Empirical Models of Demand Levels and Turn-In Rates at Roadside Rest Areas

Abstract

Roadside rest areas provide valuable and convenient services to road users as well as tangible safety benefits. However, these benefits are not always enough to warrant the costs, and therefore these facilities are not always economically justified. As such, understanding the factors that affect rest area demand is important for transportation agencies to design and maintain these facilities efficiently within their jurisdictions. The effects of nearby comparable facilities and rest areas on the demand characteristics of roadside rest areas have not been well analyzed in previous literature. This paper presents the results of binary logistic regression and negative binomial regression models on the demand characteristics of 47 roadside rest areas in Michigan. These models were developed separately for passenger cars and commercial trucks because the decision-making processes for these types of road users were likely different. Key results include the finding that greater distances between rest areas and nearest upstream rest areas or comparable facilities lead to increases in both the number and proportion of vehicles entering roadside rest areas. In addition, as volumes increase on the adjacent roadway, the proportion of vehicles entering roadside rest areas decreases despite a greater number of entering vehicles.