Although the improvement of well-being is often an implicitly-assumed goal of many, if not most, public policies, the study of subjective well-being (SWB) and travel has so far been confined to a relatively small segment of the travel behavior community. Accordingly, one main purpose of this paper is to introduce a larger share of the community to some fundamental SWB-related concepts and their application in transportation research, with the goal of attracting others to this rewarding area of study. At the same time, however, I also hope to offer some useful reflections to those already working in this field. After discussing some basic issues of terminology and measurement of SWB, I present from the literature four conceptual models relating travel and subjective well-being. Following one of those models, I review five ways in which travel can influence well-being. I conclude by examining some challenges associated with assessing the impacts of travel on well-being, as well as challenges associated with applying what we learn to policy.
Map-matching (MM) algorithms integrate positioning data from a Global Positioning System (or a number of other positioning sensors) with a spatial road map with the aim of identifying the road segment on which a user (or a vehicle) is travelling and the location on that segment. Amongst the family of MM algorithms consisting of geometric, topological, probabilistic and advanced, topological MM (tMM) algorithms are relatively simple, easy and quick, enabling them to be implemented in real-time. Therefore, a tMM algorithm is used in many navigation devices manufactured by industry. However, existing tMM algorithms have a number of limitations which affect their performance relative to advanced MM algorithms. This paper demonstrates that it is possible by addressing these issues to significantly improve the performance of a tMM algorithm. This paper describes the development of an enhanced weight-based tMM algorithm in which the weights are determined from real-world field data using an optimisation technique. Two new weights for turn-restriction at junctions and link connectivity are introduced to improve the performance of matching, especially at junctions. A new procedure is developed for the initial map-matching process. Two consistency checks are introduced to minimise mismatches. The enhanced map-matching algorithm was tested using field data from dense urban areas and suburban areas. The algorithm identified 96.8% and 95.93% of the links correctly for positioning data collected in urban areas of central London and Washington, DC, respectively. In case of suburban area, in the west of London, the algorithm succeeded with 96.71% correct link identification with a horizontal accuracy of 9.81 m (2σ). This is superior to most existing topological MM algorithms and has the potential to support the navigation modules of many Intelligent Transport System (ITS) services. 相似文献
Estimation of origin-destination (OD) matrices from link count data is a challenging problem because of the highly indeterminate relationship between the observations and the latent route flows. Conversely, estimation is straightforward if we observe the path taken by each vehicle. We consider an intermediate problem of increasing practical importance, in which link count data is supplemented by routing information for a fraction of vehicles on the network. We develop a statistical model for these combined data sources and derive some tractable normal approximations thereof. We examine likelihood-based inference for these normal models under the assumption that the probability of vehicle tracking is known. We show that the likelihood theory can be non-standard because of boundary effects, and provide conditions under which such irregular behaviour will be observed in practice. For regular cases we outline connections with existing generalised least squares methods. We then consider estimation of OD matrices under estimated and/or misspecified models for the probability of vehicle tracking. Theoretical developments are complemented by simulation experiments and an illustrative example using a section of road network from the English city of Leicester. 相似文献
Within the frame of a Sino-German Joint Research Program, two cruises of “R/V Dong Fang Hong 2” were carried out in September–October 1998 and April–May 1999, respectively, to understand the dynamics of nutrients in the Bohai. Nutrient species (NO3−, NO2−, NH4+, PO43− and SiO32−) are determined colorimetrically on board for five anchor and 30 grid stations. In situ incubation experiments are performed to determine planktonic nutrient uptake and benthic exchange flux. Nutrient concentrations display short-term variability and seasonal change in the Bohai, with higher levels in shallow coastal waters than in the Central Bohai. The influence of riverine discharge on nutrient levels can be seen from salinity isopleths, nutrient distribution and species ratios. Near-bottom (nb) waters have similar nutrient concentrations as to the surface waters in the Central Bohai, whereas stratification takes place in the Bohai Strait and North Yellow Sea. In situ incubation experiments provide evidence that the uptake ratio (i.e. N, P) by phytoplankton is proportional to the ratios among nutrient species in ambient waters. Based on the data of this study and previously publications, a preliminary estimate of nutrient budgets via riverine input and atmospheric deposition is established. The results indicate that atmospheric deposition gains importance over rivers in delivering nutrients into the Bohai and sustain the new production, following recent decrease in riverine inflow caused by drought periods in North China and damming practices. A historical review of nutrient data indicates that concentrations of nitrogen increase and phosphorus and silica decrease in the Central Bohai over last 40 years. This potentially has an important influence on the health of ecosystem in Bohai (e.g. food web and community structure), though further study is needed to examine the scenario in more detail. 相似文献