A real-time multi-vehicle simulator for longitudinal controller design

This paper presents a new multi-vehicle simulator for platoon simulation. The main new feature of the developed simulator is a network structure for the real-time simulation of multiple vehicles, each with a detailed powertrain and engine model. It has a small initial delay, which is determined by the number of connected PCs, but the actual simulation is performed and displayed in real-time after this initial and one-time delay. Several longitudinal controllers, including a PID controller with gain scheduling, an adaptive controller, and a fuzzy controller, are also implemented in the simulator. Various system parameters can be modified interactively in the simulator screen, which is very useful for simulating a platoon of heterogeneous vehicles, in which vehicles with different dynamics and different longitudinal controllers may be involved. The simulator provides an excellent tool to develop vehicle longitudinal controllers and to study platoon behaviors. The developed simulator is also effective in testing the effects of nonlinearities neglected in the controller design phase, such as actuator delays and gear shifting schedule.     

Effect of fuel choice on nanoparticle emission factors in LPG-gasoline bi-fuel vehicles

Nanoparticle and gas-phase emission factors are presented for a liquefied petroleum gas (LPG) passenger vehicle and are compared to gasoline operation. A bi-fuel LPG-gasoline vehicle certified for use on either fuel was used as the test vehicle so that a direct comparison of the emissions could be made based on fuel choice. These values were considered along with previous studies to determine the relative change in particulate emissions due to fuel choice over a wide range of vehicles and operating conditions. The vehicle examined in this study was tested on a chassis dynamometer for both steadystate and transient conditions. Transient test cycles included the US FTP72 driving cycle, Japanese driving cycle and modified Indian driving cycle while steady-state tests were done at vehicle speeds ranging from 10–90 km/hr in various transmission gears. Exhaust particle size distributions were measured in real-time using a differential mobility spectrometer (DMS50), and particle number and particle mass emission factors were calculated. For both fuels, the majority of the particles ranged from 5 to 160 nm in terms of particle diameter, with typically more than 85% of the particles in the nucleation mode (between 5–50 nm). In most cases, the vehicle produced a greater fraction of larger (accumulation mode) particles when fuelled on LPG. Using the data in the literature as well as the data in the current study, gasoline fuel produces 4.6 times more particles in terms of number and 2.1 times more particles in terms of mass.     

Small area estimates of daily person-miles of travel: 2001 National Household Transportation Survey

The National Household Transportation Survey (NHTS) was designed at the national level, and for most states it does not have a large enough sample to produce reliable estimates, especially for subdomains (e.g., age groups) within a state. Using the 2001 NHTS, we produced small area estimates (SAEs) of the percentage of persons among four age groups (17 or younger, 18–39, 40–54, and 55 or older) having high daily person-miles of travel (more than 87.5 miles a day, which is the 90th percentile for daily person-miles traveled) and associated prediction intervals for all 50 states and the District of Columbia. The survey weighted hierarchical Bayes (Folsom et al., Proc of the Sect on Surv Res Methods of the Am Stat Assoc 371–375, 1999) small area estimation (SAE) methodology was used to produce state-level SAEs. This paper describes the methodology and shows that SAE can be an effective technique for producing reliable state-level estimates from large, national surveys like the NHTS. In particular, the prediction interval relative widths for SAEs were, on average, 31–48% narrower than the corresponding design-based confidence interval widths, whereas for small states the reduction was around 47–63%.     

Fatigue features extraction of road load time data using the S-transform

This paper presents the algorithm development of a new fatigue data editing technique using S-T approach. In general, the S-transform (S-T) is a time-frequency spectral localization method which performs a multi-resolution analysis on signal. This method represents a better time-frequency resolution especially for non-stationary signal analysis. This technique was developed to produce shortened fatigue data for fatigue durability testing. The S-T method was applied to detect the damaging events contained in the fatigue signals due to high S-T spectrum location. The damaging events were extracted from an original fatigue signal to produce the shortened edited signal which has equivalent fatigue damage. Three types of road load fatigue data were used for simulation purpose, pave track, highway and country road. In this study, an algorithm was developed, to detect the damaging events in the original fatigue signal. The algorithm can be used to extract the fatigue damaging events and these events were combined in order to produce a new edited signal which neglect the low amplitude cycles. The edited signal consists of the majority of the original fatigue damage in the shortened signal with 15–25% time reduction. Thus, it has been suggested that this shortened signal can then be used in the laboratory fatigue testing for the purpose of accelerated fatigue testing.     

Determinants of the damage cost and injury severity of ferry vessel accidents

This study investigates determinants of the property damage cost and injury severity of ferry vessel accidents. Detailed data of individual ferry vessel accidents for the 11-year timeperiod 1991–2001 that were investigated by the U.S. Coast Guard are used to estimate ferry-vessel accident property damage cost and injury severity equations. Tobit regression is used to estimate the former equation and the ordered probit model is used to estimate the latter. Property damage costs include damage costs to the vessel itself, its cargo and contents, and other-property damage (e.g., damage to pier structures and waterfront facilities). Injury severity for a ferry vessel accident is measured as an ordinal variable — no injuries, non-fatal injuries and fatal injuries. Damage cost and injury severity of individual ferry vessel accidents are expressed as functions of the type of vessel accident, vessel characteristics, vessel operation phase, weather/visibility conditions, type of waterway, type of vessel propulsion, type of vessel hull construction and cause of vessel accident. The property damage estimation results suggest that allision, collision and fire ferry vessel accidents incur more vessel property damage cost per vessel gross ton than other types of accidents. The injury severity estimation results suggest that injury severity is greater when the ferry vessel accident is caused by human error as opposed to vessel and environmental factors.     

Vessel accident oil-spillage: Post US OPA-90

The vessel accident oil-spillage literature has focused on oil-cargo vessels, tankers and tank barges, implicitly assuming that these vessels incur greater accident oil-spillage than other (i.e., non-oil-cargo) vessels which just carry oil in their fuel tanks. This study investigates the validity of this assumption for the post US OPA-90 (Oil Pollution Act of 1990) period by investigating determinants of vessel accident oil-spillage, where one of the hypothesized determinants is type of vessel (including both oil-cargo and non-oil-cargo vessels). Tobit regression estimates of vessel accident oil-spillage functions suggest that tank barges have incurred greater in-water and out-of-water oil-spillage for the post OPA-90 period than non-oil-cargo vessels; alternatively, tankers have not incurred greater out-of-water (in-water) oil-spillage than non-oil-cargo vessels (except for freight ships). The policy implication is that greater attention needs to be given to reducing tank barge accident oil-spillage in the post OPA-90 period.     

Ultimate strength analysis of a bulk carrier hull girder under alternate hold loading condition,Part 2: Stress distribution in the double bottom and simplified approaches

This is the second of two companion papers dealing with nonlinear finite element modelling and ultimate strength analysis of the hull girder of a bulk carrier under Alternate Hold Loading (AHL) condition. The methodology for nonlinear finite element modelling as well as the ultimate strength results from the nonlinear FE analyses was discussed in the companion paper (Part 1). The purpose of the present paper is to use the FE results to contribute towards developing simplified methods applicable to practical design of ship hulls under combined global and local loads. An important issue is the significant double bottom bending in the empty hold in AHL due to combined global hull girder bending moment and local loads. Therefore, the stress distributions in the double bottom area at different load levels i.e. rule load level and ultimate failure load level are presented in detail. The implication of different design pressures obtained by different rules (CSR-BC rules and DNV rules) on the stress distribution is investigated. Both (partially) heavy cargo AHL and fully loaded cargo AHL are considered. Factors of influence of double bottom bending such as initial imperfections, local loads, stress distribution and failure modes on the hull girder strength are discussed. Simplified procedures for determination of the hull girder strength for bulk carriers under AHL conditions are also discussed in light of the FE analyses.     

评柯胡《社会、贸易及组织:3世纪至13世纪的闽南》

泉州位于福建沿海,是中国宋元时期著名的港口城市之一,在中国与其他国家发展贸易、文化及外交往来中发挥了重要的作用.目前,有关泉州的各种语言的文献记载和研究,数量还是相当多的,然而,将其置于一个较大的区域性框架下进行考察的研究还比较少见.在本人尚未出版的完成于1982年的博士论文中,就曾作过这方面的尝试.我在自己的论文中,不仅把泉州视作一个繁荣的海港,更把它看作是泉州、漳州、兴化三府区域的中心.[2]柯胡的大著无疑是第一部从此视角来研究泉州的英语学术著作.书中涉及的区域包括福建的南部沿海地区,明清时期多称之为闽南,但作者称之为泉南.     

Improved modeling of park‐and‐ride transfer time: Capturing the within‐day dynamics

An important factor that affects park‐and‐ride demand is transfer time. However, conventional park‐and‐ride demand models treat transfer time as a single value, without considering the time‐of‐day effect. Since early comers usually occupy spots closer to the entrance, their transfer times are shorter. Hence, there is a relationship between arrival time and transfer time. To analyze this relationship, a micro‐simulation model is developed. The model simulates the queuing system at the entrance and the pattern that parking spots are occupied in the parking lot over time. As expected, the model output illustrates an increasing relationship between arrival time and transfer time. This relationship has significant implication in mode choice models because it means that the attractiveness of park‐and‐ride depends on the time of arrival at the park‐and‐ride lot. This model of park‐and‐ride transfer time can potentially improve travel demand forecasting, as well as facilitate the operation and design of park‐and‐ride facilities.