Pareto-improving and revenue-neutral congestion pricing schemes in two-mode traffic networks

This paper studies a Pareto-improving and revenue-neutral congestion pricing scheme on a simple two-mode (highway and transit) network: this scheme aims at simultaneously improving system performance, making every individual user better off, and having zero total revenue. Different Pareto-improving situations are explored when a two-mode transportation system serves for travel groups with different value-of-time (VOT) distributions. Since the congestion pricing scheme suggested here charges transit users negative tolls and automobile users positive tolls, it can be considered as a proper way to implement congestion pricing and transit subsidy in one step, while offsetting the inequity for the poor. For a general VOT distribution of commuters, the condition of Pareto-improving is established, and the impact of the VOT distribution on solving the inequity issue is explored. For a uniform VOT distribution, we show that a Pareto-improving and revenue-neutral pricing scheme always exists for any target modal split pattern that reduces the total system travel time

User Heterogeneity and Bi-criteria System Optimum

For a traffic network with fixed demand of heterogeneous users in terms of their different values of time (VOT), the system performance can be measured either in time unit by the total system travel time (in short, system time), or in monetary unit by the total system travel cost (in short, system cost). Thus we have two different objectives for network optimization, i.e., to minimize system time and to minimize system cost, which naturally gives rise to a bi-objective minimization problem. A Pareto optimum of this bi-objective optimization problem represents a bi-criteria system optimum for network optimization in the sense that, at each Pareto optimum, neither system time nor system cost can be further reduced without increasing the other one. In this paper, we prove that any Pareto optimum can be decentralized into multi-class user equilibrium by positive anonymous link tolls. We then bound the system performance gap when optimized by the two different criteria. Specifically, we provide answers to the following questions: when system time is minimized, how far could the corresponding system cost deviate from its minimum value; conversely, when system cost is minimized, how far could the corresponding system time deviate from its minimum value; and more generally, how far can the system time and system cost at a given bi-criteria Pareto optimum deviate from their respective single-criterion based system optimum

On the Tate Conjecture in Codimension One for Varieties with h2,0=1h^{2, 0} = 1 in Positive Characteristics

We prove that the Tate conjecture in codimension $1$ is ``generically true'' for mod $p$ reductions of complex projective varieties with $h^{2, 0} = 1$, under a mild assumption on moduli. By refining this general result, we prove in characteristic $p \ge 5$ the BSD conjecture for a height $1$ elliptic curve $\mathcal{E}$ over a function field of genus $1$, assuming that the singular fibers in its minimal compactification are all irreducible. We also prove the Tate conjecture for algebraic surfaces with $p_g = K^2 = 1$, $q = 0$ and an ample canonical bundle in characteristic $p \ge 5$.Comment: 69 pages. Major Revision. Generalized the results to finitely generated fields. Considerations of conjugate Shimura varieties were replaced by a simpler trick involving the Grothendieck restriction functor. A minor mistake in the previous treatment of the non-maximal monodromy case was correcte

Bounding the inefficiency of logit-based stochastic user equilibrium

Bounding the inefficiency of selfish routing has become an emerging research subject. A central result obtained in the literature is that the inefficiency of deterministic User Equilibrium (UE) is bounded and the bound is independent of network topology. This paper makes a contribution to the literature by bounding the inefficiency of the logit-based Stochastic User Equilibrium (SUE). In a stochastic environment there are two different definitions of system optimization: one is the traditional System Optimum (SO) which minimizes the total actual system travel time, and the other is the Stochastic System Optimum (SSO) which minimizes the total perceived travel time of all users. Thus there are two ways to define the inefficiency of SUE, i.e. to compare SUE with SO in terms of total actual system travel time, or to compare SUE with SSO in terms of total perceived travel time. We establish upper bounds on the inefficiency of SUE in both situations

Knowledge and Structure of China\u27s Procedural Law From the Liu Yongan Incident (Chinese)

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Characterization of geolocation accuracy of Suomi NPP Advanced Technology Microwave Sounder measurements

The Advanced Technology Microwave Sounder (ATMS) onboard Suomi National Polar-orbiting Partnership satellite has 22 channels at frequencies ranging from 23 to 183 GHz for probing the atmospheric temperature and moisture under all weather conditions. As part of the ATMS calibration and validation activities, the geolocation accuracy of ATMS data must be well characterized and documented. In this study, the coastline crossing method (CCM) and the land-sea fraction method (LFM) are utilized to characterize and quantify the ATMS geolocation accuracy. The CCM is based on the inflection points of the ATMS window channel measurements across the coastlines, whereas the LFM collocates the ATMS window channel data with high-resolution land-sea mask data sets. Since the ATMS measurements provide five pairs of latitude and longitude data for K, Ka, V, W, and G bands, respectively, the window channels 1, 2, 3, 16, and 17 from each of these five bands are chosen for assessing the overall geolocation accuracy. ATMS geolocation errors estimated from both methods are generally consistent from 40 cases in June 2014. The ATMS along-Track (cross-Track) errors at nadir are within ±4.2 km (±1.2 km) for K/Ka, ±2.6 km (±2.7 km) for V bands, and ±1.2 km (±0.6 km) at W and G bands, respectively. At the W band, the geolocation errors derived from both algorithms are probably less reliable due to a reduced contrast of brightness temperatures in coastal areas. These estimated ATMS along-Track and cross-Track geolocation errors are well within the uncertainty requirements for all bands. © 2016. American Geophysical Union. All Rights Reserved