85,965 research outputs found
Does ridesourcing impact driving decisions: A survey weighted regression analysis
No full textThe initial public offerings (IPOs) of Uber and Lyft in 2019 marked a milestone for the decade-old ridesourcing. As we start to embrace ridesourcing in our daily life, we also rearrange our daily travel amongst different modes of transportation. As the fundamental decisions in travel behavior, car ownership and car travel should be re-examined in the advent of shared mobility. In this paper, we applied a vehicle choice model that factors in ridesourcing frequency to understand the decisions about (1) how many cars an individual would declare as the primary driver of, and (2) the annual vehicle miles traveled (VMT) for all cars he or she drive. We used a subsample of the latest 2017 National Household Travel Survey (NHTS) data that focus on the Capital region (Washington, D.C. – Maryland – Virginia) as our study area. We applied a weighted regression analysis following the NHTS survey design and derived population-representative results on both decisions. In addition, we calculated the driving cost for each household vehicle based on the latest fuel economy data and incorporated driving cost into the car travel model. The results suggest that ridesourcing is associated with a smaller chance of an individual being the primary driver of a car. However, the elasticity indicates that ridesourcing usage has a small impact on the number of primarily driven cars. Furthermore, ridesourcing has no significant impact on the annual VMT, either. Driving cost, on the other hand, still plays the key role in determining driving distances
Tire-Road Friction Coefficient Estimation Method Design for Intelligent Tires Equipped with Three-Axis Accelerometer
No full textIntelligent tires, as an emerging technology, have great potential for tire-road contact information identification and new vehicle active safety system design. In this article, a tire-road friction coefficient estimation method is proposed based on intelligent tires application with three-axis accelerometer. At first, a finite element tire model with an accelerometer is established using ABAQUS platform. Accelerometer body frame transformation is considered during the tire rotation. Subsequently, the contact patch length is determined according to the peak of the longitudinal acceleration profile. Meanwhile, tire lateral deflection is calculated from the tire lateral acceleration. By curve fitting the lateral deflection model with least square method, tire lateral force and the aligning moment are derived and then the friction coefficient is estimated via brush model. Finally, the effectiveness and accuracy of the proposed estimation method are verified through computer simulation conducted under different road surface conditions
An interpretable machine learning approach to understanding the impacts of attitudinal and ridesourcing factors on electric vehicle adoption
No full textThe global electric vehicle (EV) market has been experiencing an impressive growth in recent times. Understanding consumer preferences on this cleaner, more eco-friendly mobility option could help guide public policy toward accelerating EV adoption and sustainable transportation systems. Previous studies suggest the strong influence of individual and external factors on EV adoption decisions. In this study, we apply machine learning techniques on EV stated preference survey data to predict EV adoption using attitudinal factors, ridesourcing factors (e.g., frequency of Uber/Lyft rides), as well as underlying sociodemographic and vehicle factors. To overcome machine learning models’ low interpretability, we adopt the innovative Local Interpretable Model-Agnostic Explanations (LIME) method to elaborate each factor’s contribution to the predicting outcomes. Besides what was found in previous EV preference literature, we find that the frequent usage of ridesourcing, knowledge about EVs, and awareness of environmental protection are important factors in explaining high willingness of adopting EVs
The Benefits of Being Economics Professor A (and not Z)
No full textAlphabetic name ordering on multi-authored academic papers, which is the convention in the economics discipline and various other disciplines, is to the advantage of people whose last name initials are placed early in the alphabet. As it turns out, Professor A, who has been a first author more often than Professor Z, will have published more articles and experienced afaster growth rate over the course of her career as a result of reputation and visibility. Moreover, authors know that name ordering matters and indeed take ordering seriously: Several characteristics of an author group composition determine the decision to deviate from the default alphabetic name order to a significant extent.performance measurement, incentives, economists, name ordering
Rectification of heat current in Corbino geometry
No full textWe prove analytically the ballistic thermal rectification effect (BTRE) in the Corbino disk characterized by an annular shape. We derive the thermal rectification efficiency (RE) and show that it can be expressed as the product of two independent functions, the first dependent on the temperatures of the heat baths and the second on the system's geometry. It follows that a perfect BTRE can be reached with the increase of the ratios of the heat baths' temperatures and of the radius of the outer edge to the inner edge of the disk. We also show that, by introducing a potential barrier into the Corbino disk, the RE can be greatly improved. Quite remarkably, by an appropriate choice of parameters, the thermal diode effect can be reversed. Our results are robust under variation of the Corbino geometry, which may provide a flexible route to manipulate the heat flow at the nanoscale
Numerical simulation research on Fragmentation effect of hypervelocity impact of ellipsoid shaped projectile normally onto a thin plate
No full textProjectile shape has a crucial influence on the fragmentation of projectile and target subjected to hypervelocity impact. However, most of analytic and empirical models for predicting fragmentation in hypervelocity impact were derived based on spherical projectile. This paper presents a work performed for characterizing fragmentation of aluminum thin plates due to normal incoming aluminum ellipsoid shaped projectile by utilizing smoothed particle hydrodynamics (SPH) methodology. In simulations, the masses of ellipsoid shaped projectiles were fixed as the same, while the aspect ratio was varying from 0.05 to 5, the impact velocity was limited in the range of 3km/s to 7km/s, and the impact attitude was limited in the normal case which the rotational axis of ellipsoid being perpendicular with the target surface. In the postprocess of simulations, critical fragmentation characteristics including the velocity of the leading edge and the expanding velocity of the fragments cloud, perforation hole size, mass and velocity of primary fragment were analysed, with varying impact condition parameters. Furthermore, empirical equations of some fragmentation characteristics were proposed, and the parameters included in the equations were fit with simulation data
Final word on Jersey Dutch
No full textIn this article, William Z. Shetter compares and contrasts the dialects that developed between different Dutch colonies in the New World. He explores in-depth the nuances of Jersey Dutch, and provides theories to explain how Dutch and colonial languages blended. The article is reprinted from American Speech, December 1958, Volum XXXIII, No. 4
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