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Fix TNC fare error
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@aber-sandag
aber-sandag committed May 6, 2024
1 parent bb54188 commit e013c07
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Showing 2 changed files with 9 additions and 9 deletions.
6 changes: 3 additions & 3 deletions src/asim/configs/resident/tour_mode_choice.csv
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Original file line number Diff line number Diff line change
Expand Up @@ -278,7 +278,7 @@ util_TNC_LOC_transfer_wait_time,TNC_LOC - transfer wait time,@(odt_skims['TNCOUT
util_TNC_LOC_number_of_transfers,TNC_LOC - number of transfers,"@(-23+23*np.exp(0.414*np.clip(odt_skims['TNCOUT_LOC_XFERS'] + df.mtnev_acc_xfer + df.mtnev_egr_xfer, a_min=None,a_max=4))) + (-23+23*np.exp(0.414*np.clip(dot_skims['TNCIN_MIX_XFERS'] + df.mtnev_acc_xfer + df.mtnev_egr_xfer, a_min=None,a_max=4))) *df.time_factor",,,,,,,,,,,,,,,coef_xferdrive,,,,,,,,
util_TNC_LOC_TNC_time,TNC_LOC - TNC time,"@np.where(df.nev_local_access_available, df.nev_local_access_time, np.where(df.microtransit_local_access_available, df.microtransit_local_access_time, odt_skims['TNCOUT_LOC_ACC'] + dot_skims['TNCIN_LOC_EGR'])) *df.time_factor",,,,,,,,,,,,,,,coef_acctime,,,,,,,,
util_TNC_LOC_TNC_wait_time,TNC_LOC - TNC wait time,"@np.where(df.nev_local_access_available, 2*nevWaitTime, np.where(df.microtransit_local_access_available, 2*microtransitWaitTime, 2*df.origSingleTNCWaitTime)) *df.time_factor",,,,,,,,,,,,,,,coef_wait,,,,,,,,
util_TNC_LOC_TNC_fare,TNC_LOC - TNC fare,"(~df.nev_local_access_available) * (~df.microtransit_local_access_available) * ((np.maximum(TNC_single_baseFare*2 + ((odt_skims['TNCOUT_LOC_ACC'] + dot_skims['TNCIN_LOC_EGR'])/60 * driveSpeed) * TNC_single_costPerMile + (odt_skims['TNCOUT_LOC_ACC'] + dot_skims['TNCIN_LOC_EGR']) * TNC_single_costPerMinute, TNC_single_costMinimum*2)*100)/df.cost_sensitivity)",,,,,,,,,,,,,,,coef_income,,,,,,,,
util_TNC_LOC_TNC_fare,TNC_LOC - TNC fare,"@(~df.nev_local_access_available) * (~df.microtransit_local_access_available) * ((np.maximum(TNC_single_baseFare*2 + ((odt_skims['TNCOUT_LOC_ACC'] + dot_skims['TNCIN_LOC_EGR'])/60 * driveSpeed) * TNC_single_costPerMile + (odt_skims['TNCOUT_LOC_ACC'] + dot_skims['TNCIN_LOC_EGR']) * TNC_single_costPerMinute, TNC_single_costMinimum*2)*100)/df.cost_sensitivity)",,,,,,,,,,,,,,,coef_income,,,,,,,,
util_TNC_LOC_Walk_egress_time_(at_attraction_end),TNC_LOC - Walk egress time (at attraction end),"@np.where(df.nev_local_egress_available, df.nev_local_egress_time, np.where(df.microtransit_local_egress_available, df.microtransit_local_egress_time, 2*df.dest_local_time)) * df.time_factor",,,,,,,,,,,,,,,coef_acctime,,,,,,,,
util_TNC_LOC_wait_egress_time_(at_attraction_end),TNC_LOC - Egress mt/nev wait time (at attraction end),"@np.where(df.nev_local_egress_available, 2*nevWaitTime, np.where(df.microtransit_local_egress_available, 2*microtransitWaitTime, 0)) * df.time_factor",,,,,,,,,,,,,,,coef_wait,,,,,,,,
util_TNC_LOC_Walk_other_time,TNC_LOC - Walk other time,@(odt_skims['TNCOUT_LOC_XFERWALK'] + dot_skims['TNCIN_LOC_XFERWALK']) *df.time_factor,,,,,,,,,,,,,,,coef_xwalk,,,,,,,,
Expand All @@ -302,7 +302,7 @@ util_TNC_PRM_transfer_wait_time,TNC_PRM - transfer wait time,@(odt_skims['TNCOUT
util_TNC_PRM_number_of_transfers,TNC_PRM - number of transfers,"@(-23+23*np.exp(0.414*np.clip(odt_skims['TNCOUT_PRM_XFERS'] + df.mtnev_acc_xfer + df.mtnev_egr_xfer, a_min=None,a_max=4))) + (-23+23*np.exp(0.414*np.clip(dot_skims['TNCIN_PRM_XFERS'] + df.mtnev_acc_xfer + df.mtnev_egr_xfer, a_min=None,a_max=4))) *df.time_factor",,,,,,,,,,,,,,,,coef_xferdrive,,,,,,,
util_TNC_PRM_TNC_time,TNC_PRM - TNC time,"@np.where(df.nev_prm_access_available, df.nev_prm_access_time, np.where(df.microtransit_prm_access_available, df.microtransit_prm_access_time, odt_skims['TNCOUT_PRM_ACC'] + dot_skims['TNCIN_PRM_EGR'])) *df.time_factor",,,,,,,,,,,,,,,,coef_acctime,,,,,,,
util_TNC_PRM_TNC_wait_time,TNC_PRM - TNC wait time,"@np.where(df.nev_prm_access_available, 2*nevWaitTime, np.where(df.microtransit_prm_access_available, 2*microtransitWaitTime, 2*df.origSingleTNCWaitTime)) *df.time_factor",,,,,,,,,,,,,,,,coef_wait,,,,,,,
util_TNC_PRM_TNC_fare,TNC_PRM - TNC fare,"(~df.nev_prm_access_available) * (~df.microtransit_prm_access_available) * ((np.maximum(TNC_single_baseFare*2 + ((odt_skims['TNCOUT_PRM_ACC'] + dot_skims['TNCIN_PRM_EGR'])/60 * driveSpeed) * TNC_single_costPerMile + (odt_skims['TNCOUT_PRM_ACC'] + dot_skims['TNCIN_PRM_EGR']) * TNC_single_costPerMinute, TNC_single_costMinimum*2)*100)/df.cost_sensitivity)",,,,,,,,,,,,,,,,coef_income,,,,,,,
util_TNC_PRM_TNC_fare,TNC_PRM - TNC fare,"@(~df.nev_prm_access_available) * (~df.microtransit_prm_access_available) * ((np.maximum(TNC_single_baseFare*2 + ((odt_skims['TNCOUT_PRM_ACC'] + dot_skims['TNCIN_PRM_EGR'])/60 * driveSpeed) * TNC_single_costPerMile + (odt_skims['TNCOUT_PRM_ACC'] + dot_skims['TNCIN_PRM_EGR']) * TNC_single_costPerMinute, TNC_single_costMinimum*2)*100)/df.cost_sensitivity)",,,,,,,,,,,,,,,,coef_income,,,,,,,
util_TNC_PRM_Walk_egress_time_(at_attraction_end),TNC_PRM - Walk egress time (at attraction end),"@np.where(df.nev_prm_egress_available, df.nev_prm_egress_time, np.where(df.microtransit_prm_egress_available, df.microtransit_prm_egress_time, 2*df.dest_prm_time)) * df.time_factor",,,,,,,,,,,,,,,,coef_acctime,,,,,,,
util_TNC_PRM_wait_egress_time_(at_attraction_end),TNC_PRM - Egress mt/nev wait time (at attraction end),"@np.where(df.nev_prm_egress_available, 2*nevWaitTime, np.where(df.microtransit_prm_egress_available, 2*microtransitWaitTime, 0)) * df.time_factor",,,,,,,,,,,,,,,,coef_wait,,,,,,,
util_TNC_PRM_Walk_other_time,TNC_PRM - Walk other time,@ (odt_skims['TNCOUT_PRM_XFERWALK'] + dot_skims['TNCIN_PRM_XFERWALK']) *df.time_factor,,,,,,,,,,,,,,,,coef_xwalk,,,,,,,
Expand All @@ -327,7 +327,7 @@ util_TNC_MIX_transfer_wait_time,TNC_MIX - transfer wait time,@(odt_skims['TNCOUT
util_TNC_MIX_number_of_transfers,TNC_MIX - number of transfers,"@(-23+23*np.exp(0.414*np.clip(odt_skims['TNCOUT_MIX_XFERS'] + df.mtnev_acc_xfer + df.mtnev_egr_xfer, a_min=None,a_max=4))) + (-23+23*np.exp(0.414*np.clip(dot_skims['TNCIN_MIX_XFERS'] + df.mtnev_acc_xfer + df.mtnev_egr_xfer, a_min=None,a_max=4))) *df.time_factor",,,,,,,,,,,,,,,,,coef_xferdrive,,,,,,
util_TNC_MIX_TNC_time,TNC_MIX - TNC time,"@np.where(df.nev_mix_access_available, df.nev_mix_access_time, np.where(df.microtransit_mix_access_available, df.microtransit_mix_access_time, odt_skims['TNCOUT_MIX_ACC'] + dot_skims['TNCIN_MIX_EGR'])) *df.time_factor",,,,,,,,,,,,,,,,,coef_acctime,,,,,,
util_TNC_MIX_TNC_wait_time,TNC_MIX - TNC wait time,"@np.where(df.nev_mix_access_available, 2*nevWaitTime, np.where(df.microtransit_mix_access_available, 2*microtransitWaitTime, 2*df.origSingleTNCWaitTime)) *df.time_factor",,,,,,,,,,,,,,,,,coef_wait,,,,,,
util_TNC_MIX_TNC_fare,TNC_MIX - TNC fare,"(~df.nev_mix_access_available) * (~df.microtransit_mix_access_available) * ((np.maximum(TNC_single_baseFare*2 + ((odt_skims['TNCOUT_MIX_ACC'] + dot_skims['TNCIN_MIX_EGR'])/60 * driveSpeed) * TNC_single_costPerMile + (odt_skims['TNCOUT_MIX_ACC'] + dot_skims['TNCIN_MIX_EGR']) * TNC_single_costPerMinute, TNC_single_costMinimum*2)*100)/df.cost_sensitivity)",,,,,,,,,,,,,,,,,coef_income,,,,,,
util_TNC_MIX_TNC_fare,TNC_MIX - TNC fare,"@(~df.nev_mix_access_available) * (~df.microtransit_mix_access_available) * ((np.maximum(TNC_single_baseFare*2 + ((odt_skims['TNCOUT_MIX_ACC'] + dot_skims['TNCIN_MIX_EGR'])/60 * driveSpeed) * TNC_single_costPerMile + (odt_skims['TNCOUT_MIX_ACC'] + dot_skims['TNCIN_MIX_EGR']) * TNC_single_costPerMinute, TNC_single_costMinimum*2)*100)/df.cost_sensitivity)",,,,,,,,,,,,,,,,,coef_income,,,,,,
util_TNC_MIX_Walk_egress_time_(at_attraction_end),TNC_MIX - Walk egress time (at attraction end),"@np.where(df.nev_mix_egress_available, df.nev_mix_egress_time, np.where(df.microtransit_mix_egress_available, df.microtransit_mix_egress_time, 2*df.dest_mix_time)) * df.time_factor",,,,,,,,,,,,,,,,,coef_acctime,,,,,,
util_TNC_MIX_wait_egress_time_(at_attraction_end),TNC_MIX - Egress mt/nev wait time (at attraction end),"@np.where(df.nev_mix_egress_available, 2*nevWaitTime, np.where(df.microtransit_mix_egress_available, 2*microtransitWaitTime, 0)) * df.time_factor",,,,,,,,,,,,,,,,,coef_wait,,,,,,
util_TNC_MIX_Walk_other_time,TNC_MIX - Walk other time,@(odt_skims['TNCOUT_MIX_XFERWALK'] + dot_skims['TNCIN_MIX_XFERWALK']) *df.time_factor,,,,,,,,,,,,,,,,,coef_xwalk,,,,,,
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