全文获取类型
收费全文 | 1757篇 |
免费 | 98篇 |
专业分类
公路运输 | 495篇 |
综合类 | 567篇 |
水路运输 | 121篇 |
铁路运输 | 394篇 |
综合运输 | 278篇 |
出版年
2024年 | 1篇 |
2023年 | 8篇 |
2022年 | 51篇 |
2021年 | 70篇 |
2020年 | 72篇 |
2019年 | 47篇 |
2018年 | 54篇 |
2017年 | 65篇 |
2016年 | 62篇 |
2015年 | 94篇 |
2014年 | 137篇 |
2013年 | 96篇 |
2012年 | 128篇 |
2011年 | 142篇 |
2010年 | 124篇 |
2009年 | 93篇 |
2008年 | 98篇 |
2007年 | 118篇 |
2006年 | 121篇 |
2005年 | 62篇 |
2004年 | 48篇 |
2003年 | 44篇 |
2002年 | 23篇 |
2001年 | 24篇 |
2000年 | 8篇 |
1999年 | 7篇 |
1998年 | 4篇 |
1997年 | 7篇 |
1996年 | 7篇 |
1995年 | 8篇 |
1994年 | 11篇 |
1993年 | 11篇 |
1992年 | 3篇 |
1991年 | 2篇 |
1990年 | 1篇 |
1989年 | 3篇 |
1987年 | 1篇 |
排序方式: 共有1855条查询结果,搜索用时 15 毫秒
81.
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
82.
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
83.
The present paper deals with timetable optimisation from the perspective of minimising the waiting time experienced by passengers when transferring either to or from a bus. Due to its inherent complexity, this bi-level minimisation problem is extremely difficult to solve mathematically, since timetable optimisation is a non-linear non-convex mixed integer problem, with passenger flows defined by the route choice model, whereas the route choice model is a non-linear non-continuous mapping of the timetable. Therefore, a heuristic solution approach is developed in this paper, based on the idea of varying and optimising the offset of the bus lines. Varying the offset for a bus line impacts the waiting time passengers experience at any transfer stop on the bus line.In the bi-level timetable optimisation problem, the lower level is a transit assignment calculation yielding passengers’ route choice. This is used as weight when minimising waiting time by applying a Tabu Search algorithm to adapt the offset values for bus lines. The updated timetable then serves as input in the following transit assignment calculation. The process continues until convergence.The heuristic solution approach was applied on the large-scale public transport network in Denmark. The timetable optimisation approach yielded a yearly reduction in weighted waiting time equivalent to approximately 45 million Danish kroner (9 million USD). 相似文献
84.
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
85.
In this paper, we propose an agent-based simulation approach that is capable of simulating the flow of passengers on board buses and at bus stops. The intention is that it will be applied during vehicle development to analyze how vehicle design affects passenger flow, and thus also how it affects system performance such as dwell time. In turn, this could aid the developers in making design decisions early in the development process. Besides introducing the simulation tool itself, the paper explores the realism of the data generated by the tool. A number of passenger flow experiments featuring a full-scale bus mockup and 50 participants were carried out. The setup of these experiments mirrored a number of ‘bus journeys’ (regarding vehicle design, number of passengers boarding/alighting at each stop and so on) that had previously been simulated using the simulation tool. When the data from the simulations were compared with the data from the passenger flow experiments, it could be concluded that the tool is indeed able to generate realistic passenger flows, although with some errors when a large number of passengers board/alight. The simulated dwell times were rationally affected by the tested bus layout aspects. It was concluded that the tool makes it possible to evaluate how variations in bus layouts affect passenger flow, providing data of sufficiently high quality to be useful in early phases of vehicle design. 相似文献
86.
87.
88.
89.
90.
An analysis of the determinants of children’s weekend physical activity participation 总被引:1,自引:0,他引:1
This paper examines the out-of-home, weekend, time-use patterns of children aged 5–17 years, with a specific emphasis on their
physical activity participation. The impact of several types of factors, including individual and household demographics,
neighborhood demographics, built environment characteristics, and activity day variables, on physical activity participation
is analyzed using a joint nested multiple discrete–continuous extreme value-binary choice model. The sample for analysis is
drawn from the 2000 San Francisco Bay Area Travel Survey. The model developed in the paper can be used to assess the impacts
of changing demographics and built environment characteristics on children’s physical activity levels. 相似文献