Driving cycles are important parameters to estimate vehicle emissions. However, most previous driving cycles, which were developed at the city scale or even national scale, cannot resolve the emission variations affected by road types and thus might introduce large uncertainties in the emission estimation. In this study, we proposed a new approach based on road type-based (RT-based) driving cycles to improve the estimation of vehicle emissions. As a case study, RT-based driving cycles for passenger cars were developed using more than 600,000 s of GPS data collected through on-road tests in Guangzhou. Results showed that driving cycles varied across road types (urban arterial road, highway, and other urban road), which featured varied velocities, acceleration, deceleration, and driving mode percentages. The urban arterial road had the lowest velocity (18.7 km/h), but the largest creeping mode proportion (61%). The other urban road had the largest acceleration and deceleration, while the highway had the highest average velocity (43.2 km/h) but the lowest acceleration and deceleration. Evaluations revealed that RT-based driving cycles could accurately depict separate driving patterns and emission factors on different road types. In comparison, city-level driving cycles and standard driving cycles typically overestimated emission factors of highways but underestimated those of other road types in Guangzhou. Consequently, emissions of light-duty gasoline passenger cars could be underestimated by 33% in the downtown and overestimated by approximately 25% in and around the highways. This study highlights the development of RT-based driving cycles to accurately estimate vehicle emissions and characterize their spatial variations.

驾驶周期是估算车辆排放的重要参数。然而，大多数以前在城市规模甚至全国范围内开发的驾驶循环无法解决受道路类型影响的排放变化，因此可能会给排放估算带来很大的不确定性。在这项研究中，我们提出了一种基于道路类型（基于 RT）的驾驶循环的新方法，以改进车辆排放的估计。作为案例研究，使用通过广州道路测试收集的超过 600,000 秒的 GPS 数据开发了基于 RT 的乘用车驾驶循环。结果表明，驾驶周期因道路类型（城市主干路、高速公路和其他城市道路）而异，其特点是速度、加速度、减速度和驾驶模式百分比各不相同。城市主干道速度最低（18.7 km/h），但爬行模式比例最大（61%）。另一条城市道路的加减速最大，而高速公路的平均速度最高（43.2 km/h），但加减速最小。评估表明，基于 RT 的驾驶循环可以准确地描述不同道路类型上的不同驾驶模式和排放因子。相比之下，广州市级行车周期和标准行车周期通常高估了高速公路的排放因子，而低估了广州其他道路类型的排放因子。因此，市中心的轻型汽油乘用车的排放量可能被低估 33%，而高速公路及其周边地区的排放量可能被高估约 25%。