Transportation professionals in small and medium-sized communities (SMSCs) require planning-level methods and models to estimate arterial street mobility performance. Because financial resources are often constrained, methods that require limited field data collection are most useful. Understanding arterial performance in terms of mobility can identify problem areas and facilitate improvement prioritization. This paper describes completed research at the Texas Transportation Institute with the objective of developing a corridor travel time index (TTI) arterial model for estimating arterial performance in small to medium-sized communities. The TTI is the ratio of the travel rate (minutes per mile) during the peak period to the travel rate (minutes per mile) during the off-peak period. The TTI is a geographically scalable measure, which makes the models more transferable. This paper describes two models to assist transportation professionals in small and medium-sized communities to estimate the TTI in the arterial environment during light and moderate congestion conditions. To address limitations of existing models, the models 1) consider access management (e.g., driveway density), 2) are corridor-based, 3) are a function of generally-available or easy-to-obtain data, 4) are calibrated and validated with extensive field data, and 5) explain a relatively high degree of variability. The models were developed based upon extensive field data along a typical suburban corridor that is representative of a typical small and medium-sized community. The model for moderate congestion conditions (TTI values up to approximately 2.8) is a function of traffic volume, driveway density, signal green time relative to the cycle time (g/C), and signal coordination condition. The model for light congestion conditions (TTI values up to 1.35) is based upon traffic volume and g/C along the corridor. Intuitively, when congestion levels are relatively higher, the research found that driveway density was an important prediction variable for TTI along the arterial corridor. The research findings will benefit transportation professionals and decision-makers in small and medium-sized communities who are responsible for tracking mobility along roadways of interest and for prioritizing roadway improvements.
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