Predictive car-following scheme for improving traffic flows on urban road networks
Predictive car-following scheme for improving traffic flows on urban road networks
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DOI：
10.1007/s11768-019-9144-z
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发表时间：
2019-11-01
影响因子：
1.4
通讯作者：
Kamal, Md Abdus Samad
中科院分区：
文献类型：
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作者：
Bakibillah, A. S. M.;Hasan, Mahmudul;Kamal, Md Abdus Samad
驾驶行为是造成高速公路交通瓶颈或限制信号交叉口通行能力的主要原因之一。本文提出了一种模型预测控制（MPC）框架下的车辆跟驰方案，以改善交通流行为，特别是在连接车辆（CV）环境下密集城市交通中单个车辆的停车和加速。该方案利用车对车（V2V）通信接收到的信息，预测前车的未来状态，并通过求解一个考虑有限未来时域的约束优化问题来计算控制输入。目标函数是最小化由于速度偏差、控制输入和不安全间隙而引起的加权成本。该方案与后续车辆共享计划驾驶信息，以便它们能够更好地进行协作驾驶决策。提出的车辆跟驰方案是在一个典型的驾驶场景下模拟的，在密集的交通中，有多个交叉口的红灯停下来。通过数值仿真，比较了该方案与现有跟驰方案的交通加速、排队和停车特性。
Driving behavior is one of the main reasons that causes bottleneck on the freeway or restricts the capacity of signalized intersections. This paper proposes a car-following scheme in a model predictive control (MPC) framework to improve the traffic flow behavior, particularly in stopping and speeding up of individual vehicles in dense urban traffic under a connected vehicle (CV) environment. Using information received through vehicle-to-vehicle (V2V) communication, the scheme predicts the future states of the preceding vehicle and computes the control input by solving a constrained optimization problem considering a finite future horizon. The objective function is to minimize the weighted costs due to speed deviation, control input, and unsafe gaps. The scheme shares the planned driving information with the following vehicles so that they can make better cooperative driving decision. The proposed car-following scheme is simulated in a typical driving scenario with multiple vehicles in dense traffic that has to stop at red signals in multiple intersections. The speeding up or queue clearing and stopping characteristics of the traffic using the proposed scheme is compared with the existing car-following scheme through numerical simulation.