复杂城市交通中混合动力汽车的集成生态驾驶与动力总成优化
Integrated Eco-Driving and Powertrain Optimization for Hybrid Vehicles in Complex Urban Traffic
AI总结：
针对城市混合动力汽车，提出集成有限时域生态驾驶规划框架，联合优化交通行为与动力总成运行，同时建模多方面驾驶行为及动力总成运行，模拟研究表明该方法能在维持合规驾驶计划时改善能源性能。
AI中文摘要：
城市生态驾驶需要同时规划速度、加速度、车道决策、周围车辆安全、交叉路口规则和车辆能源使用。现有研究通常仅优化城市驾驶的某些方面，而将其余决策分开处理。本文为城市混合动力汽车开发了一个集成的有限时域生态驾驶规划框架，在统一的混合整数公式中联合优化交通行为和动力总成运行。该方法的新颖之处在于同时对纵向运动、车道占用和变化、跟车和变道安全、信号控制和无信号交叉路口行为以及混合动力总成运行进行建模。模拟研究将该方法与遵循规则、信号感知、超车启用和仅运动学优化基线进行比较。结果表明，在保持可行、安全、舒适和符合交通规则的城市驾驶计划的同时，能源性能得到了改善。
英文摘要：
Urban eco-driving requires the simultaneous planning of speed, acceleration, lane decisions, surrounding-vehicle safety, intersection rules, and vehicle energy use. Existing studies commonly optimize only selected aspects of urban driving, such as longitudinal motion, lane changing, intersection crossing, or powertrain energy management, while treating the remaining decisions separately. Unlike these studies, this paper develops an integrated finite-horizon eco-driving planning framework for urban hybrid vehicles that jointly optimizes traffic behavior and powertrain operation within a unified mixed-integer formulation. The novelty of the proposed method lies in simultaneously modeling longitudinal motion, lane occupancy and changes, car-following and lane-change safety, signalized and unsignalized intersection behavior, and hybrid powertrain operation. The formulation captures lane availability, lane-dependent speed limits, mandatory and emergency lane changes, safe-to-clear signal conditions, downstream clearance, stop-and-yield rules, engine and motor power, battery state of charge, regenerative braking, and fuel consumption. Simulation studies compare the proposed method with rule-following, signal-aware, overtaking-enabled, and kinematic-only optimization baselines. The results demonstrate improved energy performance while maintaining feasible, safe, comfortable, and traffic-rule-compliant urban driving plans.
