Xiaomin Lian

A Study on the Method for Cleaning and Repairing the Probe Vehicle Data

Probe vehicle data are being increasingly applied in urban dynamic traffic data collection. However, the mobility and scale limit of probe vehicles may lead to incomplete or inaccurate data and thus influence the measurement of the state of traffic. At present, probe vehicle data are usually repaired by linear interpolation or a historical average method, but the repair accuracy is relatively low. To address the given problems, the multi-threshold control repair method (MTCRM) was proposed to clean and repair the probe vehicle data. The MTCRM adopts threshold control and a rule based on the approximate normalization transform to clean abnormal traffic data and to fill in the missing data by a weighted average method and an exponential smoothing method. In this approach, we combine topological road network characteristics to fill in the missing data from data for neighboring road sections and repair noisy data by reconstructing the principal components. This paper mainly focuses on analyzing the component of the recurring pattern of probe vehicle data, which can provide guidelines for the subsequent traffic forecasts. The findings of data repair for different grades of road in Beijing, China, demonstrate that the mean repair error may meet the requirements of traffic-state measurement, demonstrating that MTCRM can effectively clean probe vehicle data.

Distributed vehicle body electric/electronic system architecture with central coordination control

Abstract The conventional vehicle electric/electronic system architecture has become an obstacle of the booming development of in-vehicle electric and electronic devices. The surging number of these devices and the runup of the information exchange requirement among the devices call for a brand new system architecture. In this paper, a completely distributed electric/electronic system architecture with a centralized coordinator is introduced. The new architecture concept features a set of hierarchy on-site serial buses together with a digitalized power supply network coordinated by a central controller. The basic functionality and diagnosis of all the in-vehicle electric devices are implemented as digitalized nodes with unified connection interface in the network, which execute commands and share information with the central coordinator. The new architecture facilitates the information exchange, minimizes the cost and effort of vehicle harness, and reserves the configurability and expandability. The distributed structure with twin backup central coordinators ensures the system reliability.

Synthetic Fuzzy Evaluation Method of Trajectory Similarity in Map-Matching

Despite the rapid development of concepts used in current map-matching algorithms, the continuous movement of a vehicle is often ignored or just limited to 1 or several previous matches. This may result in errors in complicated situations such as at Y-junctions, and entrance or exit ramps of a highway. The trajectory-based map-matching algorithm, which determines the matching road by comparing the vehicle trajectory against candidate roads, has the potential to overcome this limitation. However, the curve-to-curve matching as a simple form of trajectory-based map-matching fails to address this. The key issue of a trajectory-based map-matching algorithm is how to evaluate the similarity between the trajectory and the possible traveling roads. This article develops a synthetic fuzzy evaluation method to address the issue. The similarities are quantified in terms of location, shape, direction, and behavior. As a new input in map-matching, vehicle behavior refers to changes in the motion of the vehicle such as turning, which is restrained by the geometry of traveling road. The article also proposes a multilevel fuzzy synthetic evaluation process to assess the similarities and hierarchically synthesize them into a final evaluation. The method is evaluated using GPS positions recorded with a vehicle traveling in the urban area of Beijing, China. The traveled road paths include complicated roads conditions such as flyovers, highway entrances and exits. The method identifies more than 98% of the road segments correctly, showing a significant improvement over existing map-matching algorithms.

A Trajectory-Based Map-Matching System for the Driving Road Identification in Vehicle Navigation Systems

Driving road identification is the key issue of a vehicle navigation system that supports various services of intelligent transportation systems. The method for driving road identification is also known as map matching (MM). In spite of the development of MM algorithms, limitations still exist in obtaining the positioning data and preparing candidate roads (CRs) that may result in mismatches in some special difficult road configurations such as flyovers and parallel roads. To overcome the limitations, an integrated trajectory-based MM (tbMM) system is proposed based on the trajectory similarity evaluation method. The system can fuse the information from global positioning systems (GPS) and inertial sensors to generate the vehicle trajectory that represents the vehicle continuous movement in three dimensions. The elevation data of vehicle and roads are involved to enhance the trajectory-based matching process. Also the method employs an optimized mechanism for generating and maintaining CRs. Using the mechanism, separated road segments in a digital map are reorganized in the form of possible driving roads and the topology among them is guaranteed. Moreover, the CRs are obtained considering all the possibilities in determining the driving road so that the valuable historical information can be effectively reserved to provide more reliable matches in ambiguous situations. The tbMM system was evaluated using a number of real-world vehicle-level test datasets in urban areas in Beijing. Also a comparison test was performed to evaluate the driving road identification accuracy against existing MM algorithms. The results show that the tbMM system can provide reliable matches with about 99% accuracy in all the difficult scenarios and outperforms the existing algorithms.

Acoustic Modelling and Analysis of Vehicle Interior Noise Based on Numerical Calculation

In this paper, various numerical calculation methods are rigorously combined to model and analyze the acoustic characteristics of a heavy truck cab. Firstly a brief introduction of different numerical calculation methods is given, then the finite element structure model and cavity model of the cab are built. The statistical energy analysis models of the cab, including structural subsystems and cavity subsystems, are also built and used in the high-frequency range. The panel acoustic contribution analysis and the energy transfer path contribution analysis are carried out to find the panels which contribute most to the sound pressure inside the cab. Based on the analysis results, structure modification of these panels has been proposed with acoustics topology optimized. The optimization result shows that the sound pressure level on the side of the driver’s right ear can be reduced by a few decibels. Necessary tests to validate the models are also administered.

In-vehicle navigation system based on dynamic traffic information

This paper proposed a spider-web punctual road network model and a dynamic traffic information model suitable for use in the in-vehicle navigation system. Based on these models, the dynamic traffic information can integrate with the embedded GIS efficiently. The in-vehicle navigation system designed in this paper can realize the display and query of dynamic traffic information in real-time, and the optimal dynamic routing according to dynamic traffic information can avoid traffic jams automatically. The application experiments showed the feasibility and effectiveness of the road network model and the dynamic traffic information model.

Video visualization for moving sound sources based on binocular vision and short-time beamforming

Visualization of moving sound sources is very important for noise source identification of moving objects. In this paper, we introduce binocular vision technology to sound sources visualization. Binocular technology can not only obtain the visualization, but also is able to achieve the spatial measurement of moving objects and determine the relative position of moving sound sources and the microphone array automatically, so that the sound reconstruction plane can be closely attached to the moving object. Together with the short-time beamforming method, the sound map is accurately registered on to the video images, generating the sound video close to the moving sound sources. Then, by video slow motion, noises originated from moving sound sources in a real world are shown in a sound movie. To verify this method, an experiment for a non-stationary speaker in the anechoic room is conducted, where the speaker sound source is visualized and located accurately. Further verification experiments for an outdoor moving vehicle carrying speakers have also been conducted. Sound sources of the moving speakers are successfully visualized and located. The generated sound movie shows the origin of noises under real world conditions making noise source investigation easier and more accurate. These experimental results suggest that our visualization approach has potential for noise identification and control

Time-domain transfer path analysis of multiple moving noise sources

Identifying the contribution of different noise sources is a major step in reducing the impact of moving noise sources. Compared with classic transfer path analysis, operational transfer path analysis could improve efficiency of the identification process.To analyze the transient characteristics and their contribution of multiple moving noise sources, a method of time-domain transfer path analysis (TPA) is proposed. The dynamic transfer path model and transfer matrix calculation method are introduced. Simulation with three point sources is used to compare the identification results of the time-domain TPA and frequency-domain TPA. The application of the time-domain TPA to the identification of the pass-by noise source of a heavy duty truck is illustrated. The simulation and the application results show that time-domain TPA could be used to analyze the contribution of moving noise sources, and it takes less computational effort compared with frequency-domain TPA

Complete de-Dopplerization and acoustic holography for external noise of a high-speed train

Identification and measurement of moving sound sources are the bases for vehicle noise control. Acoustic holography has been applied in successfully identifying the moving sound source since the 1990s. However, due to the high demand for the accuracy of holographic data, currently the maximum velocity achieved by acoustic holography is just above 100 km/h. The objective of this study was to establish a method based on the complete Morse acoustic model to restore the measured signal in high-speed situations, and to propose a far-field acoustic holography method applicable for high-speed moving sound sources. Simulated comparisons of the proposed far-field acoustic holography with complete Morse model, the acoustic holography with simplified Morse model and traditional delay-and-sum beamforming were conducted. Experiments with a high-speed train running at the speed of 278 km/h validated the proposed far-field acoustic holography. This study extended the applications of acoustic holography to high-speed situations and established the basis for quantitative measurements of far-field acoustic holography.

Intelligent vehicle electrical power supply system with central coordinated protection

The current research of vehicle electrical power supply system mainly focuses on electric vehicles (EV) and hybrid electric vehicles (HEV). The vehicle electrical power supply system used in traditional fuel vehicles is rather simple and imperfect; electrical/electronic devices (EEDs) applied in vehicles are usually directly connected with the vehicle’s battery. With increasing numbers of EEDs being applied in traditional fuel vehicles, vehicle electrical power supply systems should be optimized and improved so that they can work more safely and more effectively. In this paper, a new vehicle electrical power supply system for traditional fuel vehicles, which accounts for all electrical/electronic devices and complex work conditions, is proposed based on a smart electrical/electronic device (SEED) system. Working as an independent intelligent electrical power supply network, the proposed system is isolated from the electrical control module and communication network, and access to the vehicle system is made through a bus interface. This results in a clean controller power supply with no electromagnetic interference. A new practical battery state of charge (SoC) estimation method is also proposed to achieve more accurate SoC estimation for lead-acid batteries in traditional fuel vehicles so that the intelligent power system can monitor the status of the battery for an over-current state in each power channel. Optimized protection methods are also used to ensure power supply safety. Experiments and tests on a traditional fuel vehicle are performed, and the results reveal that the battery SoC is calculated quickly and sufficiently accurately for battery over-discharge protection. Over-current protection is achieved, and the entire vehicle’s power utilization is optimized. For traditional fuel vehicles, the proposed vehicle electrical power supply system is comprehensive and has a unified system architecture, enhancing system reliability and security.