Intelligent vehicle-highway systems (IVHS) have the potential to manage non-recurring congestion due to incidents and recurring congestion due to capacity shortfall more effectively than current operational systems. IVHS will provide information to the traveler, both in the vehicle and at home, business, and at commercial and recreational facilities, to help in the selection of more optimal travel modes and routes. The collected data can also be used to build a historical base and support required statistical reporting to appropriate agencies. The process of designing and evaluating an architecture that supports IVHS begins by obtaining and understanding requirements. These are usually obtained from the customer (who can be a local, state, or federal transportation agency or a private sector company or individual), or from a combination of customers, users, service providers, and others who are affected in a major way by the architecture. Scenarios, defining the conditions and constraints under which the IVHS architecture operates, are used with models to assess the benefits of candidate solutions for performance and life-cycle cost. Some measures of merit (MoMs), such as “average time to clear an incident” or “average vehicle speed at rush hour,” are selected to provide quantitative measures and comparisons of the benefits from alternative architectures. Others, such as evaluation of institutional, political, and risk issues, are qualitative in nature. MoMs should encompass the entire spectrum of requirements and major characteristics desired of the architecture. Additional factors used to help assess architecture performance and eventual acceptability are the results of demonstration programs that evaluate specific components of an architecture. The approach with the greatest benefit-to-cost ratio that does not conflict with the constraints derived from the qualitative assessment factors is generally selected for implementation.