Model-Based Road Friction Estimation

The tire/road friction coefficient, μ, has a significant role in vehicle longitudinal and lateral control, and there has been associated efforts to measure or estimate the road surface condition to provide additional information for stability augmentation systems of automobiles. In this paper, a model based road friction estimation algorithm is proposed from easily measured signals such as yaw rate and wheel speed. For the development of the estimator, a low order vehicle model incorporated with simple but effective tire model. Field tests of the estimator using actual vehicle measurements show promising results.     

“Not just a taxi”? For-profit ridesharing,driver strategies,and VMT

The spread of GPS-based location services using smartphone applications has led to the rapid growth of new startups offering smartphone-enabled dispatch service for taxicabs, limousines, and ridesharing vehicles. This change in communicative technology has been accompanied by the creation of new categories of car service, particularly as drivers of limousines and private vehicles use the apps to provide on-demand service of a kind previously reserved for taxicabs. One of the most controversial new models of car service is for-profit ridesharing, which combines the for-profit model of taxi service with the overall traffic reduction goals of ridesharing. A preliminary attempt is here made at understanding how for-profit ridesharing compares to traditional taxicab and ridesharing models. Ethnographic interviews are drawn on to illustrate the range of motivations and strategies used by for-profit ridesharing drivers in San Francisco, California as they make use of the service. A range of driver strategies is identified, ranging from incidental, to part-time, to full-time driving. This makes possible a provisional account of the potential ecological impacts of the spread of this model of car service, based on the concept of taxicab efficiency, conceived as the ratio of shared versus unshared miles driven.     

Optimal Suspension Parameter Distributions and Roadway Profiles for Isolation of Heavy Trucks

Heavy trucks are known to have ride problems and are difficult to isolate from roadway unevenness. Heavy trucks are rich in modal density and are stiffly sprung, a combination that makes isolation difficult. Due to their inherent mass, trucks create roadway unevenness as they move along a roadway. Each following truck is excited by the unevenness created by the preceding one, and the road condition worsens over time. It is shown that trucks create roadway profiles from which perfect isolation is possible by having the proper parameter distribution in the suspension units. One distribution is best for rigid body isolation and one is best for 'beaming' isolation.     

Simplical decomposition of the asymmetric traffic assignment problem

This paper presents a convergent simplicial decomposition algorithm for the variational inequality formulation of the asymmetric traffic assignment problem. It alternates between generating minimum path trees based on the cost function evaluated at the current iterate and the approximate solving of a master variational inequality subject to simple convexity constraints. Thus it generalizes the popular Frank-Wolfe method (where the master problem is a line search) to the asymmetric problem. Rules are given for dropping flow patterns which are not needed to express the current iterate as a convex combination of previous patterns. The results of some computational testing are reported.     

Convergence of the Frank-Wolfe method for certain bounded variable traffic assignment problems

In two recent papers published in Transportation Research, Daganzo presented a modification of the Frank-Wolfe algorithm to solve certain link capacitated traffic assignment problems satisfying certain conditions. In order to show convergence of the modified algorithm, the assumption was made that the integral of the volume delay formula for each link tends to infinity as the link flow approaches the link capacity. In this paper we give a Theorem which establishes convergence of the modified algorithm under much weaker conditions. This result is then used to show convergence if the objective function of the assignment model is sufficiently large (not necessarily infinite) when the link flows are at capacity. Thus the modified method is applicable to a broader class of assignment problems. Two numerical examples illustrate (a) when the method converges and when it does not, and (b) that our Theorem provides a weaker condition for convergence of the method.     

Using µ Feedforward for Vehicle Stability Enhancement

A differential braking control strategy using yaw rate feedback, coupled with µ feedforward is introduced for a vehicle cornering on different µ roads. A nonlinear 4-wheel car model is developed. A desired yaw rate is calculated from the reference model based on the driver steering input. It is shown that knowledge of µ offers significant improvement of the vehicle desired trajectory over that of a yaw rate controller alone. Uncertainties and time delay in estimating µ are shown to still yield a system that is superior to using no µ information at all.     

Enhancing the developmental impact of rail transit

A number of forces currently at work in the United States are fostering the rebirth of urban rail transportation. In order to maximize the beneficial economic and developmental impact of future rail investment, certain procedures and techniques must be employed in the planning, design, and implementation of rail systems. The paper offers a set of guidelines and principles for transportation and land use policy makers.     

Public opinion and the environment: Ecology,the coastal zone,and public policy

Abstract

In a public opinion survey conducted in Santa Barbara county, California, respondents were interviewed regarding their feelings on coastal zone development, within a context of broader environmental and political issues.

A high degree of expressed concern for the environment was found, but the data also indicate a widespread reluctance to allocate a greater share of personal income to improve environmental quality.

Among the issues dealt with are citizen views on environmental problems, the effectiveness of government in the environmental field, offshore oil drilling, and coastal zone development.

The results show that on each of the issues analyzed, a person's education, age, and the extent of his political participation are the major factors which determine his concern for the environment. Additional variables appear to have some significance in determining attitudes toward local environmental projects and perceptions of government.

Offered are implications of the findings for the future of organized action on environmental problems.     

Short-line railroad managers discuss their industry

In the United States, the 1980 Staggers Rail Act created a positive regulatory environment for the creation of new short-line railroads. At present there are about 450 of these railroads that have less than 250 miles of trackage. This study asked managers/owners of these railroads two basic questions. First, what do you believe is the single most important trend that is currently taking place in your industry. The most frequently noted trend was the frustration of working with the larger Class 1 railroads. Five additional trends were also identified by the respondents. The second question asked the respondents if they thought the short-line sector of the rail industry will become more or less important in the next ten years and why. About 70% of the owner/managers believed their industry would become more important in the next decade. The most commonly expressed reason for this position is that the Class 1 railroads will increasingly specialize in mainline service only. Three other rationales were also enumerated. For the managers that thought their industry would become less important, the most noted reason was their trackage would not safely transport the newer very heavy bulk commodity freight cars.