Traffic Jam Models Do Not Wear Designer Clothing
Eliminating transportation bottle necks from modern life is not a straight forward issue. Population density shifts, changes in commercial and residential development, socio-economic factors, politics, mass transit availability, environmental considerations, and even telecommuting have an impact on traffic volume and flow, not to even mention holidays. Taking these and other factors into account has become a very complex undertaking, driving the need for predictive computer models to help optimize solutions. These models can be used by transportation planners to help determine the mobility, economic, safety, and even political value of proposed transportation projects in a given region.
Take a proposal for building a high speed bullet train, for example. The desired outcome is to move people very fast between stations using an energy efficient vehicle. These people must also have transport to and from stations. They must want to regularly travel to and from the regions that the stations are located in. They must be safe while doing so. They must be able to stay in touch. They may eat lunch. They probably will use restroom facilities. They must want to do all of this enough to fund the cost of the project through fees, taxes, bonds, and other investments. They must perceive great value in doing so. There must be well understood environmental impact. And so on.
To help grasp the total scenario, each item on the list of considerations may be given a score or value based on cost, desirability, predicted impact, ancillary effects, etc. and the aggregate score for the project determined. Alternative solutions such as adding roadways or airports can also be scored in a similar manner, and the relative value of each solution compared to each other. In an ideal world with perfect models, it would then be a simple matter of choosing the solution with the best overall score. Realistically, however, such modeling results are only used to influence and inform the overall project planning process.