汽车底盘测功机辅助驾驶装置的设计及其系统仿真

针对汽车底盘测功机进行试验时的人为误差因素,提出了辅助驾驶装置的设计方案及其模糊控制策略,并利用MATLAB/SIMULINK工具进行仿真。     

考虑前后多车的网联自动驾驶车辆混流跟驰模型

随着中国新基建战略的提出及自动驾驶和网联通信技术的不断发展,网联自动驾驶车辆(CAV)、自动驾驶车辆(AV)和常规人驾车辆混行的交通流将在未来长时间存在.建立适用于网联自动驾驶车辆、自动驾驶车辆和常规人驾车辆3种类型车辆的混流跟驰模型,考虑多前后车车头间距、多前车速度差、加速度差、与主体车辆的相对距离等因素,并进行典型...     

轻型商用车集成式电子液压制动系统助力策略设计

伴随轻型商用车电动化的发展,用于轻型商用车的线控制动技术得到发展,针对线控制动技术中的集成式电子液压制动系统,提出一种基于模糊PI控制反应盘主副面位移差的制动助力方法.通过实车验证表明:实际反应盘主副面位移差能够快速跟随目标曲线,制动过程平顺,具有实用性.     

公路隧道照明精确检测与智能控制系统研究

为解决公路隧道照明系统节能与行车安全、运营管理之间的矛盾,采用理论分析及实际检验的方法,分析了隧道照明控制系统的调光原理、照明控制系统结构以及亮度检测误差产生的原因,设计了一种可调量程的亮度检测仪并给出校准及亮度检测步骤,解决了公路隧道亮度精确检测的难题,采用模糊神经网络算法在照明系统中进行了实际应用,实践证明本算法在亮度满足实际运营需求的前提下可取得良好的节能效果。     

Quantifying travel time variability at a single bottleneck based on stochastic capacity and demand distributions

Travel time reliability, an essential factor in traveler route and departure time decisions, serves as an important quality of service measure for dynamic transportation systems. This article investigates a fundamental problem of quantifying travel time variability from its root sources: stochastic capacity and demand variations that follow commonly used log-normal distributions. A volume-to-capacity ratio-based travel time function and a point queue model are used to demonstrate how day-to-day travel time variability can be explained from the underlying demand and capacity variations. One important finding is that closed-form solutions can be derived to formulate travel time variations as a function of random demand/capacity distributions, but there are certain cases in which a closed-form expression does not exist and numerical approximation methods are required. This article also uses probabilistic capacity reduction information to estimate time-dependent travel time variability distributions under conditions of non-recurring traffic congestion. The proposed models provide theoretically rigorous and practically useful tools for understanding the causes of travel time unreliability and evaluating the system-wide benefit of reducing demand and capacity variability.     

Classification of Livebus arrivals user behavior

With the increasing use of Intelligent Transport Systems, large amounts of data are created. Innovative information services are introduced and new forms of data are available, which could be used to understand the behavior of travelers and the dynamics of people flows. This work analyzes the requests for real-time arrivals of bus routes at stops in London made by travelers using Transport for London's LiveBus Arrivals system. The available dataset consists of about one million requests for real-time arrivals for each of the 28 days under observation. These data are analyzed for different purposes. LiveBus Arrivals users are classified based on a set of features and using K-Means, Expectation Maximization, Logistic regression, One-level decision tree, Decision Tree, Random Forest, and Support Vector Machine (SVM) by Sequential Minimal Optimization (SMO). The results of the study indicate that the LiveBus Arrivals requests can be classified into six main behaviors. It was found that the classification-based approaches produce better results than the clustering-based ones. The most accurate results were obtained with the SVM-SMO methodology (Precision of 97%). Furthermore, the behavior within the six classes of users is analyzed to better understand how users take advantage of the LiveBus Arrivals service. It was found that the 37% of users can be classified as interchange users. This classification could form the basis of a more personalized LiveBus Arrivals application in future, which could support management and planning by revealing how public transport and related services are actually used or update information on commuters.     

基于SHEL和三角模糊数理论的地铁钻爆法施工安全评价方法研究

为合理应用决策数据中不同专家的背景知识,找出地铁施工过程中安全测评体系的关注重点,根据地铁施工的特点和SHEL安全模型理论,建立以人-软件(L-S)、人-硬件(L-H)、人-环境(L-E)和人-人(L-L)4个环节为基础的钻爆法地铁施工安全指标体系。请专家给出指标语义评价等级和指标权重语义评价等级,并根据其与三角模糊数的对应关系分别得出三角模糊数评价值。针对不同专家的重要性程度差异,提出基于三角模糊数的群一致性评价方法,得出专家综合权重,集结评价数据,最终得到安全评价结果。最后,对青岛地铁1号线过海段进行实例分析。结果表明,该方法可以解决群评价过程中专家个体权威与群体共识难以兼顾的问题,能够充分利用群决策中的原始评价信息,提高地铁施工安全水平评价的准确性。     

Subjective-utility travel time budget modeling in the stochastic traffic network assignment

ABSTRACT

In this article, we propose a new model called subjective-utility travel time budget (SU-TTB) model to capture travelers' risk-averse route choices. In the travel time budget (TTB) and mean-excess travel time (METT) model, a predefined confidence level is needed to capture the risk-aversion in route choice. Due to the day-to-day route travel time variations, the exact confidence level is hard to be predicted. With the SU-TTB model, we assume travelers' confidence level belongs to an interval that they may comply with in the route choice. The two main components of SU-TTB are the utility function and the TTB model. We can show that the SU-TTB can be reduced to the TTB and METT model with proper utility function for the confidence levels. We can also prove its equivalence with our recently proposed nonlinear-expectation route travel time (NERTT) model in some cases and give some new interpretation on the NERTT with this equivalence. Finally, we formulate the SU-TTB model as a variational inequality (VI) problem to model the risk-averse user equilibrium (RAUE), termed as generalized RAUE (GRAUE). The GRAUE is solved via a heuristic gradient projection algorithm, and the model and solution algorithm are demonstrated with the Braess's traffic network and the Nguyen and Dupuis's traffic network.     

Effectiveness of travel time reliability indicators in the light of the assessment of dynamic managed lane strategy

ABSTRACT

The aim of traffic management is to ensure a high quality of service for a maximum number of users by decreasing congestion and increasing safety. Uncertainty of travel times decreases the quality of service and leads end users to modify their plans regardless of the average travel time. Indicators describing travel time reliability are being developed and should be used in the future both for the optimization and for the assessment of active traffic management operations. This article discusses the efficiency of certain reliability indicators in an ex-post assessment of a traffic management strategy. Ex-post assessment is based on an observational before–after study. As some factors other than the studied management strategy may intervene between the two periods, and as most reliability indicators require knowledge of the full travel time distribution and not only its average, a methodology is developed for the identification of the impact of these exogenous factors on the whole distribution. Many reliability indicators are split into different parts allowing the identification of the part due to the management strategy impact. The methodology is tested numerically on a managed lane operation consisting of Hard Shoulder Running (HSR) at rush hour on a section of a French motorway. The variation of some reliability indicators appears misleading, whereas the splitting of the indicators increases our understanding of the strategy and highlights its impact. The paper gives the reliability assessment of the HSR field test and discusses different reliability indicators to identify their potential performances and shortcomings.     

Robust traffic assignment model: Formulation,solution algorithms and empirical application

ABSTRACT

The deterministic traffic assignment problem based on Wardrop's first criterion of traffic network utilization has been widely studied in the literature. However, the assumption of deterministic travel times in these models is restrictive, given the large degree of uncertainty prevalent in urban transportation networks. In this context, this paper proposes a robust traffic assignment model that generalizes Wardrop's principle of traffic network equilibrium to networks with stochastic and correlated link travel times and incorporates the aversion of commuters to unreliable routes.

The user response to travel time uncertainty is modeled using the robust cost (RC) measure (defined as a weighted combination of the mean and standard deviation of path travel time) and the corresponding robust user equilibrium (UE) conditions are defined. The robust traffic assignment problem (RTAP) is subsequently formulated as a Variational Inequality problem. To solve the RTAP, a Gradient Projection algorithm is proposed, which involves solving a series of minimum RC path sub-problems that are theoretically and practically harder than deterministic shortest path problems. In addition, an origin-based heuristic is proposed to enhance computational performance on large networks. Numerical experiments examine the computational performance and convergence characteristics of the exact algorithm and establish the accuracy and efficiency of the origin-based heuristic on various real-world networks. Finally, the proposed RTA model is applied to the Chennai road network using empirical data, and its benefits as a normative benchmark are quantified through comparisons against the standard UE and System Optimum (SO) models.