资源类型

期刊论文 2

年份

2022 1

2015 1

关键词

大数据分析；区域提取；人工势场；Dijkstra；路线推荐；出租车GPS轨迹 1

检索范围：

排序： 展示方式：

Fuel type preference of taxi driver and its implications for air emissions

Feng WANG,Beibei LIU,Bing ZHANG,Jun BI

《环境科学与工程前沿（英文）》 2015年 第9卷 第4期   页码 702-711 doi: 10.1007/s11783-014-0665-x

摘要： Natural gas became an available fuel for taxis in 2005 and had occupied a market share of 43.6% in taxi industry till 2010 in Nanjing, China. To investigate the energy replacement pattern as well as the pollutants reduction potential of the taxi industry, first, the fuel preference determinants of taxi drivers for their next taxis are analyzed. Results show that as an important alternative for the traditional gasoline, natural gas is widely accepted (75%) by taxi drivers. Different from the previous studies which focused on the early stage of cleaner fuel replacement, taxi drivers with various characteristics (such as age, working experience, and education level) are consistent with their fuel preference when they choose their next taxis. Result suggests that policies that concern consumers with specific characteristics may have little effects on the change of the market share, when the alternative fuel market has been developed well. In addition, the increased share of gas in the fuel market achieves a 7.2% reduction of energy consumption. Considering life cycle emissions, the following air pollutants, namely Greenhouse Gases (GHGs), carbonic oxide (CO), nitrogen oxide (NO ), particulate matters (PM) and hydrocarbons (C H ), gain 10.0%, 3.5%, 20.5%, 36.1%, and 26.4% of reduction respectively. Assuming all taxi fleets powered by natural gas with local policy intervention, the energy conservation and the five major air pollutant emissions could achieve the maximum reductions with 12.2%, 16.0%, 8.8%, 22.5%, 44.2%, and 49.4% correspondingly.

关键词： fuel preference     energy replacement     environmental impacts     taxi    

HTML PDF 收藏

APFD：面向移动轨迹大数据的出租车路径推荐方法 Research Article

张文勇1,夏大文1,常国艳5,胡杨2,霍雨佳1,冯夫健1,李艳涛3,李华青4

《信息与电子工程前沿（英文）》 2022年 第23卷 第10期   页码 1494-1510 doi: 10.1631/FITEE.2100530

摘要：

随着数据驱动智能交通系统的迅猛发展，高效的出租车路径推荐方法成为智慧城市的研究热点。基于移动轨迹大数据，提出一种基于人工势场（APF）和Dijkstra方法的出租车路径推荐方法。为提高路径推荐效率，提出一种区域提取方法，该方法通过原点和终点坐标搜索包含最优路径的区域。基于APF方法，提出一种有效的冗余节点去除方法。最后，通过Dijkstra方法推荐最优路径。将APFD方法应用于仿真地图和北京四环的实际路网。在地图上随机选取20对起点和终点坐标，采用APFD方法、蚁群（AC）算法、贪婪算法（A*）、APF、迅速探索随机树（RRT）、非支配排序遗传算法-II（NSGA-II）、粒子群算法（PSO）和Dijkstra算法进行最短路径推荐。在最短路径规划方面，与AC、A*、APF、RRT、NSGA-II和PSO相比，APFD的路径规划能力分别提高了1.45%–39.56%、4.64%–54.75%、8.59%–37.25%、5.06%–45.34%、0.94%–20.40%和2.43%–38.31%。与Dijkstra算法相比，APFD的执行效率提高了1.03–27.75倍。此外，在北京四环实际路网中，APFD推荐最短路径的能力优于AC、A*、APF、RRT、NSGA-II和PSO，且APFD的执行效率高于Dijkstra方法。

关键词： 大数据分析；区域提取；人工势场；Dijkstra；路线推荐；出租车GPS轨迹    

HTML PDF 收藏

标题 作者 时间 类型 操作

Fuel type preference of taxi driver and its implications for air emissions

Feng WANG,Beibei LIU,Bing ZHANG,Jun BI

期刊论文

APFD：面向移动轨迹大数据的出租车路径推荐方法

张文勇1,夏大文1,常国艳5,胡杨2,霍雨佳1,冯夫健1,李艳涛3,李华青4

期刊论文