Current predictors of fuel consumption are typically based on computer simulations or data collections in real traffic, where the route and vehicle type are not under the researcher’s control. Here, we predicted fuel consumption using test track data, an approach that allowed for location-specific predictions. Ninety-one drivers drove a total of 4617 laps, in two vehicles (Renault Mégane, Renault Clio), on two routes (highway and mountain), and with two eco-driving instructions (normal and eco). A multivariate analysis at the level of laps showed a strong predictive value for metrics related to speed, RPM, and throttle position, but with a considerable amount of variance attributable to route and vehicle type. A subsequent location-specific analysis showed that the predictive correlation of driving speed and throttle position fluctuated strongly during the lap and at some locations even became negative. We conclude that there is considerable potential in instantaneous location-specific prediction of fuel consumption.

当前的油耗预测值通常基于实际交通中的计算机模拟或数据收集，其中路线和车辆类型不受研究人员的控制。在这里，我们使用测试跟踪数据预测了燃油消耗，该方法允许进行特定位置的预测。九十一名驾驶员在两条路线（公路和山区）上驾驶两辆车（雷诺梅加内，雷诺克里奥）共驾驶了4617圈，并附有两条环保驾驶说明（正常行驶和环保行驶）。圈数的多变量分析显示了与速度，RPM和油门位置相关的指标的强大预测价值，但可归因于路线和车辆类型的变量却相当大。随后的针对特定位置的分析表明，驾驶速度和节气门位置的预测相关性在整个单圈中剧烈波动，在某些位置甚至变为负值。我们得出的结论是，在特定位置的瞬时油耗预测中具有相当大的潜力。