Artificial passengers are computer-generated simulations of passengers that can be used in a variety of applications, such as transportation planning, vehicle design, and emergency management. They are created using a variety of mathematical models and simulation techniques, and can be customized to represent different demographics, behaviors, and needs.

One common way to create artificial passengers is to use a Monte Carlo simulation. This involves randomly generating values for a set of parameters, such as age, gender, trip origin and destination, and mode of transportation. These parameters can be based on real-world data, or they can be estimated using assumptions or probability distributions.

Once the parameters have been generated, they are used to create a virtual passenger. This passenger can then be placed in a simulated environment, such as a transportation network, and their behavior can be simulated. For example, the passenger may be assigned a route, and their travel time and mode of transportation may be recorded.

Artificial passengers can be used for a variety of purposes, including:

* Transportation planning: Artificial passengers can be used to test the performance of different transportation systems, such as roads, highways, and public transportation. They can also be used to identify bottlenecks and congestion points, and to evaluate the impact of different transportation policies.

* Vehicle design: Artificial passengers can be used to evaluate the safety and comfort of different vehicle designs. They can also be used to test the effectiveness of different safety features, such as airbags and seat belts.

* Emergency management: Artificial passengers can be used to simulate the evacuation of buildings, stadiums, and other public spaces. This can help emergency managers to identify potential problems and develop evacuation plans.

Artificial passengers are a valuable tool for understanding and improving the transportation system. They provide a way to test different scenarios and evaluate the impact of different policies without having to conduct real-world experiments.