Reliability and safety analysis methodology for identification of drivers’ erroneous actions

Owing to significantly individual differences in everyday driving behavior, it is quite difficult to assess the relative importance of driver errors compared with vehicle faults or road environment anomalies. This paper briefly presents several basic concepts for analysis of driving dependability including driving errors, driving reliability, driver recovery from erroneous actions, and key factors that shape driving behavior. This presentation is followed by construction of a shaping architecture for driving behavior that consists of a perception stage, a decision-making stage, an execution stage and correlativity among stages, in addition to internal feedback from complex traffic states. The causation classification of driving errors is then discussed in the context of three elemental types: perception error, decision-making error and execution error. The emphasis of this paper is on how to quantify driving dependability in order to identify various erroneous driver actions during traffic accidents. Specifically, this paper proposes a methodology to measure the probability of driving errors by considering the driver recovery from erroneous actions. The purpose of model-based driving dependability analysis is to quantitatively and qualitatively analyze the relationship between driving errors and traffic accidents causations.     

Improved theoretical modeling of a cyclone separator as a diesel soot particulate emission arrester

Particulate matter is considered to be the most harmful pollutant emitted into air from diesel engine exhaust, and its reduction is one of the most challenging problems in modern society. Several after-treatment retrofit programs have been proposed to control such emission, but to date, they suffer from high engineering complexity, high cost, thermal cracking, and increased back pressure, which in turn deteriorates diesel engine combustion performance. This paper proposes a solution for controlling diesel soot particulate emissions by an improved theoretical model for calculating the overall collection efficiency of a cyclone. The model considers the combined effect of collection efficiencies of both outer and inner vortices by introducing a particle distribution function to account for the non-uniform distribution of soot particles across the turbulent vortex section and by including the Cunningham correction factor for molecular slip of the particles. The cut size diameter model has also been modified and proposed by introducing the Cunningham correction factor for molecular slip of the separated soot particles under investigation. The results show good agreements with the existing theoretical and experimental studies of cyclones and diesel particulate filter flow characteristics of other applications.     

Low cost design of parallel parking assist system based on an ultrasonic sensor

This paper presents a low cost design and implementation of a parallel parking assist system (PPAS) based on ultrasonic sensors. Generally, a PPAS requires several types of sensors, such as an ultrasonic sensor, camera sensor, radar sensor and laser sensor for parking space detection. However, our proposed PPAS only requires two ultrasonic sensors on the front and lateral sides for parking space detection. Moreover, a steering angle sensor and wheel speed sensor installed in the vehicle are used to obtain vehicle position information for localization in ultrasonic range data. The hardware architecture of the PPAS based on an electronic control unit (ECU) module, sensor modules and a human machine interface (HMI) module was proposed. Moreover, the software architecture of the PPAS is based on system initialization, scheduling, recognition and a control algorithm. In particular, a novel sensor algorithm was proposed to minimize the vehicle corner error of the ultrasonic sensor. A prototype of the PPAS based on the proposed architecture was constructed. The experimental results demonstrate that the implemented prototype is robust and successfully performs parking space detection and automatic steering control. Finally, the low cost design and implementation of the PPAS was possible due to the cheap ultrasonic sensors, simple hardware design and low computational complexity of the proposed algorithm.     

Digital human body model for seat comfort simulation

Using the recent anthropometry of the North American population, human body models were developed for seat comfort simulation. The external geometry of the models was acquired from the three-dimensional whole body laser scan of recruited volunteers in a driving position. The selection criteria for volunteers with standard size and shape were derived from a statistical factor analysis of the Size USA database. As a practical application of the model in a design process, comfortable driving postures were constructed by adopting the cascade prediction model (CPM), which takes into account both interior package layout and the driver’s anthropometry. The detail modeling process of finite element modeling and its validation results against volunteer measurements are introduced.     

Immigrant status and commute distance: an exploratory study based on the greater Golden Horseshoe

With 8.76 million residents in 2011, the population of Southern Ontario’s Greater Golden Horseshoe (GGH) has grown dramatically over the past decades, driven by net domestic in-migration and immigration. Corresponding to its growth in population, commuting distances and times within the region have grown as well. Yet, despite the number of immigrants that the region attracts on a yearly basis, there is comparatively little information on commute distances. Consequently, this paper examines commuting distance amongst immigrants in the GGH. Specifically, it evaluates commute distance by immigrant status (immigrants and native born), along with how commute distance differs by arrival cohort and ethnic and racial population groups. Results indicate that commute distance increases with increasing duration of residence, with differences by race and ethnicity.     

Multi-agent system with iterative auction mechanism for master bay plan problem in marine logistics

The support of containerization to trade development demands an efficient solution method for the container loading problem in order to reduce shipment and handling time. Hence, the stowage planning of containers is critical to provide speedy delivery of resources from the area of supply to the area of demand. Moreover, information on container terminal activities, structure of ship, and characteristics of containers is distributed among stowage planners. This information imposes constraints, and so the master bay plan problem (MBPP) becomes NP-hard. Therefore, a multi-agent systems (MAS) methodology is designed to effectively communicate the information and solve the MBPP sustainably. In the designed MAS methodology, an information exchange system (IES) is created for stowage planners to bid for ship slots in each experimental iterative combinatorial auction (ICA) market. The winner in the ICA experiments is provided with the ship slots, and the entire bay plan is prepared. Further, the ship-turnaround time is validated using the data obtained from the benchmark problem.     

Port Decision Maker Perceptions on the Effectiveness of Climate Adaptation Actions

Effective adaptation to climate change impacts is rapidly becoming an important research topic. Hitherto, the perceptions and attitudes of stakeholders on climate adaptation actions are under researched, partly due to the emphasis on physical and engineering aspects during the adaptation planning process. Building on such considerations, the paper explores the perceptions of port decision makers on the effectiveness of climate adaptation actions. The findings suggest that while port decision makers are aware of potential climate change impacts and feel that more adaptation actions should be undertaken, they are skeptical about their effectiveness and value. This is complemented by a regional analysis on the results, suggesting that more tailor-made adaptation measures suited to local circumstances should be developed. The study illustrates the complexity of climate adaptation planning and of involving port decision makers under the current planning paradigm.     

Modeling intermodal equilibrium for bimodal transportation system design problems in a linear monocentric city

This paper investigates the intermodal equilibrium, road toll pricing, and bus system design issues in a congested highway corridor with two alternative modes - auto and bus - which share the same roadway along this corridor. On the basis of an in-depth analysis of the demand and supply sides of the bimodal transportation system, the mode choice equilibrium of travelers along the continuum corridor is first presented and formulated as an equivalent variational inequality problem. The solution properties of the bimodal continuum equilibrium formulation are analytically explored. Two models, which account for different infrastructure/system regulatory regimes (public and private), are then proposed. In the public regulatory model, the road toll location and charge level are simultaneously optimized together with the bus service fare and frequency. In the private regulatory model, the fare and frequency of bus services, which are operated by a profit-driven private operator, are optimized for exogenously given toll pricing schemes. Finally, an illustrative example is given to demonstrate the application of the proposed models. Sensitivity analysis of residential/household distribution along the corridor is carried out together with a comparison of four different toll pricing schemes (no toll, first best, distance based, and location based). Insightful findings are reported on the interrelationships among modal competition, market regulatory regimes, toll pricing schemes, and urban configurations as well as their implications in practice.