A Comprehensive Study on Autonomous Vehicle Integration for Tırport

Although regular road transportation is convenient, it can be difficult for transportation companies to operate. Most issues stem from timetable delays, poor routing plans, and greater transportation costs, including wages, fuel, and operations expenditures. Wind resistance during high-speed transportation increases fuel use, and human error causes safety incidents that increase costs and environmental damage. Therefore, the platooning system is a strategically designed alternative to keep trucks in a convoy using sensors. Thus, the goal of this research is to determine optimized platooning routes in Turkey’s motorway network and the ideal locations for hubs. Also, we would like to explore the potential of platooning technology to reduce fuel consumption, carbon footprint, and transportation time with mathematical modeling and Python code. According to our results, the 5 hubs should be located in Adana, Ankara, Manisa, Istanbul, and Bursa. The greatest percentage saving is achieved by 4 truck platooning systems with an average of 11% and there is reduction of millions kg of CO2 emission in a day. In addition, we conducted a what-if-analysis with a future motorway in Turkey which resulted in an increase of profit to 12%. Finally, we implemented the waiting times of trucks for each other when forming convoys in a hub and according to our results, we discovered that it can be disregarded in each scenario because they are less than 20 minutes. And also even in the worst case, there is a reduction of total empty mileages by up to 1 in 3.

尽管常规公路运输便捷易行，但运输企业在运营中仍面临诸多困境。多数问题源于时刻表延误、路由规划不合理，以及包括人力薪酬、燃油消耗与运营开支在内的高额运输成本。
高速行驶过程中的空气阻力会提升燃油消耗，而人为失误引发的安全事故则会进一步推高成本并加剧环境破坏。为此，基于传感器实现卡车编队行驶的车队编队系统（platooning system）应运而生，作为一种具备战略价值的替代运营方案。
据此，本研究的目标在于优化土耳其高速公路网络中的卡车编队行驶路线，并确定枢纽站点的理想选址；同时，我们希望通过数学建模与Python代码，探究车队编队技术在降低燃油消耗、碳足迹与运输时长方面的应用潜力。研究结果显示，5座枢纽站点应分别设于阿达纳（Adana）、安卡拉（Ankara）、马尼萨（Manisa）、伊斯坦布尔（Istanbul）与布尔萨（Bursa）；采用4车编队的卡车编队系统可实现最高的成本节约率，平均可达11%，单日二氧化碳减排量可达数百万千克。
此外，我们针对土耳其未来规划的高速公路开展了假设情景分析（what-if-analysis），结果显示利润可提升至12%。最后，我们将枢纽站点内卡车编队时的相互等待时长纳入考量，研究发现，在所有场景下该等待时长均不足20分钟，因此可忽略不计；即便在最差工况下，总空载里程也可减少至多三分之一。