全文获取类型
收费全文 | 1209篇 |
免费 | 92篇 |
专业分类
公路运输 | 382篇 |
综合类 | 529篇 |
水路运输 | 89篇 |
铁路运输 | 101篇 |
综合运输 | 200篇 |
出版年
2024年 | 1篇 |
2023年 | 9篇 |
2022年 | 45篇 |
2021年 | 59篇 |
2020年 | 64篇 |
2019年 | 41篇 |
2018年 | 48篇 |
2017年 | 50篇 |
2016年 | 47篇 |
2015年 | 69篇 |
2014年 | 110篇 |
2013年 | 74篇 |
2012年 | 83篇 |
2011年 | 92篇 |
2010年 | 77篇 |
2009年 | 59篇 |
2008年 | 64篇 |
2007年 | 83篇 |
2006年 | 88篇 |
2005年 | 33篇 |
2004年 | 19篇 |
2003年 | 15篇 |
2002年 | 12篇 |
2001年 | 20篇 |
2000年 | 4篇 |
1999年 | 5篇 |
1998年 | 4篇 |
1997年 | 3篇 |
1996年 | 2篇 |
1995年 | 3篇 |
1994年 | 6篇 |
1993年 | 7篇 |
1992年 | 1篇 |
1991年 | 1篇 |
1989年 | 2篇 |
1987年 | 1篇 |
排序方式: 共有1301条查询结果,搜索用时 15 毫秒
61.
为刻画托运人对港口、运输方式及陆港的联合选择行为,将港口费用、等待时间、班轮频率、货物价值、单次运量、运输成本、运输及通关时间、准班率、陆港服务作为效用变量,构建港口选择位于上层、运输方式及陆港选择位于下层的巢式Logit模型.基于辽宁部分城市集装箱托运人的RP/SP调查数据,对模型参数进行估计和检验.结果表明,低运量倾向选择公路运输,托运人对多式联运的运输成本、运输及通关时间比公路运输的更重视,对公路运输的准班率比多式联运的更重视,陆港服务对多式联运具有显著正向影响,巢式Logit模型比MNL模型具有更优的统计学特征. 相似文献
62.
63.
交通调查者的行为对获取真实、有效的交通运输系统原始数据起着关键性作用.通过对调查者行为的影响因素进行分析,依据行为学理论解释交通调查者的行为机理,并提出交通调查者的行为效应模型,具有十分重要的意义. 相似文献
64.
The concept of rescheduling is essential to activity-based modeling in order to calculate effects of both unexpected incidents and adaptation of individuals to traffic demand management measures. When collaboration between individuals is involved or timetable based public transportation modes are chosen, rescheduling becomes complex. This paper describes a new framework to investigate algorithms for rescheduling at a large scale. The framework allows to explicitly model the information flow between traffic information services and travelers. It combines macroscopic traffic assignment with microscopic simulation of agents adapting their schedules. Perception filtering is introduced to allow for traveler specific interpretation of perceived macroscopic data and for information going unnoticed; perception filters feed person specific short term predictions about the environment required for schedule adaptation. Individuals are assumed to maximize schedule utility. Initial agendas are created by the FEATHERS activity-based schedule generator for mutually independent individuals using an undisturbed loaded transportation network. The new framework allows both actor behavior and external phenomena to influence the transportation network state; individuals interpret the state changes via perception filtering and start adapting their schedules, again affecting the network via updated traffic demand. The first rescheduling mechanism that has been investigated uses marginal utility that monotonically decreases with activity duration and a monotonically converging relaxation algorithm to efficiently determine the new activity timing. The current framework implementation is aimed to support re-timing, re-location and activity re-sequencing; re-routing at the level of the individual however, requires microscopic travel simulation. 相似文献
65.
This paper applies the relatively new method of latent class transition analysis to explore the notion that qualitative differences in travel behavior patterns are substantively meaningful and therefore relevant from explanatory point of view. For example, because the bicycle may function as an important access and egress mode, a car user who also (occasionally) uses the bicycle may be more likely to switch to a public transit profile than someone who only uses the car. Data from the Dutch mobility panel are used to inductively reveal travel behavior patterns and model transitions in these patterns over time. Additionally, the effects of seven exogenous variables, including two important life events (i.e. moving house and changing jobs), on cluster membership and the transition probabilities are assessed. The results show that multiple-mode users compared to single-mode users are more likely to switch from one behavioral profile to another. In addition, age, the residential environment, moving house and changing jobs have strong influences on the transition probabilities between the revealed behavioral patterns over time. 相似文献
66.
Collecting microscopic pedestrian behavior and characteristics data is important for optimizing the design of pedestrian facilities for safety, efficiency, and comfortability. This paper provides a framework for the automated classification of pedestrian attributes such as age and gender based on information extracted from their walking gait behavior. The framework extends earlier work on the automated analysis of gait parameters to include analysis of the gait acceleration data which can enable the quantification of the variability, rhythmic pattern and stability of pedestrian’s gait. In this framework, computer vision techniques are used for the automatic detection and tracking of pedestrians in an open environment resulting in pedestrian trajectories and the speed and acceleration dynamic profiles. A collection of gait features are then derived from those dynamic profiles and used for the classification of pedestrian attributes. The gait features include conventional gait parameters such as gait length and frequency and dynamic parameters related to gait variations and stability measures. Two different techniques are used for the classification: a supervised k-Nearest Neighbors (k-NN) algorithm and a newly developed semi-supervised spectral clustering. The classification framework is demonstrated with two case studies from Vancouver, British Columbia and Oakland, California. The results show the superiority of features sets including gait variations and stability measures over features relying only on conventional gait parameters. For gender, correct classification rates (CCR) of 80% and 94% were achieved for the Vancouver and Oakland case studies, respectively. The classification accuracy for gender was higher in the Oakland case which only considered pedestrians walking alone. Pedestrian age classification resulted in a CCR of 90% for the Oakland case study. 相似文献
67.
Over the past decades there has been a considerable development in the modeling of car-following (CF) behavior as a result of research undertaken by both traffic engineers and traffic psychologists. While traffic engineers seek to understand the behavior of a traffic stream, traffic psychologists seek to describe the human abilities and errors involved in the driving process. This paper provides a comprehensive review of these two research streams.It is necessary to consider human-factors in CF modeling for a more realistic representation of CF behavior in complex driving situations (for example, in traffic breakdowns, crash-prone situations, and adverse weather conditions) to improve traffic safety and to better understand widely-reported puzzling traffic flow phenomena, such as capacity drop, stop-and-go oscillations, and traffic hysteresis. While there are some excellent reviews of CF models available in the literature, none of these specifically focuses on the human factors in these models.This paper addresses this gap by reviewing the available literature with a specific focus on the latest advances in car-following models from both the engineering and human behavior points of view. In so doing, it analyses the benefits and limitations of various models and highlights future research needs in the area. 相似文献
68.
69.
70.