城市轨道交通车辆基地站场勘测内容和方法研究

车辆基地是城市轨道交通系统的重要组成部分,针对目前车辆基地勘测设计过程中普遍重设计轻勘测、缺乏系统的站场勘测内容与方法的现状,通过对行业、企业相关勘测规范的理解和归纳,结合自己勘测设计实践,系统论述车辆基地站场勘测内容和方法,主要包括车辆基地基线的测设和应用、地形测量、站场横断面测绘、专项调查与测绘等几方面,掌握车辆基地站场勘测内容和方法将为车辆基地设计与施工、节约用地、降低投资等方面发挥重要的作用。     

Accelerated vehicle retirement program: Estimating the optimal incentive payment in Israel

The paper analyzes two main aspects of the accelerated vehicle retirement program in Israel: the optimal incentive payment of private cars, and the feasibility of expanding the program to include light commercial vehicles. The benefits are the reduction of pollutant emissions and safety benefits, which were compared to the costs of the incentive payment. A differential payment scheme for private vehicles according to the vehicle’s age, is shown to have a higher net benefit than a uniform payment scheme. It is also found that the optimal payment is higher than the existing incentive payment. Additionally, it is found economically feasible to include light commercial vehicles in the program.     

基于Elman网络模型的空中目标识别方法

为了准确、迅速识别空中目标类型,建立基于Elman神经网络的空中目标识别模型。该模型降低了以往空中目标识别方法中的人为因素,提高目标识别结果的可信度和快速性。通过实例验证,证明该模型的有效性和正确性。     

一种新型船舶智能载重测量仪的研究与应用

针对船舶货物卸载重量计量难的现状,开发了一种新型的船舶智能载重测量仪,并提出一种结构树编码免疫辨识算法实现船舶重量模型的辨识,该测量仪通过检测船体前后左右四个位置的吃水深度,精确计算船舶重量、船体倾斜度等数据,实现船舶卸货计量的智能化与自动化.在散装水泥运输船上的应用实践表明,该测量仪能实现比较理想的测量精度,误差小于0.5%,完全能满足船舶运输中对中低价货物的计量要求.     

同步荧光谱法鉴别海上溢油研究

采用同步荧光光谱法对16种油品进行鉴别。实验结果显示,对于不同种类的油品,由于组分特征差异明显,其谱图轮廓,峰-谷位置都有较大的差别,使用同步荧光光谱法很容易就可以区分开。对于同一类型的油品,同步荧光光谱法也能根据油品的特征信息实现鉴别的目的,对于原油,由于其谱图相对复杂,而且有几种原油的谱图接近重合,鉴别起来难度较大,需要借助其他先进的技术手段辅助完成。     

PC连续刚构桥施工控制系统参数识别

系统参数误差是引起PC连续刚构桥悬臂施工控制误差的主要因素之一,因此消除系统参数误差是施工控制的关键所在.酉水河大桥施工监控系统参数识别过程表明,参数识别有利于施工参数的重点监测与调控.     

浅谈高速公路桥头跳车的因素及预防措施

桥头跳车一直是高速公路投入使用后普遍存在的问题,本文通过查阅各种资料及本人施工经验,归纳总结了桥头跳车问题产生的原因,提出了桥头跳车问题的预防措施,以便为今后类似工程的施工提供参考。     

(Unintended) Transport impacts of an energy-environment policy: The case of CNG conversion of vehicles in Dhaka

Motor vehicles are one of the major sources of air pollution in Dhaka, the capital of Bangladesh. The government took various policies to convert the petroleum vehicles on road to run on compressed natural gas (CNG), which allows both air quality improvements and energy security benefits. One of the market friendly policies to encourage the fuel switch was to increase the price differential between CNG and petrol and diesel. This has allowed a wide-scale adoption of CNG as the fuel of choice. However, several years into the policy, there is now a widespread belief among the policymakers that the CNG conversion may have increased car ownership and car travel due to their lower running costs, resulting in more congestion and a reversal of the strategy is on the cards. It is therefore important to test the hypothesis whether CNG conversion had genuinely increased car ownership and car travel in Dhaka city. This paper presents the results of a questionnaire survey and an econometric intervention analysis to understand the impact of CNG conversion on car ownership and car travel in Dhaka. Attention is also given to disentangle the self-selection and price-induced travel effects of CNG conversion. Results show that ownership did not increase, but travel of on-road vehicles increased due to the CNG policy. However, additional congestion costs are still around one half of the health benefits brought about by the policy.     

Order-first split-second methods for vehicle routing problems: A review

Cluster-first route-second methods like the sweep heuristic (Gillett and Miller, 1974) are well known in vehicle routing. They determine clusters of customers compatible with vehicle capacity and solve a traveling salesman problem for each cluster. The opposite approach, called route-first cluster-second, builds a giant tour covering all customers and splits it into feasible trips. Cited as a curiosity for a long time but lacking numerical evaluation, this technique has nevertheless led to successful metaheuristics for various vehicle routing problems in the last decade. As many implementations consider an ordering of customers instead of building a giant tour, we propose in this paper the more general name of ordering-first split-second methods. This article shows how this approach can be declined for different vehicle routing problems and reviews the associated literature, with more than 70 references.     

Evolution of the household vehicle fleet: Anticipating fleet composition, PHEV adoption and GHG emissions in Austin, Texas

In today’s world of volatile fuel prices and climate concerns, there is little study on the relationship between vehicle ownership patterns and attitudes toward vehicle cost (including fuel prices and feebates) and vehicle technologies. This work provides new data on ownership decisions and owner preferences under various scenarios, coupled with calibrated models to microsimulate Austin’s personal-fleet evolution.Opinion survey results suggest that most Austinites (63%, population-corrected share) support a feebate policy to favor more fuel efficient vehicles. Top purchase criteria are price, type/class, and fuel economy. Most (56%) respondents also indicated that they would consider purchasing a Plug-in Hybrid Electric Vehicle (PHEV) if it were to cost $6000 more than its conventional, gasoline-powered counterpart. And many respond strongly to signals on the external (health and climate) costs of a vehicle’s emissions, more strongly than they respond to information on fuel cost savings.Twenty five-year simulations of Austin’s household vehicle fleet suggest that, under all scenarios modeled, Austin’s vehicle usage levels (measured in total vehicle miles traveled or VMT) are predicted to increase overall, along with average vehicle ownership levels (both per household and per capita). Under a feebate, HEVs, PHEVs and Smart Cars are estimated to represent 25% of the fleet’s VMT by simulation year 25; this scenario is predicted to raise total regional VMT slightly (just 2.32%, by simulation year 25), relative to the trend scenario, while reducing CO₂ emissions only slightly (by 5.62%, relative to trend). Doubling the trend-case gas price to $5/gallon is simulated to reduce the year-25 vehicle use levels by 24% and CO₂ emissions by 30% (relative to trend).Two- and three-vehicle households are simulated to be the highest adopters of HEVs and PHEVs across all scenarios. The combined share of vans, pickup trucks, sport utility vehicles (SUVs), and cross-over utility vehicles (CUVs) is lowest under the feebate scenario, at 35% (versus 47% in Austin’s current household fleet). Feebate-policy receipts are forecasted to exceed rebates in each simulation year.In the longer term, gas price dynamics, tax incentives, feebates and purchase prices along with new technologies, government-industry partnerships, and more accurate information on range and recharging times (which increase customer confidence in EV technologies) should have added effects on energy dependence and greenhouse gas emissions.