Speed estimation and length based vehicle classification from freeway single-loop detectors

Roadway usage, particularly by large vehicles, is one of the fundamental factors determining the lifespan of highway infrastructure. Operating agencies typically employ expensive classification stations to monitor large vehicle usage. Meanwhile, single-loop detectors are the most common vehicle detector and many new, out-of-pavement detectors seek to replace loop detectors by emulating the operation of single-loop detectors. In either case, collecting reliable length data from these detectors has been considered impossible due to the noisy speed estimates provided by conventional data aggregation at single-loop detectors. This research refines non-conventional techniques for estimating speed at single-loop detectors, yielding estimates that approach the accuracy of a dual-loop detector’s measurements. Employing these speed estimation advances, this research brings length based vehicle classification to single-loop detectors (and by extension, many of the emerging out-of-pavement detectors). The classification methodology is evaluated against concurrent measurements from video and dual-loop detectors. To capture higher truck volumes than empirically observed, a process of generating synthetic detector actuations is developed. By extending vehicle classification to single-loop detectors, this work leverages the existing investment deployed in single-loop detector count stations and real-time traffic management stations. The work also offers a viable treatment in the event that one of the loops in a dual-loop detector classification station fails and thus, also promises to improve the reliability of existing classification stations.     

绿色道路:路面可持续性评价系统

绿色道路是评价路面设计和施工过程相关的可持续性发展的一种建议标准。该系统依据可持续发展的实践性为道路工程打分,通过得分的高低来评价工程的可持续性。充分完善的绿色道路系统具有以下内容和功能:1)鼓励更多道路工程尝试可持续性的实践;2)为道路可持续性评价提供一种标准和方法;3)使工程设计更优;4)使业主单位能评判道路工程的优劣。绿色道路评价系统通过6大类的54个评分项完成对道路工程的评分,是发展道路可持续性设计的可靠系统。     

耦合轮对的应用研究

建立了耦合轮对转向架车辆的动力学计算模型,利用数值模拟方法对不同半径曲线的通过情况进行了动态仿真计算.通过传统轮对与独立轮对、耦合轮对的比较,认为耦合轮对具有更好的动力学性能.基于耦合轮对的特点,提出采用耦合轮对抑制粘滑振动的新方法,并对其可行性进行了分析.分析表明,由于耦合轮对蠕滑力的可控性,采用耦合轮对能有效抑制轮对的粘滑振动.     

A suggestion of gap flow control devices for the suppression of rudder cavitation

This paper presents the numerical analysis of rudder cavitation in propeller slipstream and the development of a new rudder system aimed for lift augmentation and cavitation suppression. The new rudder system is equipped with cam devices which effectively close the gap between the horn/pintle and movable wing parts. A computational fluid dynamics code that solves the Reynolds-averaged Navier–Stokes equations is used to analyze the flow field of various rudder systems in propeller slipstream. The body force momentum source terms that mimic flow field behind a rotating propeller are added in the momentum equations to represent the influence of the propeller and its slipstream. For detailed explication of the new rudder system’s lift augmentation and cavitation suppression mechanism, three-dimensional flow analysis is carried out. Simulations clearly display the mechanism of the lift augmentation and cavitation suppression. The computational results suggest that the Reynolds-averaged Navier–Stokes-based computational fluid dynamics reproduces the flow field around a rudder in propeller slipstream and that the present concept for a cavitation suppressing rudder system is highly feasible and warrant further study for inclusion of the interaction with hull and mechanical design for manufacturing and operations.     

Simulating the household plug-in hybrid electric vehicle distribution and its electric distribution network impacts

This paper presents a multi agent-based simulation framework for modeling spatial distribution of plug-in hybrid electric vehicle ownership at local residential level, discovering “plug-in hybrid electric vehicle hot zones” where ownership may quickly increase in the near future, and estimating the impacts of the increasing plug-in hybrid electric vehicle ownership on the local electric distribution network with different charging strategies. We use Knox County, Tennessee as a case study to highlight the simulation results of the agent-based simulation framework.     

Design of ferrite magnet CFSM to improve speed response of EPS system

This paper deals with the speed response characteristic of the concentrated flux synchronous motor (CFSM) using ferrite magnets for the electric power steering (EPS) system. To analyze the response characteristic of the CFSM, an analytical method using the electromechanical undamped natural frequency and damping ratio based on the transfer function is proposed. By using the method, the speed response according to the variations of the shape of the permanent magnets (PMs) and rotor core is analyzed. It was analyzed under the conditions of the constant volume of the PMs as well as the constant diameter of the rotor. By using the proposed analysis method, the improved model is desgined based on the initial model fulfilling the required specifications. Finally, the torque and speed response characteristics of two motors are simulated through the finite element analysis (FEA) and MATLAB Simulink.     

Analysis of automotive disc brake squeal considering damping and design modifications for pads and a disc

The squeal noise occurring from the disc brakes of passenger cars has been analyzed by using the complex eigenvalue method numerically. The contact between a disc and two pads was analytically modeled as many linear springs and dampers in an effort to develop the improved equation of motion derived on the basis of Lagrange’s equation and the assumed mode method. The finite element modal analysis results for disc brake components constitute an eigenvalue matrix in the analytical equation of motion. The complex eigenvalue analyses based on the equations of motion are able to examine the dynamic instability of a brake system, which is an onset of squeal, by considering the disc rotational effect. Numerical analyses showed that the modes unstable in an undamped analysis became stable in a damped case, which illustrates the important effect of damping on the squeal instability in a brake squeal simulation. Then several modified brake models were suggested and investigated how effectively they suppressed the occurrence of squeal noise. The brake parts such as a pad chamfer and a disc vane were modified and the influence of pad chamfer and vane shapes on squeal occurrence was proved to be significant. The numerical results showed that proper structural modification of a disc brake system can suppress the brake squeal to some extent.     

A cluster analysis approach for differentiating transportation modes using Bluetooth sensor data

A variety of automatic data collection technologies have been used to gather road and highway system data. The majority of these automatic data collection technologies are designed to collect vehicle-based data and either do not have the capability to collect other travel mode data (e.g., bicycles and pedestrians), or may need to be deployed differently to support this capability.

One type of wireless-based data collection system that has been deployed recently is based on Bluetooth technology. A key feature of Bluetooth-based data collection systems that makes travel mode identification feasible is that the Bluetooth-enabled devices within vehicles are also present on bicyclists and pedestrians. This research explores the effectiveness of applying cluster analysis methods when processing data collected via Bluetooth technology from vehicles, bicyclists, and pedestrians to automatically identify the associated travel modes. The results of several experiments utilizing multiple Bluetooth-based data collection units arranged linearly and in relatively close proximity on a simulated intersection demonstrate the potential of cluster analysis to accurately differentiate transportation modes from the collected data.     

Autonomous Emergency Braking Considering Road Slope and Friction Coefficient

The Autonomous Emergency Braking (AEB) systems have been actively studied for the safety enhancement and commercialized for the past few years. Because the driver tends to overly rely upon active safety systems, AEB needs to be designed to reflect the real road situations such as various road slope and friction coefficient. In this study, an AEB control algorithm is proposed to compensate for the effects of the slope and the friction of road. Based on the maximum possible deceleration for the real road conditions, the minimum braking distance is described with margin parameters for AEB activation control. The deceleration controller with a feedforward term is designed to avoid the collision during AEB operation on real road conditions. The proposed algorithm is validated in simulations first and the experimental verification is performed in the various slope conditions.     

Development of a Driving Behavior-Based Collision Warning System Using a Neural Network

An advanced driver assistance system (ADAS) uses radar, visual information, and laser sensors to calculate variables representing driving conditions, such as time-to-collision (TTC) and time headway (THW), and to determine collision risk using empirically set thresholds. However, the empirically set threshold can generate differences in performance that are detected by the driver. It is appropriate to quickly relay collision risk to drivers whose response speed to dangerous situations is relatively slow and who drive defensively. However, for drivers whose response speed is relatively fast and who drive actively, it may be better not to provide a warning if they are aware of the collision risk in advance, because giving collision warnings too frequently can lower the reliability of the warnings and cause dissatisfaction in the driver, or promote disregard. To solve this problem, this study proposes a collision warning system (CWS) based on an individual driver’s driving behavior. In particular, a driver behavior model was created using an artificial neural network learning algorithm so that the collision risk could be determined according to the driving characteristics of the driver. Finally, the driver behavior model was learned using actual vehicle driving data and the applicability of the proposed CWS was verified through simulation.