Investigation of tailpipe and evaporative emissions from China IV and Tier 2 passenger vehicles with different gasolines

The limited understanding of vehicular emissions in China, especially evaporative emissions, is one obstacle to establishing tighter standards. To evaluate tailpipe and evaporative emissions, two typical China IV vehicles and one Tier 2 vehicle with an onboard refuelling vapour recovery (ORVR) system were selected and tested. One of the China IV vehicles was fuelled with gasoline, E10 and M15, respectively, to investigate the effect of fuel properties on vehicular emissions. For each vehicle, cold-start tailpipe emission tests were conducted first, followed by an evaporation test. Based on the emission factors and real-world vehicle activity data, the annual tailpipe and evaporative hydrocarbon (HC) emissions of each vehicle were calculated and compared. The results show that E10 and M15 significantly reduced the tailpipe CO and particle number (PN) emissions but seriously aggravated the NOx emissions, especially for M15. The hot soak losses (HSLs) and diurnal breathing losses (DBLs) were slightly impacted by the fuel properties. The annual evaporative emissions with E10 and M15 were higher than that with gasoline. The ORVR system effectively controlled the evaporative emissions, especially for DBLs. Evaporative emissions from the China IV vehicles were 1.1–1.4 times the tailpipe HC emissions. Additionally, the evaporative emission factors of the China IV vehicles were almost 50% lower than the standard (2.0 g/test), whereas their annual evaporative emissions were almost 1.8–2.8 times higher than those from the Tier 2 vehicle. Therefore, controlling evaporative emissions currently remains a great need in China, and the ORVR might be a recommended evaporative control technology.     

Free-floating bike sharing: Solving real-life large-scale static rebalancing problems

Free-floating bike sharing (FFBS) is an innovative bike sharing model. FFBS saves on start-up cost, in comparison to station-based bike sharing (SBBS), by avoiding construction of expensive docking stations and kiosk machines. FFBS prevents bike theft and offers significant opportunities for smart management by tracking bikes in real-time with built-in GPS. However, like SBBS, the success of FFBS depends on the efficiency of its rebalancing operations to serve the maximal demand as possible.Bicycle rebalancing refers to the reestablishment of the number of bikes at sites to desired quantities by using a fleet of vehicles transporting the bicycles. Static rebalancing for SBBS is a challenging combinatorial optimization problem. FFBS takes it a step further, with an increase in the scale of the problem. This article is the first effort in a series of studies of FFBS planning and management, tackling static rebalancing with single and multiple vehicles. We present a Novel Mixed Integer Linear Program for solving the Static Complete Rebalancing Problem. The proposed formulation, can not only handle single as well as multiple vehicles, but also allows for multiple visits to a node by the same vehicle. We present a hybrid nested large neighborhood search with variable neighborhood descent algorithm, which is both effective and efficient in solving static complete rebalancing problems for large-scale bike sharing programs.Computational experiments were carried out on the 1 Commodity Pickup and Delivery Traveling Salesman Problem (1-PDTSP) instances used previously in the literature and on three new sets of instances, two (one real-life and one general) based on Share-A-Bull Bikes (SABB) FFBS program recently launched at the Tampa campus of University of South Florida and the other based on Divvy SBBS in Chicago. Computational experiments on the 1-PDTSP instances demonstrate that the proposed algorithm outperforms a tabu search algorithm and is highly competitive with exact algorithms previously reported in the literature for solving static rebalancing problems in SBSS. Computational experiments on the SABB and Divvy instances, demonstrate that the proposed algorithm is able to deal with the increase in scale of the static rebalancing problem pertaining to both FFBS and SBBS, while deriving high-quality solutions in a reasonable amount of CPU time.     

Definition of wind blowers for vehicles testing at chassis-dyno facilities using a CFD approach

The need to increase measurement accuracy of fuel consumption and pollutant emissions in vehicles is forcing the market to develop chassis-dyno test cells that reproduce on-road conditions realistically.Air-cooling is key to vehicle performance. It is therefore critical that the design of a test cell guarantees realistic cooling of all vehicle components, as important errors in fuel consumption and emissions measurements may otherwise arise. In a test-room, a blower placed in front of the vehicle supplies the cooling air. While there are some guidelines in the literature for the selection of fans required for emissions measurements for standard driving cycles, the information for designing the air supply system for specific tests in other areas is scarce.New Real Driving Emissions (RDE) legislation will force manufacturers to perform on-road measurements of pollutants. This represents a significant challenge due to the variability of conditions coming from non-controlled parameters. In order to optimize vehicles, different tests are performed in cells equipped with a chassis-dyno where the on-road flow field around the vehicle is reproduced as closely as possible.This work provides some guidelines for the definition of the airflow supply system of chassis-dyno facilities for vehicle optimization tests, based on a CFD analysis of the flow characteristics around the vehicle. By comparison with the solution obtained for a vehicle in real road driving conditions, the exit section of the blower and the distance between the blower exit and the car that best reproduce realistic on-road flow conditions in a test room are determined.     

A generic data assimilation framework for vehicle trajectory reconstruction on signalized urban arterials using particle filters

With trajectory data, a complete microscopic and macroscopic picture of traffic flow operations can be obtained. However, trajectory data are difficult to observe over large spatiotemporal regions—particularly in urban contexts—due to practical, technical and financial constraints. The next best thing is to estimate plausible trajectories from whatever data are available. This paper presents a generic data assimilation framework to reconstruct such plausible trajectories on signalized urban arterials using microscopic traffic flow models and data from loops (individual vehicle passages and thus vehicle counts); traffic control data; and (sparse) travel time measurements from whatever source available. The key problem we address is that loops suffer from miss- and over-counts, which result in unbounded errors in vehicle accumulations, rendering trajectory reconstruction highly problematic. Our framework solves this problem in two ways. First, we correct the systematic error in vehicle accumulation by fusing the counts with sparsely available travel times. Second, the proposed framework uses particle filtering and an innovative hierarchical resampling scheme, which effectively integrates over the remaining error distribution, resulting in plausible trajectories. The proposed data assimilation framework is tested and validated using simulated data. Experiments and an extensive sensitivity analysis show that the proposed method is robust to errors both in the model and in the measurements, and provides good estimations for vehicle accumulation and vehicle trajectories with moderate sensor quality. The framework does not impose restrictions on the type of microscopic models used and can be naturally extended to include and estimate additional trajectory attributes such as destination and path, given data are available for assimilation.     

可持续交通——各方观点和长期挑战

从交通研究者和实践者的角度出发,以可持续交通这一概念为中心展开讨论。可持续交通宽泛地反映了可持续发展在交通领域的原则。随着可持续性这一概念的外延逐渐扩大,在它的定义、应用和价值取向上出现了不同观点。着重讨论可持续交通,以及如何理解和运用可持续交通,包括:1)将可持续性或者可持续发展作为一个整体的概念,包括关于可持续性的不同方法和定义之间的冲突;2)对可持续交通以及交通领域对其理解的探索;3)使用指标来实现可持续性的应用。然后识别了通往可持续交通之路的若干挑战,包括缺乏清晰定义、可持续性的固有冲突、可持续发展的跨领域本质、各种工作框架和指标体系、可持续发展的政治因素和交通领域实践中的不同观点。基于在该课题上的研究积累,总结解决这些问题的工作框架,提出因地制宜、注重结果、整体的方法来解决可持续交通中的挑战。     

基于计算机自动控制技术的多探头测深系统研制与改造

通过加装控制盒的方式,实现单探头测深仪与自动控制探头之间的流畅切换,将传统单探头测深仪改造成具有多探头功能的高效水下测量仪器系统,主要用于航道和码头基床等的水下扫测。利用该系统进行的码头基床扫测已经取得成功,可为同类测量设备的改造提供全新的思路。     

论孔子人才观的历史定位与普适价值

孔子的人才观虽然产生于春秋时期动荡的社会背景下,却揭示了人才的最本质内涵———＂仁、智、勇＂。三者作为人才内涵的核心三要素,形成一个内在的三角稳定结构,它能够持久地推动包括成才在内的人的生命境界的发展,因而具有超越时代和社会阶层的普适价值。     

Agent-based simulation framework for mixed traffic of cars,pedestrians and trams

In this paper, we report on the construction of a new framework for simulating mixed traffic consisting of cars, trams, and pedestrians that can be used to support discussions about road management, signal control, and public transit. Specifically, a layered road structure that was designed for car traffic simulations was extended to interact with an existing one-dimensional (1D) car-following model and a two-dimensional (2D) discrete choice model for pedestrians. The car model, pedestrian model, and interaction rules implemented in the proposed framework were verified through simulations involving simple road environments. The resulting simulated values were in near agreement with the empirical data. We then used the proposed framework to assess the impact of a tramway extension plan for a real city. The simulation results showed that the impact of the proposed tramway on existing car traffic would not be serious, and by extension, implied that the proposed framework could help stakeholders decide on expansion scenarios that are satisfactory to both tram users and private car owners.     

Estimating traffic volumes for signalized intersections using connected vehicle data

Recently connected vehicle (CV) technology has received significant attention thanks to active pilot deployments supported by the US Department of Transportation (USDOT). At signalized intersections, CVs may serve as mobile sensors, providing opportunities of reducing dependencies on conventional vehicle detectors for signal operation. However, most of the existing studies mainly focus on scenarios that penetration rates of CVs reach certain level, e.g., 25%, which may not be feasible in the near future. How to utilize data from a small number of CVs to improve traffic signal operation remains an open question. In this work, we develop an approach to estimate traffic volume, a key input to many signal optimization algorithms, using GPS trajectory data from CV or navigation devices under low market penetration rates. To estimate traffic volumes, we model vehicle arrivals at signalized intersections as a time-dependent Poisson process, which can account for signal coordination. The estimation problem is formulated as a maximum likelihood problem given multiple observed trajectories from CVs approaching to the intersection. An expectation maximization (EM) procedure is derived to solve the estimation problem. Two case studies were conducted to validate our estimation algorithm. One uses the CV data from the Safety Pilot Model Deployment (SPMD) project, in which around 2800 CVs were deployed in the City of Ann Arbor, MI. The other uses vehicle trajectory data from users of a commercial navigation service in China. Mean absolute percentage error (MAPE) of the estimation is found to be 9–12%, based on benchmark data manually collected and data from loop detectors. Considering the existing scale of CV deployments, the proposed approach could be of significant help to traffic management agencies for evaluating and operating traffic signals, paving the way of using CVs for detector-free signal operation in the future.     

变邻域搜索求解公共交通乘务调度问题

公共交通乘务调度问题是一个将车辆工作切分为一组合法班次的过程,它是NP难问题,许多求解方法的效率都与班次评价密不可分,本文通过裁剪TOPSIS方法(Technique for Order Preference by Similarity to an Ideal Solution)设计了TOPSIS班次评价方法.此外,通过裁剪变邻域搜索算法使之适合求解乘务调度问题,提出了基于变邻域搜索的乘务调度方法(Crew Scheduling Approach Based on Variable Neighbourhood Search,VNS),其中,并入了TOPSIS班次评价方法在调度过程中进行班次评价,设计了两种带概率的复合邻域结构以增加搜索的多样性,帮助跳出局部最优,在VNS中利用模拟退火算法进行局部搜索.利用中国公共交通中的11组实例进行了测试,测试结果表明,VNS优于两种新近提出的乘务调度方法,且其结果关于班次数接近于下界.