Stakeholder Perspectives on the Value of Marine Spatial Planning Towards Advancing Offshore Wind in the U.S.

The United States contributes only 0.2% of the 18,814?MW of global installed offshore wind capacity. Lack of development has been attributed in part to a cumbersome regulatory process that includes the evaluation of environmental impacts. Assessments are based on biological, social, and technical data that are often incomplete. Marine spatial planning (MSP) may help fill data gaps. We conducted semi-structured interviews with key informants to understand (1) whether a lack of biological data impedes offshore wind environmental assessments, (2) whether MSP could mitigate these impediments, and (3) whether MSP could advance offshore wind development in the U.S. in other ways. Most informants stated that a lack of biological data in offshore wind environmental assessments was problematic due to incomplete data, uncertainty of data, and mismatched scales. Data issues may be mitigated by creation of data products and increased communication, outcomes of MSP that may benefit the regulatory process by increasing data availability, resolving conflicts among users, and providing a common operating picture. Challenges remain in integrating MSP into the processes of siting and permitting offshore wind, but it provides a strategic framework for the systematic identification, collection, collation, analyses, application, and management of data in the offshore wind environmental regulatory process.     

Forecasting high-speed rail ridership using a simultaneous modeling approach

Abstract

The newly launched, June 2009, US High-Speed Intercity Passenger Rail Program has rekindled a renewed interest in forecasting high-speed rail (HSR) ridership. The first step to the concerted effort by the federal, state, rail, and other related agencies to develop a nationwide HSR network is the development of credible approaches to forecast the ridership. This article presents a nested logit/simultaneous choice model to improve the demand forecast in the context of intercity travel. In addition to incorporating the interrelationship between trip generation and mode choice decisions, the simultaneous model also provides a platform for the same utility function flowing between both the decision-making processes. Using American Travel Survey data, supplemented by various mode parameters, the proposed model improves the forecast accuracy and confirms the significant impact of travel costs on both mode choice and trip generation. Furthermore, the cross elasticity of mode choice and trip generation related to travel costs and other modal characteristics may shed some light on transportation policies in the area of intercity travel, especially in anticipation of HSR development.     

Cycle Network Planning: Towards a Holistic Approach Using Temporal Topology

ABSTRACT

Current cycle-network planning (CNP) at the local level tends to be dominated by a subjective-pragmatic approach in which it is only possible to consider a limited number of route alignment possibilities and development-sequencing scenarios. Although this method may produce acceptable results, it may also be true that the final design could be improved – and the construction efficiency could be enhanced – by a more comprehensive review of the available options in relation to the objectives of the intervention. Such objectives may include accident reduction, modal shift in favour of cycling, health benefits or strategic expansion of a network. This article presents work undertaken to demonstrate a holistic approach to CNP, based on a logically defined spatio-temporal model and allowing some semi-automated multiobjective optimization of network designs in a GIS-based decision-support system. The model is introduced briefly before a case study applying this model to development of a cycle network in a small town in northeast England is described. The results obtained from this case study and the implications of this research for cycle network planners are discussed.     

手持式蠕动泵点胶节省成本

概要螺纹锁固和螺纹密封胶已经成为装配螺纹时保持锁固力和防止漏液最具可靠性和低成本的一种最佳解决方案。大多数用户采用手工点胶的方法直接从原包装内挤出粘合剂．而有时这种方法会导致粘合剂用量过多．并且在窄小处很难点胶。一个简单有效的解决方案就是使用低成本的手持式蠕动泵,将设备直接安装在瓶口上使用。研究表明．使用手持式蠕动泵可降低粘合剂使用量的40％以上。     

Empirical assessment of urban traffic congestion

This paper presents an empirical assessment of urban traffic congestion in Central London, UK. Compared with freeways or motorways, urban networks are relatively less studied because of its complexity and availability of required traffic data. This paper introduces the use of automatic number plate recognition technology to analyze the characteristic of urban traffic congestion in Central London. We also present the use of linear regression to diagnose the observed congestion and attribute them to different causes. In particular, we distinguish the observed congestion into two main components: one due to recurrent factors and the other due to nonrecurrent factors. The methodologies are illustrated through a case study of Central London Area. It is found that about 15% of the observed congestion in the region is due to nonrecurrent factors such as accidents, roadwork, special events, and strikes. Given the significance of London, the study will be valuable for transport policy evaluation and appraisal in other global cities. Copyright © 2013 John Wiley & Sons, Ltd.     

Automatic calibration of fundamental diagram for first‐order macroscopic freeway traffic models

Despite its importance in macroscopic traffic flow modeling, comprehensive method for the calibration of fundamental diagram is very limited. Conventional empirical methods adopt a steady state analysis of the aggregate traffic data collected from measurement devices installed on a particular site without considering the traffic dynamics, which renders the simulation may not be adaptive to the variability of data. Nonetheless, determining the fundamental diagram for each detection site is often infeasible. To remedy these, this study presents an automatic calibration method to estimate the parameters of a fundamental diagram through a dynamic approach. Simulated flow from the cell transmission model is compared against the measured flow wherein an optimization merit is conducted to minimize the discrepancy between model‐generated data and real data. The empirical results prove that the proposed automatic calibration algorithm can significantly improve the accuracy of traffic state estimation by adapting to the variability of traffic data when compared with several existing methods under both recurrent and abnormal traffic conditions. Results also highlight the robustness of the proposed algorithm. The automatic calibration algorithm provides a powerful tool for model calibration when freeways are equipped with sparse detectors, new traffic surveillance systems lack of comprehensive traffic data, or the case that lots of detectors lose their effectiveness for aging systems. Furthermore, the proposed method is useful for off‐line model calibration under abnormal traffic conditions, for example, incident scenarios. Copyright © 2015 John Wiley & Sons, Ltd.