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首页> 外文期刊>Journal of the South African Institution of Civil Engineering >A self-calibrating model to estimate average speed from AADT
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A self-calibrating model to estimate average speed from AADT

机译：自我校准模型，以估计AADT的平均速度

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摘要

Transport practitioners need a universally applicable speed prediction model to estimate average speeds on any road. Average annual speed is a key input to the economic assessment of transport infrastructure where reliable estimates of future average speeds are necessary to calculate economic costs and benefits. The relationship between Annual Average Daily Traffic (AADT) and average annual speed was investigated on higher-order roads across South Africa, revealing a high level of variability in this correlation at different locations. This variation is influenced by road characteristics, such as alignment and cross-section, complicating the formulation of a universal speed prediction model. Two novel speed prediction models are proposed in this article that use AADT to forecast future average annual speed. The speeds of heavy vehicles and light vehicles can be estimated separately, as well as the average speed of all vehicles simultaneously. Both models are self-calibrating, accounting for the variation in the AADT–speed relationship. This calibration step is unique to speed prediction models and increases the reliability of these models to estimate future average speeds considerably. Furthermore, self-calibrating average annual speed prediction models are universally applicable and will simplify economic assessment of transport infrastructure.
机译：运输从业者需要一个普遍适用的速度预测模型来估计任何道路上的平均速度。年平均速度是对运输基础设施经济评估的关键投入，其中需要未来平均速度的可靠估计，以计算经济成本和福利。在南非全面的高阶道路上调查了年平均日常交通（AADT）和平均年度速度之间的关系，在不同地点的这种相关性上揭示了高水平的变化。这种变化受道路特征的影响，例如对准和横截面，使其具有通用速度预测模型的配方。在本文中提出了两种新颖的速度预测模型，这些模型使用AADT预测未来的平均年度速度。可以单独估计重型车辆和轻型车辆的速度，以及所有车辆的平均速度。两种型号都是自我校准的，占AADT速度关系的变化。这种校准步骤是速度预测模型的独特，并提高了这些模型的可靠性，以大大估计未来平均速度。此外，自校准平均年速度预测模型是普遍适用的，并将简化运输基础设施的经济评估。

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