Paratransit plays a critical role in meeting transportation needs in many cities in sub-Saharan Africa (SSA). However, it faces deep issues related to pollution, congestion, and safety. Understanding the driving patterns of paratransit in SSA can provide valuable insights into the transportation needs in the region, which is particularly relevant nowadays given the increasing focus on sustainable transportation solutions in Africa.

Representative driving cycles, which provide a realistic simulation of the driving conditions a vehicle is likely to encounter, are key to framing policies for effective transportation management, vehicle design, and urban and regional planning. However, cycle development has been limited in SSA due to a lack of data and standardized testing procedures. This study develops a representative driving cycle using GPS data gathered on paratransit vehicles traveling around Stellenbosch, South Africa, providing a benchmark for evaluation and a platform for further research and testing in SSA’s dominant transport industry.

A novel time series shape-based clustering methodology is employed that combines dynamic time warping and mixed integer programming to cluster micro-trips of varying length based on their time series shapes. Representative micro-trips from each cluster are stitched together with a maximum likelihood approach to curate the final cycle. By including transients from the measured data in cycle development, this novel approach to cycle development is particularly suited for capturing the notoriously unconventional and aggressive driving style of paratransit.

The constructed cycle and several international cycles are assessed against the measured database on the basis of eight characteristic kinematic parameters. The constructed cycle emerges as the most fitting choice to represent paratransit operating conditions, with an average deviance of 3.65% across the parameters, compared to deviations of 23%–34% for the international cycles.

辅助客运系统在满足撒哈拉以南非洲 (SSA) 许多城市的交通需求方面发挥着至关重要的作用。然而，它面临着污染、拥堵和安全等深层次问题。了解撒哈拉以南非洲辅助客运系统的驾驶模式可以为该地区的交通需求提供宝贵的见解，鉴于非洲越来越关注可持续交通解决方案，这一点在当今尤为重要。

代表性驾驶循环可以真实模拟车辆可能遇到的驾驶条件，是制定有效交通管理、车辆设计以及城市和区域规划政策的关键。然而，由于缺乏数据和标准化测试程序，SSA 的循环开发受到限制。这项研究利用在南非斯泰伦博斯周围行驶的辅助交通车辆上收集的 GPS 数据开发了一个具有代表性的驾驶周期，为 SSA 主导运输行业的进一步研究和测试提供了评估基准和平台。

采用一种新颖的基于时间序列形状的聚类方法，该方法结合了动态时间扭曲和混合整数规划，以根据时间序列形状对不同长度的微行程进行聚类。来自每个集群的代表性微旅行通过最大似然方法缝合在一起以策划最终周期。通过将测量数据的瞬态纳入自行车开发中，这种新颖的自行车开发方法特别适合捕捉辅助交通系统众所周知的非常规和激进的驾驶风格。

根据八个特征运动学参数，根据测量数据库对构建的循环和几个国际循环进行评估。构建的周期成为代表辅助交通运营条件的最合适选择，参数的平均偏差为 3.65%，而国际周期的偏差为 23%–34%。