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Open Access Publications from the University of California

Scholarly Works (2 results)

  • Article
Research Reports (2001)

Intelligent "driver assistance" systems which utilize in-vehicle forward-looking sensors can be supplemented by vehicle-vehicle and vehicle-highway cooperative elements to comprise a "sensor-friendly" highway environment that would enhance the operational efficiency, and ultimately, the safety benefits of these systems. In our research, we have identified the current limitations of autonomous sensing systems in target/background discrimination with cluttered highways. Based upon this, and by limiting ourselves to "sensed" (and not wireless) systems, we have conceived relatively inexpensive vehicle-highway cooperative systems to allow those limitations to be mitigated. Emphasis has been placed on 77 GHz (millimeter wave) automotive radar sensors - a sensor type which is in current use and when improved, will result in improved longitudinal safety products in the near-to-mid term, up through the longer term vision of full vehicle-highway automation. In the work reported here, we introduce the concept of sensor-friendly high systems, describe roadside signatures, and using these as bases, discuss our concepting and experiments several cooperative vehicle-highway concepts. We describe experiments and results from prototypes of three of the potentially nearest term means to realize a cooperative collision avoidance systems, which we regard as the first step toward sensor-friendly highways 1 . We describe three potential systems: Light Emitting Diode Brake Light Messaging, Roadside-Mounted Corner Cubes, and Passive License Plates. We believe that while experimental results point toward the need for further proof-of-concept refinements, these systems potentially represent technologically sound cooperative vehicle-roadway components, and that indeed, "sensor friendly" systems, when put to the test, can eventually translate into significant benefit in terms of lives saved.

    Cover page: Sensor-Friendly Freeways: Investigation of Progressive Roadway Changes to Facilitate Deployment of AHS
    • Article
    • Peer Reviewed
    UC Davis Previously Published Works (2022)
    Characterization of model errors is important when applying satellite-driven evapotranspiration (ET) models to water resource management problems. This study examines how uncertainty in meteorological forcing data and land surface modeling propagate through to errors in final ET data calculated using the Satellite Irrigation Management Support (SIMS) model, a computationally efficient ET model driven with satellite surface reflectance values. The model is applied to three instrumented winegrape vineyards over the 2017-2020 time period and the spatial and temporal variation in errors are analyzed. We illustrate how meteorological data inputs can introduce biases that vary in space and at seasonal timescales, but that can persist from year to year. We also observe that errors in SIMS estimates of land surface conductance can have a particularly strong dependence on time of year. Overall, meteorological inputs introduced RMSE of 0.33-0.65 mm/day (7-27%) across sites, while SIMS introduced RMSE of 0.55-0.83 mm/day (19-24%). The relative error contribution from meteorological inputs versus SIMS varied across sites; errors from SIMS were larger at one site, errors from meteorological inputs were larger at a second site, and the error contributions were of equal magnitude at the third site. The similar magnitude of error contributions is significant given that many satellite-driven ET models differ in their approaches to estimating land surface conductance, but often rely on similar or identical meteorological forcing data. The finding is particularly notable given that SIMS makes assumptions about the land surface (no soil evaporation or plant water stress) that do not always hold in practice. The results of this study show that improving SIMS by eliminating these assumptions would result in meteorological inputs dominating the error budget of the model on the whole. This finding underscores the need for further work on characterizing spatial uncertainty in the meteorological forcing of ET.

    Supplementary information

    The online version contains supplementary material available at 10.1007/s00271-022-00808-9.
      Cover page: Effects of meteorological and land surface modeling uncertainty on errors in winegrape ET calculated with SIMS
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