Route choice with fixed time and cost
Posted: Wed Feb 22, 2023 12:17 amHi Prof,
I am new to choice modeling, and currently trying to design a labeled experiment for calculating WTP values for different charging infrastructures as well as preferences.
The alternatives are Routes with Level 2, Routes with Level 3 charging, and dynamic wireless charging. I am trying to design two experiments according to length of the route 100 mi vs 30 mi and scenarios varying ACC. to EV's initial state of charging, say 80%, 50% and 30%.
For 100 miles,
The attributes are:
SOC(80%,50%,30%)- The time and cost vary according to initial SOC level, so I haven't specified them in the utilities. Should I add them?
1. Charging Time : (Fixed for the length for each alternative, and for each SOC)
2. Charging Cost: (Fixed for each alternative)
3. Coverage of charging stations: (25%,50%,75%) as of conventional gas stations
4. Serving speed: 5,15,30 minutes (Time to wait for charging)
5. Presence of restrooms and convenience store: Dummy variable (0/1)
6. Presence of entertainment options: Dummy variable (0/1)
My current design looks like this (for 100 mi)
design
;alts = level2, level3, dwpt
;eff=(mnl,d)
;rows=12
; cond:
if(level2.TT=240, level3.TT3=15 AND level2.C=1 AND level3.C3=1.5 AND dwpt.Cd=2),
if(level2.TT=300, level3.TT3=20 AND level2.C=2 AND level3.C3=2.5 AND dwpt.Cd=3),
if(level2.TT=400, level3.TT3=30 AND level2.c=3 AND level3.C3=3.5 AND dwpt.Cd=4)
;model:
U(level2)= b2*TT[240,300,400]+b3*C[1,2,3] + b4*Density[25,50,75] + b5*Servsp[5,15,30] + b6*RP[0,1] + b7*S[0,1] /
U(level3)= c1+ b2*TT3[15,20,30]+b3*C3[1.5,2.5,3.5] + b4*Density[25,50,75] + b5*Servsp[5,15,30] + b6*RP[0,1] + b7*S[0,1] /
U(dwpt)= c2 +b3*Cd[2,3,4] + b4*Density[25,50,75] + b5*Servsp[5,15,30] + b6*RP[0,1] + b7*S[0,1]
$
However, NGENE returns the following error: No valid design has been found after 1000 evaluations. There may be a problem with the specification of the design. A common problem is that the choice probabilities are too extreme (close to 1 and 0), perhaps because some or all of the prior values are too large......
My few questions are:
1. There are too many constraints because for each scenario the time and cost for each alternative are fixed, is there a way to relax these constraints? Also, is there a way we can vary the time and cost within the alternatives so that we can get WTP values for each alternative, rather than a generic one which we will get according to my specification?
2. Is the design code feasible?
Best,
I am new to choice modeling, and currently trying to design a labeled experiment for calculating WTP values for different charging infrastructures as well as preferences.
The alternatives are Routes with Level 2, Routes with Level 3 charging, and dynamic wireless charging. I am trying to design two experiments according to length of the route 100 mi vs 30 mi and scenarios varying ACC. to EV's initial state of charging, say 80%, 50% and 30%.
For 100 miles,
The attributes are:
SOC(80%,50%,30%)- The time and cost vary according to initial SOC level, so I haven't specified them in the utilities. Should I add them?
1. Charging Time : (Fixed for the length for each alternative, and for each SOC)
2. Charging Cost: (Fixed for each alternative)
3. Coverage of charging stations: (25%,50%,75%) as of conventional gas stations
4. Serving speed: 5,15,30 minutes (Time to wait for charging)
5. Presence of restrooms and convenience store: Dummy variable (0/1)
6. Presence of entertainment options: Dummy variable (0/1)
My current design looks like this (for 100 mi)
design
;alts = level2, level3, dwpt
;eff=(mnl,d)
;rows=12
; cond:
if(level2.TT=240, level3.TT3=15 AND level2.C=1 AND level3.C3=1.5 AND dwpt.Cd=2),
if(level2.TT=300, level3.TT3=20 AND level2.C=2 AND level3.C3=2.5 AND dwpt.Cd=3),
if(level2.TT=400, level3.TT3=30 AND level2.c=3 AND level3.C3=3.5 AND dwpt.Cd=4)
;model:
U(level2)= b2*TT[240,300,400]+b3*C[1,2,3] + b4*Density[25,50,75] + b5*Servsp[5,15,30] + b6*RP[0,1] + b7*S[0,1] /
U(level3)= c1+ b2*TT3[15,20,30]+b3*C3[1.5,2.5,3.5] + b4*Density[25,50,75] + b5*Servsp[5,15,30] + b6*RP[0,1] + b7*S[0,1] /
U(dwpt)= c2 +b3*Cd[2,3,4] + b4*Density[25,50,75] + b5*Servsp[5,15,30] + b6*RP[0,1] + b7*S[0,1]
$
However, NGENE returns the following error: No valid design has been found after 1000 evaluations. There may be a problem with the specification of the design. A common problem is that the choice probabilities are too extreme (close to 1 and 0), perhaps because some or all of the prior values are too large......
My few questions are:
1. There are too many constraints because for each scenario the time and cost for each alternative are fixed, is there a way to relax these constraints? Also, is there a way we can vary the time and cost within the alternatives so that we can get WTP values for each alternative, rather than a generic one which we will get according to my specification?
2. Is the design code feasible?
Best,