Fuzzy-logic-based incident detection for signalized diamond interchanges

This paper documents a fuzzy-logic-based incident detection algorithm for signalized urban diamond interchanges. The model is capable of detecting lane-blocking incidents whose effects are manifested by patterns of deterioration in traffic conditions that require adjustments in signal control strategies. As a component of a real-time traffic adaptive control system for signalized diamond interchanges, the algorithm feeds an incident report (i.e., the time, location, and severity of the incident) to the system's optimization manager, which uses that information to determine the appropriate signal control strategy.The performance of the model was studied using a simulation of an actual diamond interchange. The simulation study evaluated the model's performance in terms of detection rate, false alarm rate, and mean time to detect. The model's performance was encouraging, and the fuzzy-logic-based approach is considered promising.     

Red-light cameras at intersections: Estimating preferences using a stated choice model

Red-light cameras placed at intersections have the potential to increase safety, but they are often viewed as an invasion of privacy. Preferences for these cameras were explored using a stated choice model that presents key attributes of camera placements. Stated choice models involve careful experimental design, akin to experimental control in laboratory settings. A variety of design approaches were used, settling on a composition of the choice sets people face in the survey. To illustrate the approach, an internet survey was used with a convenience sample containing a high percentage of college students. The results show that while not the case independently, as the number of cameras and fines for violators are simultaneously increased, the preferences for one particular red light cameras program are likely to improve.     

Development of a semi-empirical friction model in automotive driveshaft joints

High speed and sport utility vehicles with large joint articulation angle demand lower friction in automotive driveshaft joints to meet noise and vibration comfort levels. Thus a more thorough understanding of internal friction characteristics and mechanisms is required. In this paper, a friction model in automotive driveshaft joints was developed through the use of test data from an instrumented Constant Velocity (CV) joint friction apparatus with actual driveshaft assemblies. Experiments were conducted under different realistic operating conditions of oscillatory speeds, CV joint articulation angles, lubrication, and torque. The experimental data was used to develop a physics-based semi-empirical CV joint internal friction model as a function of different CV joint operating parameters. It was found that the proposed friction model captures the experimental results well. Also the friction model estimates the generated axial force (GAF) in tripod CV joints well, which is the main source of force that causes vehicle vibration problems.     

Development of a low-noise cooling fan for an alternator using numerical and doe methods

An alternator, which converts mechanical rotational energy into electrical energy, is an important component of a vehicle. Alternators operate over a broad range of rotational speeds, typically from 3,000 RPM to 18,000 RPM, which demands a cooling fan producing sufficient airflow, ideally with a minimum of noise. In the current study, an optimized alternator-cooling fan was developed through a linked DOE(Design OF Experiment) process and numerical analysis. The SC/Tetra and FlowNoise S/W programs were used to calculate flow rates and noise levels, respectively, for the newly developed fan. Compared with original model, the numerical results predicted a 3 dBA noise reduction; the measured reduction was 4 dBA.     

Development of a navigation algorithm with dead reckoning for unmanned ground vehicles

A navigation algorithm is indispensable for Unmanned Ground Vehicles (UGVs). During driving, UGVs follow a global path. In this study, we propose a navigation algorithm using Real Time Kinematic (RTK)-Differential Global Positioning System (DGPS) units and encoders to complement global path planning. Sometimes GPS systems lose their signals and receive inaccurate position data due to many factors, such as edifice and barrier obstructions. This paper shows that GPS deviations can be solved using a Dead Reckoning (DR) navigation method with encoders and that position errors can be decreased through the use of RTK-DGPS units. In addition to this method, we will introduce a new waypoint update algorithm and a steering algorithm using RTK-DGPS units.     

Modified lateral control of an autonomous vehicle by look-ahead and look-down sensing

This paper presents a modified lateral control method for an autonomous vehicle with both look-ahead and look-down sensing systems. To cope with sensor noise and modeling uncertainty in the lateral control of the vehicle, a modified LMI-based H lateral controller was proposed, which uses the look-ahead information of the lateral offset error measured at the front of vehicle and the look-down information of the vehicle yaw angle error between the reference lane and the centerline of the vehicle. To verify the safety and the performance of the lateral control, a scaled-down vehicle was developed, and the positioning of the vehicle was estimated with USAT. The proposed controller, which uses both look-ahead and look-down information, was tested for lane changing and reference lane tracking with both simulation and experiment. The simulation and experimental results show that the proposed controller has better tracking and handling performance compared with a controller that uses only the look-ahead information of the target heading angle error.     

Design framework for FlexRay network parameter optimization

Because the FlexRay protocol has more than 70 configuration parameters and these parameters correlate with each other, designing a FlexRay network is a complex and difficult task. In this study, we propose a design framework that optimizes the two main FlexRay network parameters that are highly relevant to the application algorithm. The design process is composed of two steps for optimizing parameters. In the first step, the static slot length is optimized using a frame-packing algorithm. This algorithm binds network signals into static frames based on their periods and signal groups. In the second step, the communication cycle length is optimally designed with frame-scheduling algorithm and worst-case reponse time analysis. Based on the frame-scheduling algorithm, the response times are analyzed. The proposed design framework was applied to a unified chassis control system as a case study, and the analytical results were verified.     

Vehicle interior noise model based on a power law

Identifying the components of a vehicle’s interior noise is important in many phases of the noise, vibration, and harshness (NVH) development process. Many test methods that have been widely used in the automobile industry to separate noise sources are based on system identification methods in the frequency domain. However, none of the frequency response function-based methods can directly estimate the wind noise component. In this article, an analytical model for the interior noise level based on a simple power law was developed. It was assumed that the mean squared acoustic pressure for the interior noise could be obtained by summing up those of the wind noise, road noise, and background noise. The wind noise and road noise were further assumed to depend only on wind speed and the vehicle’s driving speed, respectively, and to follow a simple power law. The resulting analytical model includes five parameters that can be optimized for the vehicle and the road. The validity of the model was verified by using data obtained from cruise tests performed on a proving ground for cruise speeds ranging from 40 km/h to 130 km/h. The model is applied to the overall and 1/3-octave bands of interior noise and is shown to describe the data trends fairly well. For the test vehicle used in the present work, the overall mean squared pressures for the wind and road noise components are shown to be proportional to the wind speed to the 5.8 power and to the driving speed to the 3.4 power, respectively.     

Piston-temperature measuring system using electromagnetic induction with verification by a telemetry system

The development of an inner-piston-chamber temperature measurement system is a necessary step in engine development or when solving other fundamental problems related to automotive engines. There are various pre-existing measurement methods available, e.g., the linkage method, piston telemetry, templog, and the electromagnetic induction method. In this study, we first redesigned the coil sensor used in the electromagnetic induction method using PEEK and then used Taguchi methods to reduce the number of experiments in the development process and finally utilized piston telemetry via Bluetooth to verify the precision and accuracy of the redesigned PEEK coil sensor and electromagnetic induction method. The results displayed a reproducibility within 0.5 degrees and an accuracy within 2 degrees Celsius.