Continuous developments in automotive technology brought about the reality of having an increasing number of autonomous vehicles (AV) on roadways soon. However, this advancement comes with the uncertainty of how the interaction between the autonomous and non-autonomous (non-AV) vehicles will play out. Using traffic simulators to model both AVs and non-AVs, and studying the effect of AVs on roadway mobility can help researchers in learning what to expect in real life. In this paper, an open-source simulator called Simulation of Urban Mobility (SUMO) was used to develop AVs by modifying Intelligent Driver Model (IDM) car following and LC2013 lane changing models. Then, three actual roadways in Columbus, Ohio were modeled, and 40 simulations were run for each traffic network. The first set of simulations focused on the impacts that AVs have on vehicle roadway mobility with non-AVs when all the AVs have the same autonomy level. The second set of simulations had mixed AV autonomy levels (SAE Level 2, 3 and 4) with mixed AV and non-AV traffic. The analysis revealed that mobility of AVs and non-AVs increased generally as autonomy level increased. When the AV autonomy levels were mixed, the non-AVs experienced lower average speeds and decreased roadway mobility.

汽车技术的不断发展带来了很快就会有越来越多的自动驾驶汽车 (AV) 在道路上行驶的现实。然而，这种进步伴随着自主和非自主（非 AV）车辆之间的相互作用将如何发挥的不确定性。使用交通模拟器对 AV 和非 AV 进行建模，并研究 AV 对道路机动性的影响可以帮助研究人员了解现实生活中的期望。在本文中，通过修改智能驾驶员模型 (IDM) 汽车跟随和 LC2013 车道变换模型，使用名为城市交通仿真 (SUMO) 的开源模拟器来开发自动驾驶汽车。然后，对俄亥俄州哥伦布市的三个实际道路进行建模，并对每个交通网络运行 40 次模拟。第一组模拟侧重于当所有 AV 具有相同的自主级别时，AV 对非 AV 的车辆道路机动性的影响。第二组模拟具有混合 AV 自治级别（SAE 级别 2、3 和 4）以及混合的 AV 和非 AV 流量。分析表明，随着自主水平的提高，自动驾驶汽车和非自动驾驶汽车的移动性普遍增加。当 AV 自主级别混合时，非 AV 的平均速度较低，道路机动性降低。