Lane change algorithm for autonomous vehicles via virtual curvature method

This paper addresses the lane changing problem of autonomous vehicles when there is no road infrastructure support. The autonomous vehicle should drive from the current lane to the adjacent lane in the absence of a reference path to guide the vehicle to the new lane. We suggest an algorithm that incorporates a virtual road curvature with bicycle model for lane change guidance. As the name suggests, the virtual road curvature does not physically exist. It is a user assigned radius of a curved path which connects the current lane to the adjacent lane. Since the lateral sensor readings during lane changing maneuver are erroneous, the steering angle along with the virtual curvature is fed into a bicycle model to estimate the lateral position during the transition to the next lane. Details of the algorithm and the virtual road curvature determination are presented in the paper. In contrast to other lane changing methods, controller switching is not required and the same controller is for both lane keeping and lane changing. The algorithm is verified experimentally and the results are comparable with lane changing with physical transition lane.     

美国铁路客车的发展动向与水平

文章阐述了美国地铁、高速列车等轨道车辆的发展水平、动态,以及铁道车辆市场现状。介绍了美国针对铁路事故而开展提高车辆强度、抗碰撞能力的研究及取得的成果。     

Estimation of air–sea CO2 fluxes in the Bay of Biscay based on empirical relationships and remotely sensed observations

An empirical algorithm has been developed to compute the sea surface CO₂ fugacity (fCO₂^sw) in the Bay of Biscay from remotely sensed sea surface temperature (SST_RS) and chlorophyll a (chl a_RS) retrieved from AVHRR and SeaWiFS sensors, respectively. Underway fCO₂^sw measurements recorded during 2003 were correlated with SST_RS and chl a_RS data yielding a regression error of 0.1 ± 7.5 µatm (mean ± standard deviation). The spatial and temporal variability of air–sea fCO₂ gradient (ΔfCO₂) and air–sea CO₂ flux (FCO₂) was analyzed using remotely sensed images from September 1997 to December 2004. An average FCO₂ of ? 1.9 ± 0.1 mol m^? 2 yr^? 1 characterized the Bay of Biscay as a CO₂ sink that is suffering a significant long-term decrease of 0.08 ± 0.05 mol m^? 2 yr^? 2 in its capacity to store atmospheric CO₂. The main parameter controlling the long-term variability of the CO₂ uptake from the atmosphere was the air–sea CO₂ transfer velocity (57%), followed by the SST_RS (10%) and the chl a_RS (2%).     

Propagation and origin of warm anomalies in the Angola Benguela upwelling system in 2001

Warmer than average sea surface temperatures were observed by the Tropical Rainfall Mission Microwave Imager in the Angola Benguela Current system in late austral summer 2001 and persisted for about three months. These coastal anomalies extended offshore by 1 to 4° longitude and were not due to local ocean atmosphere interaction or relaxation of the upwelling favorable southerly winds. Instead, they were remotely forced by ocean atmosphere interaction in the Tropical Atlantic. Satellite remote sensing and a linear ocean model suggest that relaxation of trade winds along the equator triggered Kelvin waves that crossed the basin within a month in early 2001. Westerly wind anomalies were also observed in December 2000 and January 2001 over most of the Tropical Atlantic contributing to a warm preconditioning due to an enhancement of the oceanic annual cycle. This led to abnormal sea level heights near equatorial Africa that propagated southwards along the coast towards the Angola Benguela Frontal zone. This process increased the seasonal penetration of warm and salty water of tropical origin into the Angola Benguela upwelling system.     

A Mean Dynamic Topography of the Mediterranean Sea computed from altimetric data, in-situ measurements and a general circulation model

In the Mediterranean Sea, where the mean circulation is largely unknown and characterized by smaller scales and less intensity than in the open ocean, the interpretation of altimetric Sea Level Anomalies (SLA) is rather difficult. In the context of operational systems such as MFS (Mediterranean Forecasting System) or MERCATOR, that assimilate the altimetric information, the estimation of a realistic Mean Dynamic Topography (MDT) consistent with altimetric SLA to be used to reconstruct absolute sea level is a crucial issue. A method is developed here to estimate the required MDT combining oceanic observations as altimetric and in-situ measurements and outputs from an ocean general circulation model (OGCM).In a first step, the average over the 1993–1999 period of dynamic topography outputs from MFS OGCM provides a first guess for the computation of the MDT. Then, in a second step, drifting buoy velocities and altimetric data are combined using a synthetic method to obtain local estimates of the mean geostrophic circulation which are then used to improve the first guess through an inverse technique and map the MDT field (hereafter the Synthetic Mean Dynamic Topography or SMDT) on a 1/8° resolution grid.Many interesting current patterns and cyclonic/anticyclonic structures are visible on the SMDT obtained. The main Mediterranean coastal currents are well marked (as the Algerian Current or the Liguro–Provenço–Catalan Current). East of the Sicily channel, the Atlantic Ionian Stream divides into several main branches crossing the Ionian Sea at various latitudes before joining at 19°E into a unique Mid-Mediterranean Jet. Also, strong signatures of the main Mediterranean eddies are obtained (as for instance the Alboran gyre, the Pelops, Ierapetra, Mersa-Matruh or Shikmona anticyclones and the Cretan, Rhodes or West Cyprius cyclones). Independent in-situ measurements from Sea Campaigns NORBAL in the North Balearic Sea and the North Tyrrhenian Sea and SYMPLEX in the Sicily channel are used to validate locally the SMDT: deduced absolute altimetric dynamic topography compares well with in-situ observations. Finally, the SMDT is used to compute absolute altimetric maps in the Alboran Sea and the Algerian Current. The use of absolute altimetric signal allows to accurately follow the formation and propagation of cyclonic and anticyclonic eddies in both areas.     

Effective arterial road incident detection: A Bayesian network based algorithm

Timely and accurate incident detection is an essential part of any successful advanced traffic management system. The complex nature of arterial road traffic makes automated incident detection a real challenge. Stable performance and strong transferability remain major issues concerning the existing incident detection algorithms. A new arterial road incident detection algorithm TSC_ar is presented in this paper. In this algorithm, Bayesian networks are used to quantitatively model the causal dependencies between traffic events (e.g. incident) and traffic parameters. Using real time traffic data as evidence, the Bayesian networks update the incident probability at each detection interval through two-way inference. An incident alarm is issued when the estimated incident probability exceeds the predefined decision threshold. The Bayesian networks allow us to subjectively build existing traffic knowledge into their conditional probability tables, which makes the knowledge base for incident detection robust and dynamic. Meanwhile, we incorporate intersection traffic signals into traffic data processing. A total of 40 different types of arterial road incidents are simulated to test the performance of the algorithm. The high detection rate of 88% is obtained while the false alarm rate of the algorithm is maintained as low as 0.62%. Most importantly, it is found that both the detection rate and false alarm rate are not sensitive to the incident decision thresholds. This is the unique feature of the TSC_ar algorithm, which suggests that the Bayesian network approach is advanced in enabling effective arterial road incident detection.     

An analysis of the retail and lifecycle cost of battery-powered electric vehicles

Regulators, policy analysts, automobile manufacturers, environmental groups, and others are debating the merits of policies regarding the development and use of battery-powered electric vehicles (BPEVs). At the crux of this debate is lifecycle cost: the annualized initial vehicle cost, plus annual operating and maintenance costs, plus battery replacement costs. To address this issue of cost, we have developed a detailed model of the performance, energy use, manufacturing cost, retail cost, and lifecycle cost of electric vehicles and comparable gasoline internal-combustion engine vehicles (ICEVs). This effort is an improvement over most previous studies of electric vehicle costs because instead of assuming important parameter values for such variables as vehicle efficiency and battery cost, we model these values in detail. We find that in order for electric vehicles to be cost-competitive with gasoline ICEVs, batteries must have a lower manufacturing cost, and a longer life, than the best lithium-ion and nickel–metal hydride batteries we modeled. We believe that it is most important to reduce the battery manufacturing cost to $100/kWh or less, attain a cycle life of 1200 or more and a calendar life of 12 years or more, and aim for a specific energy of around 100 Wh/kg.