Overview
Continuing growth in urban travel demand will inevitably require more physical capacity in the transportation system. However, because of limited financial resources, high construction costs, environmental considerations, long timelines, and an increasingly complex regulatory process, capacity-adding projects have become actions of last resort. It therefore behooves decision makers, planners, and engineers to evaluate operational improvement strategies that can—singly or in combination—eliminate or mitigate the need for a more traditional highway construction project.
Effectively evaluating the wide range of operational improvement strategies that are available is not a trivial matter, particularly when their performance is to be compared against the construction of new lanes. Traditional travel demand forecasting models are not effective for this kind of comparative analysis for several reasons:
- They assume that all drivers have perfect knowledge of the travel time on each of the travel paths available to them, an assumption that masks the effectiveness of operational improvement strategies aimed at improving driver awareness.
- They assume that the capacity of a freeway link or an arterial segment is a constant value, whereas an emerging body of research indicates that such capacity is better represented as a random variable (1–3). This limitation reduces the effectiveness of traditional tools for comparing alternatives because fluctuating capacity introduces variability that measurably affects vehicle assignments and network performance characteristics.
- They are not usually sensitive to the effects that upstream bottlenecks and blockages can have on downstream service rates. As an example, the models do not generally recognize that when the upstream queue of a separate turn lane extends into the adjoining through lane, this blockage prevents through traffic from reaching the downstream intersection for as long as the blockage exists, even when the downstream signal is green.
- They assume that all vehicle trips identified in the origin–destination (O-D) matrix will be completed by the end of the time period being analyzed, regardless of whether there is actually sufficient capacity to accommodate these trips within the specified time window. Thus, each vehicle trip is assigned to an entire travel path from origin to destination, even if some bottlenecks along that path operate with a volume/capacity ratio greater than 1.0.
Some modeling advancements are beginning to address these issues, but the advancements have not yet reached the point of practical and regular application, nor do they address all of the issues simultaneously. Ideally, the analysis methods should enable evaluation of improvement strategies that cut across the full spectrum of operations, technology, and design. They should also provide multiple performance measures that can be used to evaluate different strategies according to their impacts at the point, link, corridor, and network levels.
This report summarizes the results of a capacity project undertaken through the second Strategic Highway Research Program (SHRP 2) to advance the state of practice in this area. The objectives of this project were to (a) quantify the capacity benefits, individually and in combination, of operations, design, and technology improvements at the network level for both new and existing facilities; (b) provide information and tools to analyze operational improvements as an alternative to traditional construction; and (c) develop guidelines for sustained service rates (SSRs) to be used in planning networks for limited access highways and urban arterials (2).