ABM3 Intra-Household AV Allocation and Taxi/TNC Routing Models

src/asim/configs/common/constants.yaml

@@ -89,6 +89,9 @@ autoParkingCostFactorAV: {policy-AV-autoParkingCostFactor:}
 autoCostPerMileFactorAV: {policy-AV-autoCostPerMileFactor:}
 autoTerminalTimeFactorAV: {policy-AV-autoTerminalTimeFactor:}
 minAgeDriveAloneAV: {policy-AV-minAgeDriveAlone:}
+AV_maxDuration: 1.5 # max duration for keeping car close (hrs)
+AV_maxBenefit: 60 # max benefit for keeping car close (mins)
+RemoteParkingCostPerHour: 3  #dollar
 
 
 #valueOfTime: 8.00

src/asim/configs/resident/av_repositioning.csv

@@ -0,0 +1,31 @@
+Label,Description,Expression,stay_with_person,go_to_parking,go_home,service_next_trip_1,service_next_trip_2,service_next_trip_3
+# stay with person utils,,,,,,,,
+util_cost_of_parking,Cost of parking at destination,parkingCost,coef_cost,,,,,
+util_time_stay,Stay- Need car soon,"@np.where(df.duration_hrs < df.AV_maxDuration, (-1)*(df.AV_maxBenefit + (df.duration_hrs*df.slope)), 0)",coef_ivt,,,,,
+# go to parking utils,,,,,,,,
+util_remote_park_only_if_park_const,Can only use remote parking if in parking constrained zone,~parkingConstrained,,coef_unavailable,,,,
+util_time_go_to_parking,Remote- Need car soon,"@np.where(df.duration_hrs < df.AV_maxDuration, (-1)*(df.AV_maxBenefit + (df.duration_hrs*df.slope)), 0)",,coef_ivt,,,,
+util_remote_cost,Remote park - Cost of parking until departure,duration_hrs * RemoteParkingCostPerHour * 100,,coef_cost,,,,
+util_remote_ivt,in vehicle time to remote parking location,@v_to_parking_skim['SOV_TR_H_TIME'],,coef_ivt,,,,
+util_remote_rel,reliability vehicle location to remote parking location,"@v_to_parking_skim['SOV_TR_H_REL'] * 14 / np.maximum(0.1, v_to_parking_skim['SOV_TR_H_DIST'])",,coef_ivt,,,,
+util_remote_auto_cost,auto operating cost from vehicle location to remote parking location,@(v_to_parking_skim['SOV_TR_H_DIST'] * costPerMile * autoCostPerMileFactorAV) + v_to_parking_skim['SOV_TR_H_TOLLCOST'],,coef_cost,,,,
+# go home utils,,,,,,,,
+util_already_at_home,Unavailable if already at home destination,destination == home_zone_id,,,coef_unavailable,,,
+util_home_ivt,in vehicle time to go home,@v_to_home_skim['SOV_TR_H_TIME'],,,coef_ivt,,,
+util_home_rel,reliability vehicle location to home,"@v_to_home_skim['SOV_TR_H_REL'] * 14 / np.maximum(0.1, v_to_home_skim['SOV_TR_H_DIST'])",,,coef_ivt,,,
+util_home_auto_cost,auto operating cost from vehicle location to home,@(v_to_home_skim['SOV_TR_H_DIST'] * costPerMile * autoCostPerMileFactorAV) + v_to_home_skim['SOV_TR_H_TOLLCOST'],,,coef_cost,,,
+# service next trip util 1,,,,,,,,
+util_next_trip_available,Unavailable if no next trip,next_trip_id_1 == -1,,,,coef_unavailable,,
+util_next1_ivt,in vehicle time to next trip 1 origin,v_to_trip_orig1_time,,,,coef_ivt,,
+util_next1_rel,reliability vehicle location to next trip 1 origin,"@df.v_to_trip_orig1_rel * 14 / np.maximum(0.1, df.v_to_trip_orig1_dist)",,,,coef_ivt,,
+util_next1_auto_cost,auto operating cost from vehicle location to next trip 1 origin,@(df.v_to_trip_orig1_dist * costPerMile * autoCostPerMileFactorAV) + df.v_to_trip_orig1_toll,,,,coef_cost,,
+# service next trip util 2,,,,,,,,
+util_next_trip_available,Unavailable if no next trip,next_trip_id_2 == -1,,,,,coef_unavailable,
+util_next2_ivt,in vehicle time to next trip 2 origin,v_to_trip_orig2_time,,,,,coef_ivt,
+util_next2_rel,reliability vehicle location to next trip 2 origin,"@df.v_to_trip_orig2_rel * 14 / np.maximum(0.2, df.v_to_trip_orig2_dist)",,,,,coef_ivt,
+util_next2_auto_cost,auto operating cost from vehicle location to next trip 2 origin,@(df.v_to_trip_orig2_dist * costPerMile * autoCostPerMileFactorAV) + df.v_to_trip_orig2_toll,,,,,coef_cost,
+# service next trip util 3,,,,,,,,
+util_next_trip_available_3,Unavailable if no next trip 3,next_trip_id_3 == -1,,,,,,coef_unavailable
+util_next3_ivt,in vehicle time to next trip 3 origin,v_to_trip_orig3_time,,,,,,coef_ivt
+util_next3_rel,reliability vehicle location to next trip 3 origin,"@df.v_to_trip_orig3_rel * 14 / np.maximum(0.3, df.v_to_trip_orig3_dist)",,,,,,coef_ivt
+util_next3_auto_cost,auto operating cost from vehicle location to next trip 3 origin,@(df.v_to_trip_orig3_dist * costPerMile * autoCostPerMileFactorAV) + df.v_to_trip_orig3_toll,,,,,,coef_cost

src/asim/configs/resident/av_repositioning_coefficients.csv

@@ -0,0 +1,4 @@
+coefficient_name,value,constrain
+coef_unavailable,-999.0,F
+coef_ivt,-0.03,F
+coef_cost,-0.002,F

src/asim/configs/resident/av_repositioning_preprocessor.csv

@@ -0,0 +1,50 @@
+Description,Target,Expression
+next trip start time,next_depart,df['trip_id'].map(trips.groupby('tour_id')['depart'].shift(-1).to_dict())
+trip duration,duration_hrs,"np.where(next_depart.isna(), 0, next_depart - df.depart) / 2"
+duration benefit,duration_benefit,"np.where((duration_hrs < 1.5) & (duration_hrs > 0), 60 - (60/1.5 * duration_hrs), 0)"
+#Parking cost calculation,,
+,tour_id,"reindex(trips.tour_id, df.trip_id)"
+,tour_type,"reindex(tours.tour_type, tour_id)"
+,person_id,"reindex(trips.person_id, df.trip_id)"
+,ptype,"reindex(persons.ptype, person_id)"
+,free_parking_at_work,"reindex(persons.free_parking_at_work,  person_id)"
+,free_parking_available,(tour_type == 'work') & free_parking_at_work
+,number_of_participants,"reindex(tours.number_of_participants, tour_id)"
+,is_indiv,(number_of_participants == 1)
+person has free on-site parking at workplace,freeOnsite,"(free_parking_available)*np.where(is_indiv,1,0)"
+new reimbursement amount,reimburseProportion,0
+new daily parking cost with reimbursement,parkingCostDayDollars,"reindex(land_use.exp_daily, df.destination)"
+new hourly parking cost with reimbursement,parkingCostHourDollars,"reindex(land_use.exp_hourly, df.destination)"
+new monthly parking cost with reimbursement,parkingCostMonthDollars,"reindex(land_use.exp_monthly, df.destination)"
+daily cost converted to cents,parkingCostDay,parkingCostDayDollars*100
+hourly cost converted to cents,parkingCostHour,parkingCostHourDollars*100
+monthly cost converted to cents,parkingCostMonth,parkingCostMonthDollars*100
+Trip parking cost for full-time workers and university students,_parkingCostBeforeReimb,"ptype.isin([1,3]).values * is_indiv * np.minimum(parkingCostMonth/22, parkingCostDay)"
+Trip parking cost for full-time workers and university students,_parkingCostBeforeReimb,"ptype.isin([1,3]).values * is_indiv * np.minimum(_parkingCostBeforeReimb, parkingCostHour * duration_hrs)"
+,is_joint,(number_of_participants > 1)
+Trip parking cost for other person types,parkingCostBeforeReimb,"np.where((~ptype.isin([1,3]).values * is_indiv) | (is_joint), np.minimum(parkingCostDay, parkingCostHour * duration_hrs), _parkingCostBeforeReimb)"
+Reimbursement applies to this tour purpose,reimbursePurpose,tour_type=='work'
+Effective parking cost for free parkers,_parkingCost,"0 * np.where(reimbursePurpose*freeOnsite,1,0)"
+Effective parking cost for reimbursed parkers,_parkingCost,"np.where(is_indiv*reimbursePurpose*(1-freeOnsite), np.maximum((1-reimburseProportion) * parkingCostBeforeReimb, 0),_parkingCost)"
+Effective parking cost,parkingCost,"np.where(is_joint+is_indiv*(1-reimbursePurpose), parkingCostBeforeReimb,_parkingCost)"
+Parking cost is 0 if going home,parkingCost,"np.where(df.destination == df.home_zone_id, 0, parkingCost)"
+# These following two are from AutonomousVehicleAllocationChoice.xls,,
+Maximim benefit for keeping car close (min),AV_maxBenefit,60
+Maximum duration for keeping car close (hrs),AV_maxDuration,1.5
+Slope of benefit calculation,slope, (-1)*(AV_maxBenefit / AV_maxDuration)
+# below taken from parametersByYear.csv,,
+,RemoteParkingCostPerHour,0.81
+#,,
+,parkingConstrained,"reindex(land_use.parking_type,df.destination)==1"
+,v_to_trip_orig1_time,"np.where(df.next_trip_id_1 > 0, v_to_trip_orig1_skim['SOV_TR_H_TIME'], 0)"
+,v_to_trip_orig2_time,"np.where(df.next_trip_id_2 > 0, v_to_trip_orig2_skim['SOV_TR_H_TIME'], 0)"
+,v_to_trip_orig3_time,"np.where(df.next_trip_id_3 > 0, v_to_trip_orig3_skim['SOV_TR_H_TIME'], 0)"
+,v_to_trip_orig1_dist,"np.where(df.next_trip_id_1 > 0, v_to_trip_orig1_skim['SOV_TR_H_DIST'], 0)"
+,v_to_trip_orig2_dist,"np.where(df.next_trip_id_2 > 0, v_to_trip_orig2_skim['SOV_TR_H_DIST'], 0)"
+,v_to_trip_orig3_dist,"np.where(df.next_trip_id_3 > 0, v_to_trip_orig3_skim['SOV_TR_H_DIST'], 0)"
+,v_to_trip_orig1_rel,"np.where(df.next_trip_id_1 > 0, v_to_trip_orig1_skim['SOV_TR_H_REL'], 0)"
+,v_to_trip_orig2_rel,"np.where(df.next_trip_id_2 > 0, v_to_trip_orig2_skim['SOV_TR_H_REL'], 0)"
+,v_to_trip_orig3_rel,"np.where(df.next_trip_id_3 > 0, v_to_trip_orig3_skim['SOV_TR_H_REL'], 0)"
+,v_to_trip_orig1_toll,"np.where(df.next_trip_id_1 > 0, v_to_trip_orig1_skim['SOV_TR_H_TOLLCOST'], 0)"
+,v_to_trip_orig2_toll,"np.where(df.next_trip_id_2 > 0, v_to_trip_orig2_skim['SOV_TR_H_TOLLCOST'], 0)"
+,v_to_trip_orig3_toll,"np.where(df.next_trip_id_3 > 0, v_to_trip_orig3_skim['SOV_TR_H_TOLLCOST'], 0)"

src/asim/configs/resident/av_routing.yaml

@@ -0,0 +1,37 @@
+# spec and coefficients for AV trip matching model
+AV_TRIP_MATCHING_SPEC: av_trip_matching.csv
+AV_TRIP_MATCHING_COEFFICIENTS: av_trip_matching_coefficients.csv
+
+# spec and coefficients for AV repositioning model
+AV_REPOSITIONING_SPEC: av_repositioning.csv
+AV_REPOSITIONING_COEFFICIENTS: av_repositioning_coefficients.csv
+
+# needed to pass logit settings validation, but not used in this model
+SPEC: None
+
+# Column in landuse DataFrame that indicates if a zone has AV parking available
+AV_PARKING_ZONE_COLUMN: remoteAVParking
+
+# Skim core for nearest parking zone calculations
+NEAREST_ZONE_SKIM: DIST
+
+# List of modes that are eligible for routing with a household AV
+DRIVING_MODES: 
+  - DRIVEALONE
+  - SHARED2
+  - SHARED3
+
+av_trip_matching_preprocessor:
+  SPEC: av_trip_matching_preprocessor.csv
+  DF: df
+  TABLES:
+    - trips
+
+av_repositioning_preprocessor:
+  SPEC: av_repositioning_preprocessor.csv
+  DF: df
+  TABLES:
+    - trips
+    - land_use
+    - tours
+    - persons

src/asim/configs/resident/av_trip_matching.csv

@@ -0,0 +1,9 @@
+Label,Description,Expression,coefficient
+util_veh_to_trip_origin_time,Time veh to trip origin,"@np.where((df.veh_location == df.origin) | (df.veh_location < 0) | (df.origin < 0), 0, veho_tripo_t_skims['SOV_TR_L_TIME'])",coef_ivt
+util_veh_to_trip_origin_cost,cost veh to trip origin,"@np.where((df.veh_location == df.origin) | (df.veh_location < 0) | (df.origin < 0), 0, (df.auto_operating_cost * veho_tripo_t_skims['SOV_TR_L_DIST']) + veho_tripo_t_skims['SOV_TR_L_TOLLCOST'])",coef_cost
+# *14 multiplier to convert from ivt to reliability as used in abm2+ uec,,,
+util_veh_to_trip_origin_reliability,reliability veh to trip origin,"@np.where((df.veh_location == df.origin) | (df.veh_location < 0) | (df.origin < 0), 0, veho_tripo_t_skims['SOV_NT_L_REL']) * 14",coef_ivt
+util_trip_duration,Trip duration,df.duration_benefit,coef_ivt
+util_no_vehicle,Alternative unavailable if no vehicle,df.vehicle_id.isna() & (df.trip_number > 0),coef_unavailable
+util_no_trip,unavailable if no trip and alt is not idle,df.trip_id.isna() & (df.trip_number > 0),coef_unavailable
+util_idle,Do not service any trips,(df.trip_number == 0) & ~df.vehicle_id.isna(),coef_idle

src/asim/configs/resident/av_trip_matching_coefficients.csv

@@ -0,0 +1,6 @@
+coefficient_name,value,constrain
+coef_unavailable,-999.0,F
+coef_one,1.0,F
+coef_idle,-10.0,F
+coef_ivt,-0.03,F
+coef_cost,-0.002,F

src/asim/configs/resident/av_trip_matching_preprocessor.csv

@@ -0,0 +1,4 @@
+Description,Target,Expression
+next trip start time,next_depart,df['trip_id'].map(trips.groupby('tour_id')['depart'].shift(-1).to_dict())
+trip duration,duration_hrs,"np.where(next_depart.isna(), 0, next_depart - df.depart) * 2"
+duration benefit,duration_benefit,"np.where((duration_hrs < 1.5) & (duration_hrs > 0), 60 - (60/1.5 * duration_hrs), 0)"

src/asim/extensions/__init__.py

@@ -1,4 +1,5 @@
 from . import av_ownership
+from . import av_routing
 from . import external_identification
 from . import external_location_choice
 from . import transponder_ownership