University of California Pavement Research Center

The intention of the study is to demonstrate the potential economic effects of delayed road maintenance and management, leading to deteriorated riding quality and subsequent increased vehicle operating costs, vehicle damage and freight damage. The overall objectives of this project is to enable Caltrans to better manage the risks of decisions about freight and the management and preservation of the pavement network, as the potential effects of such decisions (i.e., to resurface and improve riding quality earlier or delay such a decision for a specific pavement) will be quantifiable in economic terms. This objective will be reached through applying the principles of vehicle-pavement interaction (V-PI) and state-of-the-practice tools to simulate and measure peak loads and vertical acceleration of trucks and their freight on a selected range of typical pavement surface profiles on the State Highway System (SHS) for a specific region or Caltrans district. The objectives of this report are to: Provide information on Tasks 7 and 8. Analyze data collected for Companies A and B. Compare vehicle and freight data with riding quality Conclusions The following conclusions are drawn based on the information provided and discussed in this report: The TruckSIMTM simulations provided reasonable estimates of the expected tire loads and vertical accelerations of the two trucks used in the simulations. The trends observed for the TruckSIMTM simulation data were similar to published and expected trends, and it appears as if the data can thus be used to model roads and vehicles where data cannot be collected on roads using real trucks. The measured data obtained from the two trucks on the various roads were consistent with expected trends in published literature. Measured data were used to analyze trends on the effects of riding quality on speeds, as well as the effect of unique features such as concrete slabs on the generated vertical accelerations in the vehicles. A high-level comparison between the simulated and measured data indicated similar trends and similar data obtained from the two processes. Matching locations exactly between the simulated and measured data proved to be complicated, but reasonable location comparisons could be obtained. If exact location comparisons and vehicle conditions (load, inflation pressure, suspension stiffness, etc.) could be obtained, the match between the two sets of data could be improved further. Recommendations The following recommendations are made based on the information provided and discussed in this report: TruckSIMTM simulations should be incorporated into any further studies of this kind to enable a cost-effective option of generating realistic vehicle parameters (accelerations, tire loads, etc.) for a wide array of roads in California. Additional measurements of densification of tomatoes on trailers during transportation on a range of roads causing a range of vertical acceleration frequencies should be obtained to enable a detailed analysis of the potential damage to the transported tomatoes. The data measured and simulated for Tasks 7 and 8 should be incorporated into the methodologies for Tasks 9 to 11 to ensure that the map of road conditions and relationship for riding quality and tire loads/freight accelerations is realistic in terms of typical California data.