Analysis of cost estimation disclosure in environmental impact statements for surface transportation projects

Reliability in cost estimates in publicly funded projects is more important today than ever with increased governmental funding to infrastructure projects and associated accountability requirements, but surface transportation projects, large and small, in the United States have a legacy of cost overruns. The problems with these overruns start with the cost estimation process before projects begin. Studies have shown that early cost estimations reflect best-case scenarios rather than realistic expectations, and have attributed technical, economic, psychological, and political reasons for underestimation. The primary objectives of this research were to determine how costs have been presented and updated in environmental impact statements, to identify endemic technical problems with cost estimation during the environmental review of surface transportation projects, and to develop recommendations for improving cost estimation and disclosure. Cost estimation methods were analyzed from the documents of 100 projects, including draft environmental impact statements, final environmental impact statements, and records of decision. The study concluded that the lack of guidance on how to include cost estimation in environmental review revealed itself in the level of detail and attention given to estimating costs. Agencies omitted or included various aspects of cost estimation randomly. Professional organizations should fill the gap of the need for specific guidance to cost estimation for environmental review so it can evolve as a state of the practice.     

Modeling adoption timing of autonomous vehicles: innovation diffusion approach

Autonomous vehicles (AVs) are expected to act as an economically-disruptive transportation technology offering several benefits to the society and causing significant changes in travel behavior and network performance. However, one of the critical issues that policymakers are facing is the absence of a sound estimation of their market penetration. This study is an effort to quantify the effect of different drivers on the adoption timing of AVs. To this end, we develop an innovation diffusion model in which individuals’ propensities to adopt a new technology such as AVs takes influence from a desire to innovate and a need to imitate the rest of the society. It also captures various sources of inter-personal heterogeneity. We found that conditional on our assumptions regarding the changes in market price of AVs over time, their market penetration in our study region (Chicago metropolitan area) will eventually reach 71.3%. Further, model estimation results show that a wide range of socio-demographic factors, travel pattern indicators, technology awareness, and perceptions of AVs are influential in people’s AV adoption timing decision. For instance, frequent long-distance travelers are found to make the adoption decision more innovatively while those who have experienced an accident in their lifetime are found to be more influenced by word of mouth.     

Discretionary activity location choice: in-home or out-of-home?

This paper examines the location choice associated with discretionary activities (in-home vs. out-of-home). These substitution patterns are important in terms of travel demand as in-home activities do not necessitate travel while out-of-home activities incur travel. Mixed logit models are estimated using an activity dataset (2003 CHASE data) to analyze the factors associated with this choice at the individual activity-level. Results suggest that the attributes of an activity significantly contribute to understanding the likelihood of engaging in out-of-home activities. Activity type interaction terms reveal the varying influence that socio-demographics, activity attributes and travel have over four different activity types modeled. The results reveal that the location choice (in-home vs. out-of-home) is sensitive to travel characteristics. As the travel time and cost increases, an individual is less likely to engage in an activity out-of-home. Compared to passive and social activities, the location of active activities is more sensitive to changes in travel attributes.     

Simulation of the mean zero-up-crossing wave period using artificial neural networks trained with a simulated annealing algorithm

The aim of this work was to develop a predictive model to forecast the mean zero-up-crossing wave periods (T _z ) for 3-hourly sea states at a location in the Pacific using artificial neural networks (ANNs). Seven multilayer ANNs were trained with a simulated annealing algorithm. The output of each trained ANN was used to estimate each of the seven parameters of a new distribution called the hepta-parameter spline proposed for the conditional distribution of T _z , given some mean zero-up-crossing wave periods and significant wave heights. After estimating the parameters of the distribution, the model was used to simulate and predict future values of T _z . Forecasting a sea state and developing the joint distribution of sea state characteristics with the help of the simulated characteristics are also discussed in this article.     

The precautionary principle in maritime affairs

Since the 1980s, the precautionary principle has been drawing more and more international attention. This became particularly clear during the series of Conferences on the Protection of the North Sea, which addressed marine environmental protection, and initiated the application of the principle into maritime affairs. Although a unified concept of the precautionary principle is lacking, some typical formulations have been concluded in regional treaties and international documents, and components of the principle can be summarised (Part I and Part II). The precautionary principle has been adopted by international documents involving different fields of law of the sea, and been addressed by international courts and tribunals (Part III). While the precautionary principle is still not part of customary international law (Part IV), its increasing level of worldwide acceptance suggests that it will become a customary international law in the future.     

Human reliability analysis method on armored vehicle system considering error correction

Human reliability analysis(HRA) is an expansion of man-machine engineering. It is also a new multidisciplinary based on behavioral science, cognitive science, information processing, system analysis and probability statistics in order to analyze, predict, reduce and prevent human errors. Firstly, the quantitative analysis model of HRA is proposed based on Markov process theory by using human error probability(HEP) and error correction cycle(ECC) as parameters. And human reliability evaluation criterion is built. Then, the HRA process considering error correction is proposed based on cognitive reliability and error analysis method(CREAM). Finally, according to the characteristics of armored vehicle system, common performance condition(CPC) in CREAM is improved.A reliability impact index is characterized by the overall contexts of tasks. Human reliability evaluation criterion of armored vehicle system is formulated. And the result of HRA is obtained based on the method presented in this paper. In addition, the relative weights are estimated by combining scale of 10/10—18/2 and analytical hierarchy process(AHP), and the triangular fuzzy number considering confidence factor and optimism index is adopted in order to reduce the subjectivity. The analysis results show that the method presented in this paper is reasonable and feasible. Meantime, the method can provide guidance for human reliability analysis of other weapon systems.     

Dynamic modeling and active control of a strap-on launch vehicle

Dynamic modeling and active control of a strap-on launch vehicle are studied in this paper. In the dynamic modeling, the double-compatible free-interface modal synthesis method is used to establish dynamic model of the system, and its model precision is compared with those of finite element method(FEM), fixedinterface modal synthesis method and free-interface modal synthesis method. In the active control, the swing angle of rocket motor is used as design variable, and the control law design based on the model of mass center motion is adopted to validate the system. Simulation results indicate that the double-compatible model synthesis method can properly approximate the FEM which is used as the benchmark solution, and the model precision of the double-compatible modal synthesis method is obviously higher than those of the fixed-interface and freeinterface modal synthesis methods. Based on the control law design, the deflection of mass center of the launch vehicle is very small.     

A bayesian based process monitoring and fixture fault diagnosis approach in the auto body assembly process

The auto body process monitoring and the root cause diagnosis based on data-driven approaches are vital ways to improve the dimension quality of sheet metal assemblies. However, during the launch time of the process mass production with an off-line measurement strategy, the traditional statistical methods are difficult to perform process control effectively. Based on the powerful abilities in information fusion, a systematic Bayesian based quality control approach is presented to solve the quality problems in condition of incomplete dataset. For the process monitoring, a Bayesian estimation method is used to give out-of-control signals in the process. With the abnormal evidence, the Bayesian network (BN) approach is employed to identify the fixture root causes. A novel BN structure and the conditional probability training methods based on process knowledge representation are proposed to obtain the diagnostic model. Furthermore, based on the diagnostic performance analysis, a case study is used to evaluate the effectiveness of the proposed approach. Results show that the Bayesian based method has a better diagnostic performance for multi-fault cases.     

Deliberative collision avoidance for unmanned surface vehicle based on the directional weight

The purpose of this study is to realize the intelligent deliberative obstacle avoidance for unmanned surface vehicle (USV), based on the International Regulations for Preventing Collisions at Sea called COLREGS. Firstly, a three-level system architecture is designed for the ship intelligent collision avoidance system. Secondly, an intelligent collision avoidance algorithm is presented based on the calculation of motion parameters and the rules of COLREGS. Thirdly, according to COLREGS, the marine environment is modeled from the electronic chart data and radar information, and a deliberative collision avoidance algorithm is written. Finally, the deliberative collision avoidance simulation is carried out for the USV. The feasibility and reliability of intelligent collision avoidance algorithm are verified by the vivid simulation results.     

A dynamic computable general equilibrium simulation of China’s innovation-based economy under the new normal

Researching China’s innovative economic and financial innovation issues under the background of the New Normal, we need to carefully analyze the internal structure and interaction of China’s macroeconomics. The computable general equilibrium (CGE) model has outstanding advantages on predicting the external shock influences on economic system, but previous studies on forecast for China’s future economy mostly considered a high growth rate which is hard to comply with the New Normal scene. By constructing China’s macroeconomic dynamic CGE (DCGE) model and anticipating the economic impact of the New Normal, this paper finds that the New Normal has a certain extent inhibition on China’s macro-economy and innovation. However, after adding the research and development (R&D) subsidy policy, the negative impacts of the New Normal on macro-economy can be eliminated to realize the optimization of economic structure. In addition, after combining the financial innovation promoting policy and the KeQiang index through the simulation of macro-economy, we find that the quality of economic growth is improved. Finally, we provide the policy recommendations for the realization of an innovative economy under China’s New Normal.