Fuzzy-logic-based incident detection for signalized diamond interchanges

This paper documents a fuzzy-logic-based incident detection algorithm for signalized urban diamond interchanges. The model is capable of detecting lane-blocking incidents whose effects are manifested by patterns of deterioration in traffic conditions that require adjustments in signal control strategies. As a component of a real-time traffic adaptive control system for signalized diamond interchanges, the algorithm feeds an incident report (i.e., the time, location, and severity of the incident) to the system's optimization manager, which uses that information to determine the appropriate signal control strategy.The performance of the model was studied using a simulation of an actual diamond interchange. The simulation study evaluated the model's performance in terms of detection rate, false alarm rate, and mean time to detect. The model's performance was encouraging, and the fuzzy-logic-based approach is considered promising.     

The performance of route modification and demand stabilization strategies in stochastic vehicle routing

A key concern in managing vehicle routing operations under stochastic demands is whether, on the basis of travel distance, route modification yields materially greater logistical efficiency than fixed routes. This research uses statistical calibration as the primary technique to develop a robust and tractable model for estimating this difference in logistical efficiency. Based on features such as the models predictive accuracy and generalizability, it constitutes a substantive improvement over existing models. The present study also expands the range of predictive models relevant to vehicle routing under stochastic demands with models to estimate the transportation and inventory effects of persuading customers to stabilize their ordering patterns.     

The simple,compelling case for PRT

When compared with existing urban modes, Personal Rapid Transit (PRT) offers compelling advantages in every important respect. The desirable attributes of any urban mobility mode are well documented, such as minimal travel time, safety, comfort, low cost, and minimal impacts. These attributes are used to define a hypothetical, ideal urban mode. The ideal mode would possess characteristics such as no waiting, no stops, from anywhere to anywhere service, risk-free, non-polluting, and accessible to everyone at any time. Although not attainable in the real world, the ideal provides a model and benchmark for design much as the Carnot thermodynamic cycle guides the development of internal combustion engines, or ideal gases and perfect fluids are postulated in physics. A matrix format is used to present the characteristics of various modes against the desirable attributes of any mode. Modes presented are the ideal, walking, bicycles, motorcycles, automobiles, taxis, buses, rail transit, Automated Guideway Transit (AGT), and PRT. In all respects, PRT is shown to approach the ideal much more closely than competing modes.     

地面注汽管线表面散热损失影响因素分析

文中采用Fluent模拟与理论计算结合比较的方法,研究了不同因素对蒸汽管道散热损失的影响规律,并分析了理论计算模型的相对误差.发现增加注汽管线距地面高度,对其散热损失影响较弱;空气温度升高,注汽管道表面散热损失降低;风速和表面发射率对注汽管线表面热损失影响较大;数值模拟结果与理论计算数据相对误差较大.     

Approximate algorithms for the discrete network design problem

The discrete network design problem is one of finding a set of feasible actions (projects) from among a collection of possible actions, that when implemented, optimizes some objective function(s). This is a combinatorial optimization problem that is very expensive to solve exactly. This paper proposes two algorithms for obtaining approximate solutions to the discrete network design problem with much less computational effeort. The computational savings are achieved by approximating the original problem with a new formulation which is easier to solve. The first algorithm proposed solves this approximate problem exactly, while the second is even more efficient, but provides only a near-optimal solution to the approximate problem. Experience with test problems indicates that these approximations can reduce the computational effort by a factor of 3–5, with little loss in solution accuracy.     

An application of variance reduction techniques in freeway simulation

Computer simulation models are used in a variety of applications in transportation engineering and have become a prime aid in decision making. The applications range from evaluating traffic control strategies for single intersections to such complex decision processes as evaluating the impact of removing toll facilities at the George Washington Bridge in New York City. While it is widely accepted that simulation offers an unmatchable capability of evaluating alternate control policies, the high variance of the output variable presents a critical problem in such comparative analyses. The simulation models with high output variance must be run longer or replicated many times to achieve a desired precision level, and that corresponds to increased cost of computer resources. This paper describes and illustrates the application of variance reduction concepts that can improve the reliability and efficiency of the simulation experimental process by taking advantage of the simulation model structure. The two variance reduction concepts (common random numbers and antithetic variates) reduce the variance of the output variable by replacing the original sampling procedure with a new procedure that yields the same expected value but with a smaller variance. The application of the variance reduction concept was illustrated using results from experiments with a freeway simulation model. The results indicate that both common random numbers and antithetic variates sampling procedures appreciably reduce the variance of the simulation output measure.     

The construction and use of continuous autoregressive models for traffic indices

This article discusses the use of continuous autoregressive models to describe the behavior of traffic indices. From discretely sampled data, second-order differential equation models are constructed to represent dynamic traffic fluctuations as the response of a linear system to a stochastic forcing function. The results are compared to the more common M/G/∞ queueing model approach, and the analysis is demonstrated on time series of aircraft concentration in thirty-one enroute air traffic control sectors.