在发达国家，随着越来越多的人搬到城市中心，汽车使用量正在下降，而年轻人更倾向于选择其他出行方式。
Across the developed world, car use is in decline as more people move to city centres, while young people especially are opting for other means of travel.
随后三晚入住率开始下跌，因为人们找到替代飞机出行的旅游方式或者选择回家。
Occupancy declined for the following three nights, as people found alternative travel methods or returned home.
2009年，埃因霍温6个月的试行结果表明，该收费方式改变了70%驾车员的习惯，他们避开高峰期出行，或者选择不拥堵的路段。
A six-month pilot trial in Eindhoven last year showed that 70 percent of users changed their behavior as a result of pricing, by traveling either at off-peak hours or on less crowded roadways.
该模型体系顺序地包括四部分，分别是活动决策生活方式基础、活动的产生、目的地和交通工具选择、出行时间分布。
The modeling system comprises four steps sequentially, that are, lifestyle basis of activity decisions, activity generation, destination and mode choice, and departure time choice.
不同的出行目的、出行方式均可能带来不同的保险需求，旅游保险可以根据个人的出行目的来做个性化的选择。
The different trip purpose, the trip mode possibly bring the different safe demand, the traveling insurance may act according to individual trip purpose to make personalized the choice.
宏观因素决定着出行方式的总结构，微观因素则决定着各交通区之间出行的具体选择。
The macroscopic factors determine the structure of urban passenger traffic mode, the microscopic factors determine the concrete mode selection between traffic zones.
在决定城市出行方式选择的众多因素中，道路交通设施空间资源的供给是最为关键的因素之一。
The supply of urban road traffic infrastructures 'spacing resources is the most important one of the influence factors on traffic mode choosing behaviors.
出行者交通方式选择行为决定城市的交通方式结构。
The structure of city traffic mode is decided by the traveler traffic mode choice behavior.
传统的交通需求4阶段分析模型大多基于各类出行的起讫点调查(OD调查)，建立出行生成、出行分布、出行方式选择和流量分配的4阶段预测模式。
The traditional travel demand model usually bases itself on the od study survey and employs a 4-step modeling process including trip generation, trip distribution, mode choice and assignment.
此外，该方法计算简便、易于实现，对于各种交通方式下的旅客出行偏好选择问题具有普遍适用性。
Furthermore, the presented method is easy to calculate, convenient to implement and universally applicable in passenger's preference choice problem under every traffic modes.
利用模型预测出行量在各种交通方式中分配的比率，分析不同服务属性对出行者选择交通方式的影响。
By this model, one can predict a ratio of different kinds of transportation method assigned, and analyze what influence different properties of the services have on the executor.
建立出行者基本属性与交通方式选择的关系模型，研究影响和引导城市交通方式结构的有效措施。
To build the relational model between fundamental characteristics of travelers and trip mode choice, effective measures that impact and guide urban trip mode structure have been studied.
居民出行交通方式选择与个人属性、家庭属性和出行属性之间有较稳定的关系，其随着时间的推移变化甚微。
There are stable relations between trip mode split and personal characteristics, family characteristics and trip characteristics, which change little with the change of time.
在节约时间方面，高速铁路采用高速度、高密度、全天候运行方案，借助市内交通的有机衔接，大幅缩短了点到点旅行时间，改善了人们出行方式的选择。
In saving time, high-speed railway reduced the travel time and improves the traveling condition by using the high speed, high density and all-weather running programs.
而本文是从旅客出行运输方式选择的微观角度来分析旅客出行时间价值的内涵以及大小的。
However, this paper analyzes the time value from the transportation method choosing of passengers when they go out.
交通方式选择是出行行为中最基本的选择行为，对它的分析和预测是交通规划的主要内容之一。
Trip mode choice is the most basic process of travelling, and its analysis and prediction is one of the main elements of traffic and transportation planning.
论文首先对交通信息按不同的分类方法进行了划分，分析了交通信息的质量、发布方式、发布位置等影响出行选择行为的交通信息属性。
Firstly, traffic information has been classified by different standards, the attributes of traffic information, such as the quality, released channel and location, have been analyzed.
研究出行方式选择行为有助于引导私人小汽车出行者改乘轨道交通出行。
Studying travelers' behavior provides information on how to encourage travelers switching from private car to rail transit.
人行道是城市步行交通系统的重要组成部分，其服务水平直接决定出行者对步行出行方式的选择态度。
The sidewalk is an important part of urban pedestrian transportation system, the service quality of which influences the attitude of townspeople towards walk.
由于许多自行车通勤者并不是每天都骑车上下班，所以也考虑了其日常出行方式选择情况，以使用频率表示。
As many bicycle commuters do not cycle every day, we also examine people's daily choices, in terms of frequency.
由于许多自行车通勤者并不是每天都骑车上下班，所以也考虑了其日常出行方式选择情况，以使用频率表示。
As many bicycle commuters do not cycle every day, we also examine people's daily choices, in terms of frequency.
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