Optimal traffic assignment to urban streets with air pollution consideration

Traffic assignment is usually determined solely on the basis of minimum travel time through the network. The present study on traffic assignment has taken into account not only traffic performance but also air quality over the street. A simple model of highway air pollution is developed by considering macroscopic material balance of polluted air mass over a segment of a highway that passes through an urban area, A new traffic assignment scheme has been developed based on the air pollution model. The optimal traffic assignment obtained by the new scheme is affected significantly by meteorological conditions.     

Review of computer software for traffic engineers

The mid‐1970s saw the initiation of several lengthy research and development programmes in the United Kingdom which culminated in a range of software for the traffic engineer. The early 1980s brought cheap, powerful microcomputers, thereby enabling the facilities offered by the software to be exploited to the full. This article describes the range of programs now available and in common usage for the design and appraisal of traffic management schemes in the United Kingdom, and suggests a few of the areas where some research and development effort is still needed.     

Joint user and antenna selection for multiuser MIMO downlink with block diagonalization

User selection is necessary for multiuser multiple-input multiple-output (MIMO) downlink systems with block diagonalization (BD) due to the limited free spatial transmit dimensions. The pure user selection algorithms can be improved by performing receive antenna selection (RAS) to increase sum rate. In this paper, a joint user and antenna selection algorithm, which performs user selection for sum rate maximization in the first stage and then performs antenna selection in the second stage, is proposed. The antenna selection process alternately drops one antenna with the poorest channel quality based on maximum determinant ranking (MDR) from the users selected during the first stage and activates one antenna with the maximum norm of projected channel from the remaining users. Simulation results show that the proposed algorithm significantly outperforms the algorithm only performing user selection as well as the algorithm combining user selection with MDR receive antenna selection in terms of sum rate.     

广清城际铁路岩溶发育成因和工程地质条件

对广清城际铁路沿线岩溶发育成因进行分析，对沿线的岩溶发育类型进行划分，进而评价全线岩溶地段的工程地质条件。     

Characteristics of premium transit services that affect mode choice

This research seeks to improve the understanding of the full range of determinants for mode choice behavior and to offer practical solutions to practitioners on representing and distinguishing these characteristics in travel demand forecasting models. The principal findings were that the representation of awareness of transit services is significantly different than the underlying assumption of mode choice and forecasting models that there is perfect awareness and consideration of all modes. Furthermore, inclusion of non-traditional transit attributes and attitudes can improve mode choice models and reduce bias constants. Additional methods and analyses are necessary to bring these results into practice. The work is being conducted in two phases. This paper documents the results of Phase I, which included data collection for one case study city (Salt Lake City), research and analysis of non-traditional transit attributes in mode choice models, awareness of transit services, and recommendations for bringing these analyses into practice. Phase II will include data collection for two additional case study cities (Chicago and Charlotte) with minor modifications based on limitations identified in Phase I, additional analyses where Phase I results indicated a need, and a demonstration of the research in practice for at least one case study city.     

Examining the influence of firm performance on business risk-taking and the mediation effect of scale of operations in the container terminal industry

Container shipping and its related service sectors help accelerate globalization of the world economy. This industry has been experiencing rapid growth, prompting container terminal operators to increase their handling capacity in response. Providing container terminal services requires substantial capital investment in physical assets such as cargo handling facilities and information systems. On the other hand, operating container terminals is a long-term investment that typically spans several business cycles. Hence prudent asset management using appropriate tools is critical for container terminal operators to sustain their businesses. Generally, due to risk-adverseness, investors are unwilling to take more risk in their investment unless they can reap a higher return. Contrary to this argument, this study finds no direct influence of better firm performance as a proxy of higher return on business risk-taking by container terminal operators. Instead, scale of operations is positively associated with business risk-taking, suggesting that container terminal operators with a larger scale of operations are willing to take more business risk.     

Developing green fleet management strategies: Repair/retrofit/replacement decisions under environmental regulation

The considerable cost of maintaining large fleets has generated interest in cost minimization strategies. With many related decisions, numerous constraints, and significant sources of uncertainty (e.g. vehicle breakdowns), fleet managers face complex dynamic optimization problems. Existing methodologies frequently make simplifying assumptions or fail to converge quickly for large problems. This paper presents an approximate dynamic programming approach for making vehicle purchase, resale, and retrofit decisions in a fleet setting with stochastic vehicle breakdowns. Value iteration is informed by dual variables from linear programs, as well as other bounds on vehicle shadow prices. Sample problems are based on a government fleet seeking to comply with emissions regulation. The model predicts the expected cost of compliance, the rules the fleet manager will use in deciding how to comply, and the regulation’s impact on the value of vehicles in the fleet. Stricter regulation lowers the value of some vehicle categories while raising the value of others. Such insights can help guide regulators, as well as the fleet managers they oversee. The methodologies developed could be applied more broadly to general multi-asset replacement problems, many of which have similar structures.     

Impacts of biodiesel blending on freight emissions in the Midwestern United States

We use a combination of petroleum–diesel models, datasets and tools along with biodiesel-specific corrections to create a roadway-level emissions inventory capable of evaluating spatial, temporal and scale aspects of fuel distribution options for the Midwestern US. Specifically, we compare the emissions of a year-round “low-blend” biodiesel implementation scenario, already under consideration in a variety of states, with a more strategic summer-only, interstate-only “high-blend” scenario. Our results indicate that spatial and seasonal distribution decisions do affect the overall emissions impacts of any biodiesel deployment, even those at low-blend levels. However, we also finds that changes in emissions due to biodiesel are considerably smaller than those anticipated from improvements to engine and control technologies.