Abstract representation of an individual that makes one trip per day.
{
"id": 1,
"mode_choice": {
"type": "Logit",
"value": {
"mu": 2.0,
"u": 0.5
}
},
"modes": [
{
"type": "Constant",
"value": 1.0
},
{
"type": "Road",
"value": {
"departure_time_model": {
"type": "ContinuousChoice",
"value": {
"choice_model": {
"type": "Logit",
"value": {
"mu": 4.0,
"u": 0.5
}
},
"period": [
0.0,
86400.0
]
}
},
"destination": 1,
"origin": 0,
"utility_model": {
"type": "Proportional",
"value": -10.0
},
"vehicle": 0
}
}
],
"schedule_utility": {
"type": "AlphaBetaGamma",
"value": {
"beta": 5.0,
"desired_arrival": true,
"gamma": 20.0,
"t_star_high": 31350.0,
"t_star_low": 27900.0
}
}
}
Id used when writing the results of the agents.
Value must be greater or equal to 0.0
Choice model used for mode choice.
When not specified, the first mode is always chosen.
Choose the alternative with the largest utility.
Choose the alternative with the largest value.
Uniform random number between 0.0 and 1.0 to choose the alternative in case of tie.
Value must be greater or equal to 0.0 and lesser or equal to 1.0
Choose the alternative using Logit probabilities.
A discrete or continuous Logit model
Variance of the error terms, must be positive.
Value must be greater or equal to 0.0001
Uniform random number between 0.0 and 1.0 for inversion sampling.
Value must be greater or equal to 0.0 and lesser or equal to 1.0
{
"type": "Deterministic",
"value": {
"u": 0.5
}
}
Modes accessible to the agent.
Must contain a minimum of 1 items
Mode of transportation available to an agent.
A mode of transportation that always provide the same utility level.
Representation of a utility (or monetary) amount.
A trip with a vehicle on the road network, with potential congestion.
Mode of transportation for a vehicle that travels on the road network.
{
"departure_time_model": {
"type": "ContinuousChoice",
"value": {
"choice_model": {
"type": "Logit",
"value": {
"mu": 4.0,
"u": 0.5
}
},
"period": [
0.0,
86400.0
]
}
},
"destination": 1,
"origin": 0,
"utility_model": {
"type": "Proportional",
"value": -10.0
},
"vehicle": 0
}
Model used for the departure-time choice.
The departure time is always equal to the given value.
Representation of time duration or timestamp, expressed in seconds.
The departure time is chosen according to a continuous choice model.
Continuous choice model.
A discrete or continuous Logit model
Variance of the error terms, must be positive.
Value must be greater or equal to 0.0001
Uniform random number between 0.0 and 1.0 for inversion sampling.
Value must be greater or equal to 0.0 and lesser or equal to 1.0
Interval in which the departure time is chosen.
Must contain a minimum of 2 items
Must contain a maximum of 2 items
Representation of time duration or timestamp, expressed in seconds.
Id of the destination node on the road network graph.
Value must be greater or equal to 0.0
Id of the origin node on the road network graph.
Value must be greater or equal to 0.0
Travel-utility model describing how travel utility is computed.
Travel utility is always null.
Travel utility is proportional to the travel time.
Representation of a value of time, i.e., a utility amount per time unit, expressed in utility unit per second.
Travel utility is a quadratic function of travel time: u = a * tt + b * tt^2.
First-degree coefficient.
Second-degree coefficient.
{
"type": "Proportional",
"value": -10.0
}
{
"type": "Quadratic",
"value": {
"a": -5.0,
"b": -2.0
}
}
Id of the vehicle.
Value must be greater or equal to 0.0
Schedule-utility preferences.
The schedule utility is always null.
The schedule utility is computed using the alpha-beta-gamma model.
Compute the schedule-delay utility using Vickrey's alpha-beta-gamma model
The penalty for early arrivals (or departures), in utility per second.
If true, tstar_low and t_star_high represent the desired arrival-time interval, otherwise they represent the desired departure-time interval.
The penalty for late arrivals (or departures), in utility per second.
The latest desired arrival (or departure) time.
The earliest desired arrival (or departure) time.
{
"type": "AlphaBetaGamma",
"value": {
"beta": 5.0,
"desired_arrival": true,
"gamma": 20.0,
"t_star_high": 31350.0,
"t_star_low": 27900.0
}
}