S
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OPOP logsum for work purpose,"@np.where((df.tour_type == 'business'), (df.mode_choice_logsum), 0)",1
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OPOP logsum for eating out purpose,"@np.where((df.tour_type == 'eat'), (df.mode_choice_logsum), 0)",1
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OPOP logsum for other purpose,"@np.where((df.tour_type == 'maint'), (df.mode_choice_logsum), 0)",1
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Size variable applied for work purposes,"@np.where((df.tour_type == 'business'), df['atwork'].apply(np.log1p), 0)",0.461
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Size variable applied for eating out purposes,"@np.where((df.tour_type == 'eat'), df['atwork'].apply(np.log1p), 0)",0.6904
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Size variable applied for other purposes,"@np.where((df.tour_type == 'maint'), df['atwork'].apply(np.log1p), 0)",0.6166
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Size variable applied for work purposes,"@np.where((df.tour_type == 'business'), df['size_term'].apply(np.log1p), 0)",0.461
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Size variable applied for eating out purposes,"@np.where((df.tour_type == 'eat'), df['size_term'].apply(np.log1p), 0)",0.6904
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Size variable applied for other purposes,"@np.where((df.tour_type == 'maint'), df['size_term'].apply(np.log1p), 0)",0.6166
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# shortWalkOrig == 1 for all purposes,,
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Not SOV on mandatory tour & short walk,"@(~df.tour_mode.isin(['DRIVEALONEFREE','DRIVEALONEPAY']))",2.485
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No Eat subtour Attractions,"@np.where(((df.tour_type == 'eat') & (df['atwork'].apply(np.log1p) == 0)), 1, 0)",-999
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No Business subtour Attractions,"@np.where(((df.tour_type == 'business') & (df['atwork'].apply(np.log1p) == 0)), 1, 0)",-999
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No Maint subtour Attractions,"@np.where(((df.tour_type == 'maint') & (df['atwork'].apply(np.log1p) == 0)), 1, 0)",-999
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No Eat subtour Attractions,"@np.where(((df.tour_type == 'eat') & (df['size_term'].apply(np.log1p) == 0)), 1, 0)",-999
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No Business subtour Attractions,"@np.where(((df.tour_type == 'business') & (df['size_term'].apply(np.log1p) == 0)), 1, 0)",-999
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No Maint subtour Attractions,"@np.where(((df.tour_type == 'maint') & (df['size_term'].apply(np.log1p) == 0)), 1, 0)",-999
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Distance,"@(np.minimum(skims[('SOV_FREE_DISTANCE', 'MD')], 20))",0.135698
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Distance squared,"@((np.minimum(skims[('SOV_FREE_DISTANCE', 'MD')], 20)) ** 2)",-0.0123613
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Distance cubed,"@((np.minimum(skims[('SOV_FREE_DISTANCE', 'MD')], 20)) ** 3)",0.0001337

‎configs/atwork_subtour_destination_sample.csv‎

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Description,Expression,atwork
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offpeak period sov distance,"@skims[('SOV_FREE_DISTANCE', 'MD')]",-0.2
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Size variable ,@df['atwork'].apply(np.log1p),1
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No attractions,@df['atwork']==0,-999
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Size variable ,@df['size_term'].apply(np.log1p),1
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No attractions,@df['size_term']==0,-999

‎configs/auto_ownership.yaml‎

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SPEC: auto_ownership.csv
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COEFFICIENTS: auto_ownership_coeffs.csv
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LOGSUM_CHOOSER_COLUMNS:
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- num_drivers
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- num_workers
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‎configs/cdap.yaml‎

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INDIV_AND_HHSIZE1_SPEC: cdap_indiv_and_hhsize1.csv
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COEFFICIENTS: _dummy_coefficients.csv
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INTERACTION_COEFFICIENTS: cdap_interaction_coefficients.csv
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FIXED_RELATIVE_PROPORTIONS_SPEC: cdap_fixed_relative_proportions.csv
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‎configs/logging.yaml‎

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handlers: [console, logfile]
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propagate: false
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orca:
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sharrow:
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level: WARN
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handlers: [console, logfile]
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propagate: false
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black:
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# sharrow uses black to reformat code, but we don't generally care
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# about messages emitted by black unless they are serious
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level: WARN
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blib2to3:
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# this is a vendored library within black that we also want to squelch
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level: WARN
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handlers:
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logfile:
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class: logging.FileHandler
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filename: !!python/object/apply:activitysim.core.config.log_file_path ['activitysim.log']
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filename:
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get_log_file_path: activitysim.log
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mode: w
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formatter: fileFormatter
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level: NOTSET
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console:
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class: logging.StreamHandler
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stream: ext://sys.stdout
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formatter: simpleFormatter
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formatter: elapsedFormatter
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level: NOTSET
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formatters:
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format: '%(asctime)s - %(levelname)s - %(name)s - %(message)s'
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datefmt: '%d/%m/%Y %H:%M:%S'
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elapsedFormatter:
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(): activitysim.core.tracing.ElapsedTimeFormatter
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format: '[{elapsedTime}] {levelname:s}: {message:s}'
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style: '{'

‎configs/mandatory_tour_frequency.csv‎

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@@ -25,10 +25,10 @@ Can walk to work - Retired interaction,(ptype == 5) & (distance_to_work < 3),0,0
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Can walk to school - University student interaction,(ptype == 3) & (distance_to_school < 3),0,0,0,0.7114,0
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Can walk to school - Driving-age child interaction,(ptype == 6) & (distance_to_school < 3),0,0,0,0.7114,0
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Can walk to school - Pre-driving age child who is in school interaction,((ptype == 7)|(ptype == 8)) & (distance_to_school < 3),0,0,0,0.7114,0
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Can walk to work or school - Full-time worker interaction,(ptype == 1) & (distance_to_work < 3 | distance_to_school < 3),0,0,0,0,0.1391
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Can walk to work or school - Part-time worker interaction,(ptype == 2) & (distance_to_work < 3 | distance_to_school < 3),0,0,0,0,0.1391
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Can walk to work or school - University student interaction,(ptype == 3) & (distance_to_work < 3 | distance_to_school < 3),0,0,0,0,0.1391
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Can walk to work or school - Driving-age child interaction,(ptype == 6) & (distance_to_work < 3 | distance_to_school < 3),0,0,0,0,0.1391
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Can walk to work or school - Full-time worker interaction,(ptype == 1) & ((distance_to_work) < 3 | (distance_to_school < 3)),0,0,0,0,0.1391
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Can walk to work or school - Part-time worker interaction,(ptype == 2) & ((distance_to_work < 3) | (distance_to_school < 3)),0,0,0,0,0.1391
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Can walk to work or school - University student interaction,(ptype == 3) & ((distance_to_work < 3) | (distance_to_school < 3)),0,0,0,0,0.1391
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Can walk to work or school - Driving-age child interaction,(ptype == 6) & ((distance_to_work < 3) | (distance_to_school < 3)),0,0,0,0,0.1391
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Round trip auto time to work - Full-time worker interaction,(ptype == 1) * roundtrip_auto_time_to_work,0,-0.003518,0,0,-0.003124
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Round trip auto time to work - Part-time worker interaction,(ptype == 2) * roundtrip_auto_time_to_work,0,-0.003518,0,0,-0.003124
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Round trip auto time to work - University student interaction,(ptype == 3) * roundtrip_auto_time_to_work,0,-0.003518,0,0,-0.003124

‎configs/mandatory_tour_scheduling.yaml‎

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work: workplace_zone_id
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school: school_zone_id
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univ: school_zone_id
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explicit_chunk: 0.2

‎configs/non_mandatory_tour_destination.csv‎

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Description,Expression,escort,escortkids,escortnokids,shopping,eatout,othmaint,social,othdiscr
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Mode choice logsum,mode_choice_logsum,1,1,1,coef_shopping_mode_logsum,coef_eatout_mode_logsum,coef_othmaint_mode_logsum,1,1
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Intrazonal,@(df['zone_id']==df['home_zone_id']),0,0,0,0,0,0,0,0
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Intrazonal,@(df['alt_dest']==df['home_zone_id']),0,0,0,0,0,0,0,0
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CBD area type,@df['is_CBD'],0,0,0,coef_shopping_cbd,coef_eatout_cbd,coef_othmaint_cbd,coef_social_cbd,0
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Urban high area type,@df['is_urban'],0,0,0,coef_shopping_urban,coef_eatout_urban,coef_othmaint_urban,coef_social_urban,coef_othdiscr_urban
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"# CTRAMP expression has two 'Distance' coefficients. For example, 0.2553 and 0.0100 for Escort, so used their sum here",,,,,,,,,
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Distance,"@skims[('SOV_FREE_DISTANCE', 'MD')]",coef_escort_distance,coef_escortkids_distance,coef_escortnokids_distance,coef_shopping_distance,coef_eatout_distance,coef_othmaint_distance,coef_social_distance,coef_othdiscr_distance
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Distance squared,"@(skims[('SOV_FREE_DISTANCE', 'MD')] ** 2)",coef_escort_distance_squared,coef_escortkids_distance_squared,coef_escortnokids_distance_squared,coef_shopping_distance_squared,coef_eatout_distance_squared,coef_othmaint_distance_squared,coef_social_distance_squared,coef_othdiscr_distance_squared
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Distance cubed,"@(skims[('SOV_FREE_DISTANCE', 'MD')] ** 3)",coef_escort_distance_cubed,coef_escortkids_distance_cubed,coef_escortnokids_distance_cubed,coef_shopping_distance_cubed,coef_eatout_distance_cubed,coef_othmaint_distance_cubed,coef_social_distance_cubed,coef_othdiscr_distance_cubed
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Log of distance,"@np.log(skims[('SOV_FREE_DISTANCE', 'MD')])",coef_escort_log_distance,coef_escortkids_log_distance,coef_escortnokids_log_distance,coef_shopping_log_distance,coef_eatout_log_distance,coef_othmaint_log_distance,coef_social_log_distance,coef_othdiscr_log_distance
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Distance - high income,"@((df['income_in_thousands']>50) & skims[('SOV_FREE_DISTANCE', 'MD')])",0,0,0,0,coef_eatout_distance_high_income,0,0,0
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Distance - high income,"@((df['income_in_thousands']>50) * skims[('SOV_FREE_DISTANCE', 'MD')])",0,0,0,0,coef_eatout_distance_high_income,0,0,0
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Distance - non-driving age student in hh,"@np.where(df['num_nondriving_age_children']>0, skims[('SOV_FREE_DISTANCE', 'MD')], 0)",coef_escort_distance_nondrive,coef_escortkids_distance_nondrive,coef_escortnokids_distance_nondrive,coef_shopping_distance_nondrive,0,0,coef_social_distance_nondrive,coef_othdiscr_distance_nondrive
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Distance bin 0 to 1,"@((skims[('SOV_FREE_DISTANCE', 'MD')]>=0) & (skims[('SOV_FREE_DISTANCE', 'MD')]<1))",0,0,0,coef_shopping_dist_0_1,coef_eatout_dist_0_1,coef_othmaint_dist_0_1,0,coef_othdiscr_dist_0_1
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Distance bin 1 to 2,"@((skims[('SOV_FREE_DISTANCE', 'MD')]>=1) & (skims[('SOV_FREE_DISTANCE', 'MD')]<2))",0,0,0,coef_shopping_dist_1_2,coef_eatout_dist_1_2,coef_othmaint_dist_1_2,0,coef_othdiscr_dist_1_2

‎configs/non_mandatory_tour_frequency.csv‎

Lines changed: 1 addition & 1 deletion
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@@ -139,7 +139,7 @@ util_presence_of_university_student_and_maintenance_tour,Dummy for Presence of U
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util_presence_of_driving_school_kid_and_maintenance_tour,Dummy for Presence of Driving School Kid (other than modeled person) & Maintenance tour ,has_driving_kid * othmaint,coef_presence_of_driving_school_kid_and_maintenance_tour,coef_presence_of_driving_school_kid_and_maintenance_tour,coef_presence_of_driving_school_kid_and_maintenance_tour,coef_presence_of_driving_school_kid_and_maintenance_tour,coef_presence_of_driving_school_kid_and_maintenance_tour,coef_presence_of_driving_school_kid_and_maintenance_tour,coef_presence_of_driving_school_kid_and_maintenance_tour,coef_presence_of_driving_school_kid_and_maintenance_tour
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util_presence_of_pre_driving_school_kid_and_maintenance_tour,Dummy for Presence of Pre-Driving School Kid (other than modeled person) & Maintenance tour ,has_school_kid * othmaint,coef_presence_of_pre_driving_school_kid_and_maintenance_tour,coef_presence_of_pre_driving_school_kid_and_maintenance_tour,coef_presence_of_pre_driving_school_kid_and_maintenance_tour,coef_presence_of_pre_driving_school_kid_and_maintenance_tour,coef_presence_of_pre_driving_school_kid_and_maintenance_tour,coef_presence_of_pre_driving_school_kid_and_maintenance_tour,coef_presence_of_pre_driving_school_kid_and_maintenance_tour,coef_presence_of_pre_driving_school_kid_and_maintenance_tour
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util_presence_of_pre_school_kid_and_maintenance_tour,Dummy for Presence of Pre-School Kid (other than modeled person) & Maintenance tour ,has_preschool_kid * othmaint,coef_presence_of_pre_school_kid_and_maintenance_tour,coef_presence_of_pre_school_kid_and_maintenance_tour,coef_presence_of_pre_school_kid_and_maintenance_tour,coef_presence_of_pre_school_kid_and_maintenance_tour,coef_presence_of_pre_school_kid_and_maintenance_tour,coef_presence_of_pre_school_kid_and_maintenance_tour,coef_presence_of_pre_school_kid_and_maintenance_tour,coef_presence_of_pre_school_kid_and_maintenance_tour
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util_at_home_pre_driving_school_kid_and_maintenance_tour,Dummy for At home Pre-Driving School Kid & Maintenance tour ,has_school_kid_at_home * othmaint,coef_at_home_pre_driving_school_kid_and_maintenance_tour,coef_at_home_pre_driving_school_kid_and_maintenance_tour,coef_at_home_pre_driving_school_kid_and_maintenance_tour,coef_at_home_pre_driving_school_kid_and_maintenance_tour,coef_at_home_pre_driving_school_kid_and_maintenance_tour,coef_at_home_pre_driving_school_kid_and_maintenance_tour,coef_at_home_pre_driving_school_kid_and_maintenance_tour,coef_at_home_pre_driving_school_kid_and_maintenance_tour
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util_at_home_pre_driving_school_kid_and_maintenance_tour,Dummy for At home Pre-Driving School Kid & Maintenance tour ,df.has_school_kid_at_home * df.othmaint,coef_at_home_pre_driving_school_kid_and_maintenance_tour,coef_at_home_pre_driving_school_kid_and_maintenance_tour,coef_at_home_pre_driving_school_kid_and_maintenance_tour,coef_at_home_pre_driving_school_kid_and_maintenance_tour,coef_at_home_pre_driving_school_kid_and_maintenance_tour,coef_at_home_pre_driving_school_kid_and_maintenance_tour,coef_at_home_pre_driving_school_kid_and_maintenance_tour,coef_at_home_pre_driving_school_kid_and_maintenance_tour
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util_at_home_pre_school_kid_and_maintenance_tour,Dummy for At homef Pre-School Kid & Maintenance tour ,has_preschool_kid_at_home * othmaint,coef_at_home_pre_school_kid_and_maintenance_tour,coef_at_home_pre_school_kid_and_maintenance_tour,coef_at_home_pre_school_kid_and_maintenance_tour,coef_at_home_pre_school_kid_and_maintenance_tour,coef_at_home_pre_school_kid_and_maintenance_tour,coef_at_home_pre_school_kid_and_maintenance_tour,coef_at_home_pre_school_kid_and_maintenance_tour,coef_at_home_pre_school_kid_and_maintenance_tour
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util_presence_of_full_time_worker_and_eating_out_tour,Dummy for Presence of Full time Worker (other than modeled person) & Eating Out tour ,has_full_time * eatout,coef_presence_of_full_time_worker_and_eating_out_tour,coef_presence_of_full_time_worker_and_eating_out_tour,coef_presence_of_full_time_worker_and_eating_out_tour,coef_presence_of_full_time_worker_and_eating_out_tour,coef_presence_of_full_time_worker_and_eating_out_tour,coef_presence_of_full_time_worker_and_eating_out_tour,coef_presence_of_full_time_worker_and_eating_out_tour,coef_presence_of_full_time_worker_and_eating_out_tour
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util_presence_of_part_time_worker_and_eating_out_tour,Dummy for Presence of Part time Worker (other than modeled person) & Eating Out tour ,has_part_time * eatout,coef_presence_of_part_time_worker_and_eating_out_tour,coef_presence_of_part_time_worker_and_eating_out_tour,coef_presence_of_part_time_worker_and_eating_out_tour,coef_presence_of_part_time_worker_and_eating_out_tour,coef_presence_of_part_time_worker_and_eating_out_tour,coef_presence_of_part_time_worker_and_eating_out_tour,coef_presence_of_part_time_worker_and_eating_out_tour,coef_presence_of_part_time_worker_and_eating_out_tour

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