With the increasing number of vehicles in large-and medium-sized cities challenges in urban traffic management, control, and road planning are being faced. Taxi GPS trajectory data is a novel data source that can be u...With the increasing number of vehicles in large-and medium-sized cities challenges in urban traffic management, control, and road planning are being faced. Taxi GPS trajectory data is a novel data source that can be used to study the potential dynamic traffic characteristics of urban roads, and thus identify locations that show a notable lack of road planning. Considering that road traffic characteristics on their own are insufficient for a comprehensive understanding of urban traffic, we develop a road traffic characteristic time series clustering model to analyze the relationship between urban road traffic characteristics and road grade based on existing taxi trajectory data. We select the main urban area of Nanjing as our study area and use the taxi trajectory data of a single month for evaluating our method. The experiments show that the clustering model exhibit good performance and can be successfully used for road traffic characteristic classification. Moreover, we analyze the correlation between traffic characteristics and road grade to identify road segments with planning designs that do not match the actual traffic demands.展开更多
在先进场面活动引导和控制系统(advanced surface movement guidance and control systems,A-SMGCS)中,针对航空器滑行时间延迟而导致场面运行效率和安全水平的降低,提出一种集成场面态势监测的滑行路由实时更新算法。该算法采用局部路...在先进场面活动引导和控制系统(advanced surface movement guidance and control systems,A-SMGCS)中,针对航空器滑行时间延迟而导致场面运行效率和安全水平的降低,提出一种集成场面态势监测的滑行路由实时更新算法。该算法采用局部路由更新方式,首先采用时间窗约束Petri网建立航班滑行时间延迟时的场面局部模型;其次,定义模型中库所对应时间窗的合并运算规则;并据此展开局部模型约简,进而得到约简模型中航班滑行冲突判定条件;再次,以最小化航班在冲突区域的滑行成本为目标,实现了相关航班局部滑行路由优化同时保证了对原路由扰动最小;最后,通过算例验证了所提滑行路由实时更新方法的有效性。展开更多
电动出租车的规模化运营需要以充电设施为支撑。当前,对于电动出租车充电站规划,未能给出较为科学的方法。为此,综合考虑出租车驾驶员充电经济性、充电站服务便捷性以及配电网运行的经济性和安全性,提出一种基于出租车随机概率行为特性...电动出租车的规模化运营需要以充电设施为支撑。当前,对于电动出租车充电站规划,未能给出较为科学的方法。为此,综合考虑出租车驾驶员充电经济性、充电站服务便捷性以及配电网运行的经济性和安全性,提出一种基于出租车随机概率行为特性和道路行程时间可靠性的多目标规划方法,建立以全社会出租车充电时间最小、行程时间可靠性最高、配电网网损最低为目标函数,以充电站站间距离、配电网安全运行指标为约束条件的多目标规划模型。其次,基于排队理论的M/G/c模型,采用带约束条件的边际分析法对充电站容量进行优化配置。在此基础上,采用NSGA-2对模型进行求解,获得多目标模型的帕累托前沿,通过逼近理想排序法(technique for order preference by similarity to ideal solution,TOPSIS)确定最优规划方案。最后,通过包含47节点路网与60节点配电网的算例,验证了所提方法的正确性和有效性。展开更多
基金Under the auspices of National Natural Science Foundation of China(No.41571377)
文摘With the increasing number of vehicles in large-and medium-sized cities challenges in urban traffic management, control, and road planning are being faced. Taxi GPS trajectory data is a novel data source that can be used to study the potential dynamic traffic characteristics of urban roads, and thus identify locations that show a notable lack of road planning. Considering that road traffic characteristics on their own are insufficient for a comprehensive understanding of urban traffic, we develop a road traffic characteristic time series clustering model to analyze the relationship between urban road traffic characteristics and road grade based on existing taxi trajectory data. We select the main urban area of Nanjing as our study area and use the taxi trajectory data of a single month for evaluating our method. The experiments show that the clustering model exhibit good performance and can be successfully used for road traffic characteristic classification. Moreover, we analyze the correlation between traffic characteristics and road grade to identify road segments with planning designs that do not match the actual traffic demands.
基金This work was supported by the National Natural Science Foundation of China(Nos.U1833103,71801215)the China Civil Aviation Environment and Sustainable Development Research Center Open Fund(No.CESCA2019Y04).
文摘随着航班数量的不断增加,机场协同决策系统(Airport collaborative decision?making,A?CDM)的使用也越来越广泛。滑行时间预测的准确性对A?CDM计算离场航空器起飞排序队列和给出准确的撤轮挡时间具有重要的作用。本文提出一种基于时间?空间?环境数据的深度学习模型(Spatio?temporal?environment deep learning model,STEDL)来提高滑行时间预测的准确性。该模型由时间?流量变量(机场实际容量,场面航空器数量,时间段)、空间变量(滑行距离)、外部环境变量(天气,流控信息,跑道运行模式,机型)3部分组成。使用STEDL模型对香港机场离场航空器滑行时间进行预测验证。实验结果显示,STEDL模型预测准确率为95.4%,预测精度明显优于其他机器学习算法。
文摘在先进场面活动引导和控制系统(advanced surface movement guidance and control systems,A-SMGCS)中,针对航空器滑行时间延迟而导致场面运行效率和安全水平的降低,提出一种集成场面态势监测的滑行路由实时更新算法。该算法采用局部路由更新方式,首先采用时间窗约束Petri网建立航班滑行时间延迟时的场面局部模型;其次,定义模型中库所对应时间窗的合并运算规则;并据此展开局部模型约简,进而得到约简模型中航班滑行冲突判定条件;再次,以最小化航班在冲突区域的滑行成本为目标,实现了相关航班局部滑行路由优化同时保证了对原路由扰动最小;最后,通过算例验证了所提滑行路由实时更新方法的有效性。
文摘电动出租车的规模化运营需要以充电设施为支撑。当前,对于电动出租车充电站规划,未能给出较为科学的方法。为此,综合考虑出租车驾驶员充电经济性、充电站服务便捷性以及配电网运行的经济性和安全性,提出一种基于出租车随机概率行为特性和道路行程时间可靠性的多目标规划方法,建立以全社会出租车充电时间最小、行程时间可靠性最高、配电网网损最低为目标函数,以充电站站间距离、配电网安全运行指标为约束条件的多目标规划模型。其次,基于排队理论的M/G/c模型,采用带约束条件的边际分析法对充电站容量进行优化配置。在此基础上,采用NSGA-2对模型进行求解,获得多目标模型的帕累托前沿,通过逼近理想排序法(technique for order preference by similarity to ideal solution,TOPSIS)确定最优规划方案。最后,通过包含47节点路网与60节点配电网的算例,验证了所提方法的正确性和有效性。
