A Review on Research Status and Trends of Eco-driving on Intelligent Connected Vehicles
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摘要: 作为近年来智能网联汽车领域的研究焦点，生态驾驶旨在提高驾驶安全的基础上，通过改善驾驶行为，有效缓解能源消耗和污染排放等问题，引起了各国政府、企业、高校和研究机构等的高度重视。同时，随着智能网联车辆技术的迅速发展，网联环境为生态驾驶提供了新的发展契机。为了分析智能网联车辆生态驾驶的研究进展，通过与传统生态驾驶进行对比，从车辆自身特性、驾驶人个性、道路交通状况与社会条件4个方面分析了智能网联环境下的生态驾驶的影响因素；从生态驾驶控制策略和生态驾驶应用现状2个方面对现有智能网联生态驾驶研究进行了归纳与分析；并从影响因素、控制策略和决策优化3个方面讨论了生态驾驶的意义、应用与目前所存在的问题，致力于为未来的相关研究提供有益的指导与借鉴。分析结果表明：智能网联环境下的生态驾驶和传统生态驾驶的影响因素较为相似，不过网联传感器和通信条件对智能网联环境生态驾驶有着较为显著的影响；相较于传统生态驾驶，智能网联环境下生态驾驶的控制策略与决策优化多考虑复杂驾驶工况、多车级别的全局生态驾驶；且由于各种新型技术的快速发展，结合先进的技术、适应行业发展需要也将成为未来智能网联生态驾驶发展的必然趋势。Abstract: In recent years, eco-driving has become a major research focus within intelligent connected vehicles, aiming to effectively alleviate problems such as energy consumption and emission by improving driving behaviors, which attracts the great attention from governments, businesses, universities, and research centers. Meanwhile, with the rapid advancement of intelligent networked vehicles, the networked environment provides new development opportunities for eco-driving. To analyze the research progress of eco-driving on intelligent connected vehicles, the influencing factors are analyzed from four aspects compared with traditional eco-driving: vehicle characteristics, drivers' personality, road traffic conditions, and social environment. The existing studies on intelligent connected eco-driving are summarized from two aspects: eco-driving control strategies and current status of eco-driving applications. To provide useful guidance and references for future research, the significance, application, and current problems of eco-driving are also discussed from three aspects: influencing factors, control strategies, and decision optimization. The analysis results show that the influencing factors of eco-driving under intelligent connected environment or traditional environment are relatively similar; however, the networked sensors and communication conditions have greater impacts on eco-driving under the intelligent connected environment. Compared with traditional eco-driving, the control strategies and decision optimization for eco-driving under the intelligent connected environment consider more complex driving conditions, as well as global eco-driving at multi-vehicle levels. In addition, with the rapid growth of new technologies, combining advanced technologies and adapting them to the development of the industry will become an inevitable trend of eco-driving on intelligent connected vehicles in the future.
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图 1 智能网联车辆（CAVs）示意图
Figure 1. Schematic diagram of connected automated vehicles (CAVs)
图 3 网联环境下生态驾驶控制策略研究流程
Figure 3. Research process of eco-driving control strategy in networked environment
表 1 网联环境下与传统生态驾驶控制策略的对比
Table 1. The comparison of eco-driving control strategies in conventional environment and in networked environment
项目 传统生态驾驶策略控制研究 网联环境下生态驾驶策略控制 研究对象 传统车辆(燃油车） 智能网联车辆CAVs 研究内容 单车能源消耗 多车、系统整体消耗 研究场景 交叉口、信号灯范围 交叉口、多车队列控制 评价标准 能源消耗、排放污染 能源消耗、安全、通行效率 
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表 2 对于未来生态驾驶研究方向的建议
Table 2. Suggestions for future research directions of eco-driving
项目 传统生态驾驶研究 未来生态驾驶研究 研究对象 人工驾驶车辆 自动驾驶车辆 路段级 路网级 人工驾驶车辆 自动驾驶车辆(L3〜L5) 研究方法 单车动态规划 集群算法动态规划 模型预测控制 人工智能预测 理论求解 理论实际结合 研究方向 单车内部交互 车路协同多车交互 单车控制规划 多车车队控制规划 单交叉路口决策优化 多交叉路口决策优化 研究平台 Matlab PerScan CarSim HIL TruckSim VISSIM 数据来源 仿真模拟驾驶 实体车驾驶实验 仿真/模拟交通数据 真实交通大数据
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