Second best toll and capacity optimisation in networks: solution algorithm and policy implications

This paper looks at the first and second best jointly optimal toll and road capacity investment problems from both policy and technical oriented perspectives. On the technical side, the paper investigates the applicability of the constraint cutting algorithm for solving the second best problem under elastic demand which is formulated as a bilevel programming problem. The approach is shown to perform well despite several problems encountered by our previous work in Shepherd and Sumalee (Netw. Spat. Econ., 4(2): 161–179, 2004). The paper then applies the algorithm to a small sized network to investigate the policy implications of the first and second best cases. This policy analysis demonstrates that the joint first best structure is to invest in the most direct routes while reducing capacities elsewhere. Whilst unrealistic this acts as a useful benchmark. The results also show that certain second best policies can achieve a high proportion of the first best benefits while in general generating a revenue surplus. We also show that unless costs of capacity are known to be low then second best tolls will be affected and so should be analysed in conjunction with investments in the network.

Identifying optimal data aggregation interval sizes for link and corridor travel time estimation and forecasting

With the recent increase in the deployment of ITS technologies in urban areas throughout the world, traffic management centers have the ability to obtain and archive large amounts of data on the traffic system. These data can be used to estimate current conditions and predict future conditions on the roadway network. A general solution methodology for identifying the optimal aggregation interval sizes for four scenarios is proposed in this article: (1) link travel time estimation, (2) corridor/route travel time estimation, (3) link travel time forecasting, and (4) corridor/route travel time forecasting. The methodology explicitly considers traffic dynamics and frequency of observations. A formulation based on mean square error (MSE) is developed for each of the scenarios and interpreted from a traffic flow perspective. The methodology for estimating the optimal aggregation size is based on (1) the tradeoff between the estimated mean square error of prediction and the variance of the predictor, (2) the differences between estimation and forecasting, and (3) the direct consideration of the correlation between link travel time for corridor/route estimation and forecasting. The proposed methods are demonstrated using travel time data from Houston, Texas, that were collected as part of the automatic vehicle identification (AVI) system of the Houston Transtar system. It was found that the optimal aggregation size is a function of the application and traffic condition.

Regulation of the informal transport sector in Rio de Janeiro,Brazil: welfare impacts and policy analysis

In Brazil, the explosion of informal transport activity during the past decade has had profound effects on formal public transport systems and is a source of great controversy in the urban transportation sector. A variety of policies have been proposed to manage the growth of the sector. This study seeks to understand how proposed policies will impact the users of these systems. A corridor in Rio de Janeiro with substantial informal activity was used as a case study. Measures of welfare changes in a discrete choice framework were used to estimate proposed policies’ impacts on users. Eleven candidate policies were evaluated, ranging from the eradication of the informal modes and investment in formal modes, to the legalization of the informal modes. Benefits were compared with costs and the distribution of benefits across income classes was explored. Net benefits from some policies were found to be substantial. Legalizing the informal sector was found to benefit users slightly but further investments in the sector are probably inefficient. Users benefited most from improvements in formal mass transit modes, at roughly 100–200 dollars per commuter per year. Finally, policies to foster a competitive environment for the delivery of both informal and formal services were shown to benefit users about 100 dollars per commuter per year. Together, the regulation of the informal sector and investments in the formal sector serve to reinforce the movement towards competitive concessions for services and help reduce the impacts of cartelization and costly in-road competition.

Tool for Predicting the Ultimate Bending Moment of Ship and Ship-Shaped Hull Girders

The present paper presents a historical review associated with the research works on hull girder strength of ship and ship-shaped structures. Then, a new program is developed to determine the ultimate vertical bending moment of hull girder by applying direct method, stress distribution method, and progressive collapse analysis method. Six ships and ship-shaped structures used in the benchmark study of International Ship and Offshore Structures Congress (ISSC) in 2012 are adopted as examples. The calculation results by applying the developed program are analyzed and compared with the existing results. Finally, the roles of the developed program and its further development are discussed.     

Real-Time Fault Diagnosis for Gas Turbine Blade Based on Output-Hidden Feedback Elman Neural Network

In order to remotely monitor and maintain large-scale complex equipment in real time, China Telecom plans to create a total solution that integrates remote data collection, transmission, storage, analysis and prediction. This solution can provide manufacturers with proactive, systematic, integrated operation and maintenance service, and the data analysis and health forecasting are the most important part. This paper conducts health management for the turbine blades. Elman neural network, and improved Elman neural network, i.e., outputhidden feedback (OHF) Elman neural network are studied as the main research methods. The results verify the applicability of OHF Elman neural network.     

Review of Secure Communication Approaches for In-Vehicle Network

In the connected vehicles, connecting interfaces bring threats to the vehicles and they can be hacked to impact the vehicles and drivers. Compared with traditional vehicles, connected vehicles require more information transfer. Sensor signals and critical data must be protected to ensure the cyber security of connected vehicles. The communications among ECUs, sensors, and gateways are connected by in-vehicle networks. This paper discussed the state-of-art techniques about secure communication for in-vehicle networks. First, the related concepts in automotive secure communication have been provided. Then we have compared and contrasted existing approaches for secure communication. We have analyzed the advantages/disadvantages of MAC and digital signatures for message authentication and compared the performance and limitations of different cryptographic algorithms. Firewall and intrusion detection system are introduced to protect the networks. The constraints and features of different intrusion detection approaches are presented. After that, the technical requirements for cryptographic mechanism and intrusion detection policy are concluded. Based on the review of current researches, the future development directions of the automotive network security have been discussed. The purpose of this paper is to review current techniques on automotive secure communication and suggest suitable secure approaches to implement on the in-vehicle networks.     

Creep Life Prediction of Alloy 718 for Automotive Engine Materials

This study was carried out to investigate the creep life at the high temperature of the Alloy 718 for automotive engine components using the initial strain parameter method (ISPM). Creep tests have performed at elevated temperatures in the range of 550 oC to 700 oC in this work. We also carried out constant stress creep tests. The initial strains were measured during 1 minute after loading. Both the creep stress and rupture time depend on the initial strain. We calculated the creep life of Alloy 718 by using the creep life prediction equations obtained from the ISPM. Then, we compared the creep life predicted by the ISPM to the Larson-Miller parameter (LMP). The experimental rupture time and the calculated rupture time by using the ISPM agreed with a confidence level of 95 %. The creep life predicted by using the ISPM was in very good agreement with the creep life predicted using the LMP method.     

Crew resource management training in the maritime industry: a literature review

The study is based on a literature review of recent empirical research on crew resource management (CRM) training in the maritime industry, organised around what non-technical skills to learn and how. The review indicates that existing work is dominated by individualistic theories of learning with less focus on learning as a social process. Five main categories of skills that need to be trained are identified: assertiveness, decision-making, communication, situation awareness and team coordination. We argue that it is necessary to operationalise these broad concepts further, emphasising the work context and crew-specific needs. The review also shows that a combination of classroom lectures and simulator-based exercises is commonly used in maritime education and training in these skills. The learning effect seems to be suffering from training programmes that are exported ‘as is’ from aviation and not adjusted to the maritime domain or to operation-specific needs. This paper examines maritime crew resource management training from a social learning perspective, involving the view that learning is a context bound, social process that might take place in communities of practice (CoP). A CoP is a group (e.g. a crew) wherein members share an activity and learn from each other. It is argued that CRM training programmes will benefit from including a social learning perspective. Factors that enable the assessment of teams are discussed, and it is argued that the training should be tailored to existing crews, emphasising a learning environment as close to reality as possible.     

Simulation of hydrodynamic performance of drag and double reverse propeller podded propulsors

The unsteady performance of drag and double reverse propeller podded propulsors in open water was numerically simulated using a computational fluid dynamics (CFD) method. A moving mesh method was used to more realistically simulate propulsor working conditions, and the thrust, torque, and lateral force coefficients of both propulsors were compared and analyzed. Forces acting on different parts of the propulsors along with the flow field distribution of steady and unsteady results at different advance coefficients were compared. Moreover, the change of the lateral force and the difference between the abovementioned two methods were mainly analyzed. It was shown that the thrust and torque results of both methods were similar, with the lateral force results having the highest deviation