Commute Time Uncertainty Model
10
To estimate the expected commute time by accounting for the compounding effects of traffic congestion and weather conditions.
NOTEAbout This Model
## To estimate the expected commute time by accounting for the compounding effects of traffic congestion and weather conditions. This model estimates **Estimated Commute Time** based on uncertain inputs: Traffic Delay Factor, Weather Delay Factor. Run the simulation to see the distribution of possible outcomes.
VARIABLETraffic Delay Factor
triangular(0.8, 1.65, 2.5)
Represents the variance in time due to traffic; 0.8 accounts for light traffic, while 2.5 represents heavy congestion.
traffic_delay_factor
VARIABLEWeather Delay Factor
triangular(0.9, 1.2, 1.5)
Weather can slightly speed up (clear roads) or significantly slow down (snow/rain) travel.
weather_delay_factor
FORMULATotal Impact Multiplier
traffic_delay_factor * weather_delay_factor
Combined delay factor multiplying traffic and weather impact. Normalizes weather (min 0.9) and traffic.
total_impact_multiplier
FORMULAEstimated Commute Time
base_commute_minutes * total_impact_multiplier
Final estimated commute time based on the base duration and the combined delay factors.
estimated_commute_time
OUTPUTEstimated Commute Time
estimated_commute_time
Estimated door-to-door commute time accounting for traffic variability, weather, and route uncertainty. The spread helps you decide how much buffer time to build into your schedule.
CONSTANTBase Commute Minutes
30
Typical commute time under ideal conditions (no traffic, good weather).
base_commute_minutes
What is Carlo?
Carlo is a visual tool for Monte Carlo simulation. Model uncertainty by dragging probability distributions, connecting them visually, and running thousands of scenarios instantly.