The growth of app-based taxi services has disrupted the urban taxi market. It has seen significant demand shift between the traditional and emerging app-based taxi services. This study explores the influencing factors for determining the ridership distribution of taxi services. Considering the spatial, temporal, and modal heterogeneity, we propose a mixture modeling structure of spatial lag and simultaneous equation model. A case study is designed with 6-month trip records of two traditional taxi services and one app-based taxi service in New York City. The case study provides insights on not only the influencing factors for taxi daily ridership but also the appropriate settings for model estimation. In specific, the hypothesis testing demonstrates a method for determining the spatial weight matrix, estimation strategies for heterogeneous spatial and temporal units, and the minimum sample size required for reliable parameter estimates. Moreover, the study identifies that daily ridership is mainly influenced by number of employees, vehicle ownership, density of developed area, density of transit stations, density of parking space, bike-rack density, day of the week, and gasoline price. The empirical analyses are expected to be useful not only for researchers while developing and estimating models of taxi ridership but also for policy makers while understanding interactions between the traditional and emerging app-based taxi services.
The broad application of virtual reality (VR) to medicine has been of great value. The virtual surgery is one of technically difficult applications. With the expansion of the increasingly fine and complicated ear microsurgery, new methods are required to train the doctors. It is necessary and of practical significance to apply VR to the ear micro-operation, which is a functional operation with high precision and great difficulties. In this article,medical VR applications were reviewed. The application of VR to the ear microsurgery was discussed and the virtual ear microsurgery system was designed. 相似文献
Buses are an integral part of the national transportation system of each country. A rollover event is one of the most important
hazards that concerns the safety of the passengers and the crew in a bus. In the past, it was observed after the accident
that the deforming superstructure seriously threatens the lives of the passengers. Thus, the stiffness of the bus frame is
the first thing that needs to be considered. The unfortunate side of strengthening the bus superstructure is that it usually
causes the bus weight to increase. This paper presents an efficient and robust analysis method with which to design the bus
superstructure for a reduction in occupant injuries from rollover accidents while the weight of the strengthened bus is maintained
at the same level. First, the absorbed energy of the bus frame and its components during a rollover were investigated by using
a LS-DYNA numerical study. The highest energy absorption region, which is the side section of the bus frame, was found and
focused on for the investigation of a means to re-distribute the energy-absorption ability of the side frame component. Then
the thickness parameters that were obtained from the re-distribution of the energy-absorption ability were used in the analysis
to optimize the design. Finally, a prototype of the bus with a reasonable thickness for the window pillars and the side wall
bars, which was based on the optimized parameters, was verified to ensure it satisfied ECE R66. In this paper, an effective
usage of materials and an efficient and robust analysis method were presented to design the bus superstructure. Although the
optimization process for increasing the stiffness is simple, this study improves the upper displacement by 39.9% and the lower
displacement by 49.3% (versus the bus survivor space) while maintaining the bus weight at the existing level. 相似文献