基于Simulink的轮边驱动电动车振动分析与仿真

为解决轮边驱动电动车安全性和平顺性低的问题,文章以基于吸振原理的轮边驱动电动车垂向3自由度系统为例,运用机械振动学原理建立动力学微分方程,采用状态空间法将此系统的微分方程转化为便于Matlab/Simulink软件仿真的模型。通过分析和仿真可以直接获得轮边驱动电动车沿垂直地面方向的运动曲线图,在正弦激励作用下,动力吸振器、车轮及车身均作周期性运动。将机械振动学和Simulink软件相结合能够准确方便地对轮边驱动电动车的振动进行分析与仿真,为处理类似的汽车振动系统仿真提供了参考。     

Generalized extreme value (GEV)-based error structures for multiple discrete-continuous choice models

This paper formally derives the class of multiple discrete-continuous generalized extreme value (MDCGEV) models, a general class of multiple discrete-continuous choice models based on generalized extreme value (GEV) error specifications. Specifically, the paper proves the existence of, and derives the general form of, closed-form consumption probability expressions for multiple discrete-continuous choice models with GEV-based error structures. In addition to deriving the general form, the paper derives a compact and readily usable form of consumption probability expressions that can be used to estimate multiple discrete-continuous choice models with general cross-nested error structures.The cross-nested version of the MDCGEV model is applied to analyze household annual expenditure patterns in various transportation-related expenses using data from a Consumer Expenditure Survey in the United States. Model estimation results and predictive log-likelihood based validation tests indicate the superiority of the cross-nested model over the mutually exclusively nested and non-nested model specifications. Further, the cross-nested model was amenable to the accommodation of socio-demographic heterogeneity in inter-alternative covariance across decision-makers through a parameterization of the allocation parameters.     

Estimation of mean and covariance of stochastic multi-class OD demands from classified traffic counts

This paper proposes a new model to estimate the mean and covariance of stochastic multi-class (multiple vehicle classes) origin–destination (OD) demands from hourly classified traffic counts throughout the whole year. It is usually assumed in the conventional OD demand estimation models that the OD demand by vehicle class is deterministic. Little attention is given on the estimation of the statistical properties of stochastic OD demands as well as their covariance between different vehicle classes. Also, the interactions between different vehicle classes in OD demand are ignored such as the change of modes between private car and taxi during a particular hourly period over the year. To fill these two gaps, the mean and covariance matrix of stochastic multi-class OD demands for the same hourly period over the year are simultaneously estimated by a modified lasso (least absolute shrinkage and selection operator) method. The estimated covariance matrix of stochastic multi-class OD demands can be used to capture the statistical dependency of traffic demands between different vehicle classes. In this paper, the proposed model is formulated as a non-linear constrained optimization problem. An exterior penalty algorithm is adapted to solve the proposed model. Numerical examples are presented to illustrate the applications of the proposed model together with some insightful findings on the importance of covariance of OD demand between difference vehicle classes.     

A static free-floating bike repositioning problem with multiple heterogeneous vehicles,multiple depots,and multiple visits

In this paper, a bike repositioning problem with multiple depots, multiple visits, and multiple heterogeneous vehicles for the free-floating bike-sharing system (FFBSS) is studied. Two types of nodes (i.e., easily and hardly access nodes) with different penalties are defined to represent different convenience levels of getting bikes from the FFBSS. The objective of the repositioning is to minimize the weighted sum of the inconvenience level of getting bikes from the system and the total unmet demand and the total operational time. To solve this problem, an enhanced version of chemical reaction optimization (CRO) is developed. A loading and unloading quantity adjustment procedure with the consideration of the node characteristics, including the type of node and its current state (i.e., in a balanced, surplus, or deficit state) is proposed and incorporated into this version to improve its solution quality. A concept of the nearby-node set is also proposed to narrow the search space. Numerical results are presented and indicate that compared to the traditional CRO and CPLEX, the enhanced CRO improves solution quality and has potential to tackle the repositioning problem for larger, longer repositioning duration, and more vehicle instances. The results also demonstrate the effectiveness of the proposed adjustment procedure.     

How much is too much for tolled road users: Toll saturation and the implications for car commuting value of travel time savings?

The current practice of forecasting the demand for new tolled roads typically assumes that car users are prepared to pay a higher toll for a shorter journey, and they will keep doing so as long as the toll cost is not higher than their current value of travel time savings. Practice ignores the possibility that there could be a point when motorists stop driving on toll roads due to a toll budget constraint. The unconstrained toll budget assumption may be valid in networks where the addition of a new toll road does not result in a binding budget constraint that car users may have for using toll roads (although it could also be invoked for existing tolled routes through a reduction in use of a tolled route). In a road network like Sydney which offers a growing number of (linked) tolled roads, the binding budget constraint may be invoked, and hence including additional toll links might in turn reduce the car users’ willingness to pay for toll roads to save the same amount of travel time. When this occurs, car users are said to reach a toll saturation point (or threshold) and begin to consider avoiding one or more toll roads. Whilst toll saturation has important implications for demand forecasting and planning of toll roads, this type of behaviour has not been explored in the literature. We investigate the influence that increasing toll outlays has on preferences of car commuters to use one or more tolled roads as the number of tolled roads increases. The Sydney metropolitan area offers a unique laboratory to test this phenomenon, with nine tolled roads currently in place and another five in planning. The evidence supports the hypothesis that the value of travel time savings decreases as a consequence of toll saturation.     

Impacts of accident severity factors and loss values of crashes on expressways in Thailand

The number of road accidents and the level of accident severity have been extensively applied as the indicators for measuring the efficiency of service provision in road network systems of each country. This research utilized accident data on expressway networks during B.E.2550 (2007) to B.E.2553 (2010) (updated data was collected), in which Expressway Authority of Thailand (EXAT) as legislatively mandated unit has taken responsibility for the execution of nine expressway routes covering distances totaling over 207 km with a record of 2194 crashes. The chief objective of the study aims to forecast the accident severity through formulating Multiple Logistic Regression Model to analyze the probability of injury accident and fatal accident in comparison with property damage only accident. Its measurement comprehensively considers statistical relationship among variables such as average speed on road section, average traffic volume per day, period of time, weather conditions, physical characteristics of accident area, and causes of accident. Together, the research question is to verify whether these variables affect the opportunity or probability of three levels of accidents and investigate impacts of accident loss values due to the reduction in crash severity measures.     

影响Superpave混合料VTM的主要因素分析

沥青混合料生产过程中,级配或沥青含量的变异会造成沥青混合料体积指标与生产配合比发生偏差,在某条高速公路施工过程中,对下面层Superpave25、中面层Superpave20、下面层Superpave 13三种类型的混合料现场取样,在实验室使用旋转压实成型试件测得试件体积指标,通过抽提试验分析级配与生产配合比的差异,运用多元线性回归方法,分析影响矿料间隙率（VTM）的主要因素,并且通过工程实例验证回归公式的正确性.通过分析得知影响空隙率最显著的影响因素为沥青含量,其次为0.075mm及附近筛孔的通过率.     

雷达跟踪目标的残差检测自适应多模型算法

提出了一种基于残差的自适应多模型算法，通过残差的大小来分配多模型中单个模型在整体估计中的权重。本算法无须机动检测，从理论上避免了延迟。通过Monte Carlo仿真表明本算法的有效性。     

混沌CDMA系统中多址干扰分析

以logistic混沌扩频序列为例，对混沌扩频序列的多址干扰进行了分析，在用户信号之间完全异步的条件下，采用新的估值算法，推出混沌扩频序列的误码率表达式，指出混沌扩频序列长度、用户数及误码率的关系。领导 具结果表明，在混沌扩频序列长度有限的情况下，用户数偏少时，实际的误码率比用高斯估值法计算的误码率略大一些。     

Vehicle value of travel time savings: Evidence from a group-based modelling approach

The value of travel time savings (VTTS) accounts for a majority of the total user benefits in economic appraisal of transport investments. This means that having an accurate estimate of VTTS for different segments of travel continues to retain currency, despite there being a rich literature on estimates of VTTS for different travel modes, travel purposes, income groups, life cycles, and distance bands. In contrast, there is a dearth of research and evidence on vehicle VTTS, although joint travel by car is an important segment of travel. This paper fills this gap by developing a group-based modelling approach to quantify the vehicle VTTS and compares this with the VTTS for a driver with and without a passenger. An online survey was conducted in Sydney in 2014 and the data used to obtain a number of new empirical estimates of vehicle and driver VTTS. The new evidence questions the validity of various assumptions adopted in current practice for valuing the time savings of car passengers and multiple occupant cars.