Abstract

We develop a traffic congestion index using data for California highways from 1976 through 1994. The technique yields a congestion measure which has several advantages. The index developed here can be applied to counties, urbanized areas, highway segments, or other portions of geographic areas or highway networks. The index allows cross-sectional and time series comparisons which have only rarely been possible. Most importantly, the congestion index developed here is based on data which are readily available. We compare our index to others based on Highway Performance Monitoring System (HPMS) data, and illustrate similarities and differences. We also discuss important issues for future research and data collection efforts which can contribute to more refined congestion measurement.

Abstract

Transportation policy making frequently requires evaluating a proposed change, whether it be a physical investment or a new set of operating rules for allocating rights to an existing facility. Some, like the rail tunnel under the English channel, are one-time capital investments with enormous and complex effects on accessibility throughout a network. Others, like congestion pricing proposed for Hong Kong, may be technically reversible but require major behavioral and political groundwork. 

In such cases, the optimization framework that proves useful in so much transportation analysis is often inadequate. In an optimization model, important aspects of a problem are represented as a few variables which can be chosen to maximize some objective. For example, Robert Strotz shows how highway capacity can be chosen to minimize total travel costs in the presence of traffic congestion. But often the change is too sharp a break from existing practice, or the objectives too numerous, to represent the problem in a mathematical optimization framework. Perhaps a given highway improvement not only expands capacity to handle peak traffic flows but also speeds off-peak travel, reduces accidents, and imposes noise on residential neighborhoods. Perhaps the required capital expenditures occur in a complex time pattern, and the safety effects depend on future but uncertain demographic shifts. One would like a method for analyzing the merits of such a package of changes, and for comparing it to alternative packages. 

Such a method is called project evaluation. Performed skillfully, it can identify key consequences of a proposed project and provide quantitative information about them to guide policy makers. Much of this information may be non-commensurable: i.e., the consequences may not all be measured in the same units and hence the analyst may not be able to determine the precise extent to which these effects offset each other. For example, a tax-financed improvement in airway control equipment might improve safety but magnify existing income inequalities.