Connected variable speed limits control and car-following control with vehicle-infrastructure communication to resolve stop-and-go waves

The vision of intelligent vehicles traveling in road networks has prompted numerous concepts to control future traffic flow, one of which is the in-vehicle actuation of traffic control commands. The key of this concept is using intelligent vehicles as actuators for traffic control systems. Under this concept, we design and test a control system that connects a traffic controller with in-vehicle controllers via vehicle-to-infrastructure communication. The link-level traffic controller regulates traffic speeds through variable speed limits (VSL) gantries to resolve stop-and-go waves, while intelligent vehicles control accelerations through vehicle propulsion and brake systems to optimize their local situations. It is assumed that each intelligent vehicle receives VSL commands from the traffic controller and uses them as variable parameters for the local vehicle controller. Feasibility and effectiveness of the connected control paradigm are tested with simulation on a two-lane freeway stretch with intelligent vehicles randomly distributed among human-driven vehicles. Simulation shows that the connected VSL and vehicle control system improves traffic efficiency and sustainability; that is, total time spent in the network and average fuel consumption rate are reduced compared to (uncontrolled and controlled) scenarios with 100% human drivers and to uncontrolled scenarios with the same intelligent vehicle penetration rates.     

不同加载幅值下考虑层间界面条件和侧向剪力作用的柔性铺面响应

该文进行了一个三维有限元参数量化的粘弹性路面响应研究,由于不同的轮胎配置:双轮和宽基轮胎在3种温度(5、25和40℃)和两种速度(8、72 km/h);还有影响路面响应的3种因素:移动车轮荷载幅值(连续,梯形),层间界面条件(简单的摩擦和粘弹性模型)和横向力共同对路面响应的影响进行了研究.研究发现连续加载幅值,不但可以模拟路面对运动轮荷载的响应,并且是一种比目前使用的梯形荷载幅值更准确的研究模型.粘弹性模型极大地提高了双轮胎对预测路面的响应,而简单的摩擦模型更接近宽基轮胎的实地测量.侧向剪力是积极改善预测轮底的表面磨损和底部热拌沥青(沥青)基层的较小程度上的应变.研究表明:使用连续加载幅值和非均匀压力分布模拟移动轮,侧向剪切力和适当的界面摩擦可显著改善有限元模型对车辆加载路面响应的预测能力.     

Exhaust emissions and its control methods in compression ignition engines: A review

Extensive usage of automobiles has certain disadvantages and one of them is its negative effect on environment. Carbon dioxide (CO₂), carbon monoxide (CO), hydrocarbons (HC), oxides of nitrogen (NO_x), sulphur dioxide (SO₂) and particulate matter (PM) come out as harmful products during incomplete combustion from internal combustion (IC) engines. As these substances affect human health, regulatory bodies impose increasingly stringent restrictions on the level of emissions coming out from IC engines. This trend suggests the urgent need for the investigation of all aspects relevant to emissions. It is required to modify existing engine technologies and to develop a better after-treatment system to achieve the upcoming emission norms. Diesel engines are generally preferred over gasoline engines due to their undisputed benefit of fuel economy and higher torque output. However, diesel engines produce higher emissions, particularly NO_x and PM. Aftertreatment systems are costly and occupy more space, hence, in-cylinder solutions are preferred in reducing emissions. Exhaust gas recirculation (EGR) technology has been utilized previously to reduce NO_x. Though it is quite successful for small engines, problem persists with large bore engines and with high rate of EGR. EGR helps in reducing NO_x, but increases particulate emissions and fuel consumption. Many in-cylinder solutions such as lower compression ratios, modified injection characteristics, improved air intake system etc. are required along with EGR to accomplish the future emission norms. Modern combustion techniques such as low temperature combustion (LTC), homogeneous charge compression ignition (HCCI), premixed charge compression ignition (PCCI) etc. would be helpful for reducing the exhaust emissions and improving the engine performance. However, controlling of autoignition timing and achieving wider operating range are the major challenges with these techniques. A comprehensive review of diesel engine performance and emission characteristics is given in this paper.     

Artificial neural network approach to study the effect of injection pressure and timing on diesel engine performance fueled with biodiesel

This study intends to predict the influence of injection pressure and injection timing on performance, emission and combustion characteristics of a diesel engine fuelled with waste cooking palm oil based biodiesel using the artificial neural network (ANN) model. To acquire data for training and testing in the proposed ANN, experiments were carried out in a single cylinder, four stroke direct injection diesel engine at a constant speed of 1500 rpm and at full load (100%) condition. From the experimental results, it was observed that waste cooking palm oil methyl ester provided better engine performance and improved emission and combustion characteristics at injection pressure of 280 bar and timing of 25.5° bTDC. An ANN model was developed using the data acquired from the experiments. Training of ANN was performed based on back propagation learning algorithm. Multilayer perceptron (MLP) network was used for non-linear mapping of the input and output parameters. Among the various networks tested the network with two hidden layers and 11 neurons gave better correlation coefficient for the prediction of engine performance, emission and combustion characteristics. The ANN model was validated with the test data which was not used for training and was found to be very well correlated.     

Computational and experimental investigation of the unsteady flow structures around automotive outside rear-view mirrors

The unsteady flow field around two automotive outside rear-view mirrors is investigated. This study includes comprehensive experimental and computational approaches in order to characterize the complex flow structures in the wake of the mirrors. The experiments were carried out in a wind tunnel which included the measurements of the instantaneous and averaged velocity fields as well as mean and unsteady surface pressure distributions. The simulations were performed using Large Eddy Simulation (LES). The LES approach (particularly with the dynamic subgrid viscosity model) provided good agreements with the experiments for the velocity and the surface pressure distributions. The experimental and the computational results of this study will be used as a benchmark to validate the current and the future CFD development and the subsequent aero-acoustic computations.     

Scantling multi-objective optimisation of a LNG carrier

Numerous real-world problems related to ship design can be solved by various alternatives. However, the scantling design has conflicting objectives such as minimum production cost, minimum weight and maximum moment of inertia (stiffness). Therefore a multi-purpose solution had to be settled in order to meet all these requirements at once. Ship design is a complex endeavour requiring successful coordination of many different disciplines, both technical and non-technical. Basic design is the least defined stage of the ship design process and seeks to define the optimal amidships section structure. For that purpose, recent improvements have been made to a numerical tool in order to optimise the scantling of ship sections by considering production cost, weight and moment of inertia in the optimisation objective function. A multi-criteria optimisation of a LNG carrier is conducted in this paper to illustrate the analysis process. Pareto frontiers are obtained and results have been validated by the Bureau Veritas rules. The methodology presented in this paper has demonstrated its effectiveness in optimising scantling of ships at a very early design stage thanks to a management of critical problems usually studied at a later stage of the design.     

Flexible long range planning using low cost information

Contemporary transport planning requires a flexible modelling approach which can be used to monitor the implementation of a long term plan checking regularly its short term performance with easily available data; the original model is periodically updated using low cost information and this allows the evaluation of the changes to the plan which may be required. Such an approach requires models suited to regular updating and to the use of data from different sources. Models to update trip matrices from traffic counts have been available for some time; however, the estimation and/or updating of other model stages with low cost data has escaped analytical treatment. The paper discusses this idea and formulates the updating problem for an example involving a joint destination/mode choice model under various assumptions about the nature of the available data. Analytical solutions are proposed as well as some general conclusions.requests for offprints     

Seasonality of picophytoplankton chlorophyll a and biomass in the central Cantabrian Sea, southern Bay of Biscay

Seasonal changes in the abundance and biomass of cyanobacteria (Synechococcus and Prochlorococcus) and picoeukaryotes were studied by flow cytometry in the upper layers of the central Cantabrian Sea continental shelf, from April 2002 to April 2006. The study area displayed the typical hydrographic conditions of temperate coastal zones. A marked seasonality of the relative contribution of prokaryotes and eukaryotes was found. While cyanobacteria were generally more abundant for most of the year (up to 2.4 10⁵ cells mL^− 1), picoeukaryotes dominated the community (up to 10⁴ cells mL^− 1) from February to May. The disappearance of Prochlorococcus from spring through summer is likely related to shifts in the prevailing current regime. The maximum total abundance of picophytoplankton was consistently found in late summer–early autumn. Mean photic-layer picoplanktonic chlorophyll a ranged from 0.06 to 0.53 µg L^− 1 with a relatively high mean contribution to total values (33 ± 2% SE), showing maxima around autumn and minima in spring. Biomass (range 0.58–40.16 mg C m^− 3) was generally dominated by picoeukaryotes (mean ± SE, 4.28 ± 0.27 mg C m^− 3) with an average contribution of cyanobacteria of 30 ± 2%. Different seasonality of pigment and biomass values resulted in a clear temporal pattern of picophytoplanktonic carbon to chlorophyll a ratio, which ranged from 10 (winter) to 140 (summer). This study highlights the important contribution of picoplanktonic chlorophyll a and carbon biomass in this coastal ecosystem.     

A new methodology for incident detection and characterization on surface streets

In this paper, a new methodology is presented for real-time detection and characterization of incidents on surface streets. The proposed automatic incident detection approach is capable of detecting incidents promptly as well as characterizing incidents in terms of time-varying lane-changing fractions and queue lengths in blocked lanes, lanes blocked due to incidents, and incident duration. The architecture of the proposed incident detection approach consists of three sequential procedures: (1) Symptom Identification for identification of incident symptoms, (2) Signal Processing for real-time prediction of incident-related lane traffic characteristics and (3) Pattern Recognition for incident recognition. Lane traffic counts and occupancy are the only two major types of input data, which can be readily collected from point detectors. The primary techniques utilized in this paper include: (1) a discrete-time, nonlinear, stochastic system with boundary constraints to predict real-time lane-changing fractions and queue lengths and (2) a pattern-recognition-based algorithm employing modified sequential probability ratio tests (MSPRT) to detect incidents. Off-line tests based on simulated as well as video-based real data were conducted to assess the performance of the proposed algorithm. The test results have indicated the feasibility of achieving real-time incident detection using the proposed methodology.     

Scheduling short-term marine transport of bulk products

A multinational company uses a personal computer to schedule a fleet of coastal tankers and barges transporting liquid bulk products among plants, distribution centres (tank farms), and industrial customers. A simple spreadsheet interface cloaks a sophisticated optimization-based decision support system and makes this system useable via a varity of natural languages. The dispatchers, whose native language is not English, and some of whom presumably speak no English at all, communicate via the spreadsheet, and view recommended schedules displayed in Gantt charts both internationally familiar tools. Inside the spreadsheet, a highly detailed simulation can generate every feasible alternate vessel employment schedule, and an integer linear set partitioning model selects one schedule for each vessel so that all loads and deliveries are completed at minimal cost while satisfying all operational requirements. The optimized fleet employment schedule is displyed graphically with hourly time resolution over a planning horizon of 2-3 weeks. Each vessel will customarily make several voyages and many port calls to load and unload products during this time.