Publication Detail
Regression Models of Road User Cost Prediction for Highway Maintenance and Rehabilitation for Life Cycle Planning in California
UCD-ITS-RP-21-60 Journal Article UC Pavement Research Center Available online at: https://doi.org/10.1177%2F03611981211027153 |
Suggested Citation:
Kedarisetty, Sampat, Changmo Kim, John T. Harvey (2021) Regression Models of Road User Cost Prediction for Highway Maintenance and Rehabilitation for Life Cycle Planning in California. Transportation Research Record
Road user costs (RUCs) have been studied for the past few decades and still need to be considered to obtain a complete picture of the impact of road construction, maintenance, and rehabilitation. RUCs comprise delay costs (value of time), vehicle operating costs, and accident costs. Federal Highway Administration’s Life Cycle Cost Analysis software RealCost has been adapted, customized, and enhanced by California’s Department of Transportation (Caltrans) for California’s traffic patterns and maintenance practices in RealCostCA. However, the different types of roadways, traffic distributions, and work zone types have not been analyzed. In addition, RealCostCA works for selecting the most cost-effective pavement alternative under a project-specific basis and does not address network-level integration of RUCs. This study aimed to build easy-to-use look-up tables to obtain RUCs for a factorial of different work zone and traffic conditions. Different combinations of three roadway types (freeways, state highways, county roads), four representative hourly traffic distributions, three typical work zone closures (10-hour nighttime, 24-hour, 55-hour weekend closure), the numbers of lanes available in normal conditions (no work zone), and the numbers of lanes open during work zones were included in the factorial to calculate RUCs for specific traffic demand ranges at an interval of 5,000 vehicles per day per direction. The data obtained were subsequently used to combine into mixed regression models. These models enable calculation of RUC at any traffic level customized to the location of the project. Future work will be undertaken to combine the models into Caltrans’ network-level pavement management system.
Key words: road user costs, life cycle cost analysis, work zone, regression model, Caltrans, network, pavement, management