scholarly journals Rollover Index for Rollover Mitigation Function of Intelligent Commercial Vehicle’s Electronic Stability Control

Electronics ◽  
2021 ◽  
Vol 10 (21) ◽  
pp. 2605
Author(s):  
Donghoon Shin ◽  
Seunghoon Woo ◽  
Manbok Park
Keyword(s):  
Estimation Method ◽  
Stability Control ◽  
Dynamic State ◽  
Electronic Stability Control ◽  
Simulation Studies ◽  
Limited Information ◽  
Parameter Uncertainties ◽  
Bank Angle ◽  
The Road ◽  
Rollover Index

This paper describes a rollover index for detection or prediction of impending rollover in different driving situations using minimum sensor signals which can be easily obtained from an electronic stability control (ESC) system. The estimated lateral load transfer ratio (LTR) was used as a rollover index with only limited information such as the roll state of the vehicle and some constant parameters. A commercial vehicle has parameter uncertainties because of its load variation. This is likely to affect the driving performance and the estimation of the dynamic state of the vehicle. The main purpose of this paper is to determine the rollover index based on reliable measurements and the parameters of the vehicle. For this purpose, a simplified lateral and vertical vehicle dynamic model was used with some assumptions. The index is appropriate for various situations although the vehicle parameters may change. As part of the index, the road bank angle was investigated in this study, using limited information. Since the vehicle roll dynamics are affected by the road bank angle, the road bank angle should be incorporated, although previous studies ignore this factor in order to simplify the problem. Because it increases or reduces the chances of rollover, consideration of the road bank angle is indispensable in the rollover detection and mitigation function of the ESC system. The performance of the proposed algorithm was investigated via computer simulation studies. The simulation studies showed that the proposed estimation method of the LTR and road bank angle with limited sensor information followed the actual LTR value, reducing the parameter uncertainties. The simulation model was constructed based on a heavy bus (12 tons).

Reduction in Fatal Longitudinal Barrier Crash Rate Due to Electronic Stability Control

2015 ◽  
Vol 2521 (1) ◽  
pp. 79-85 ◽  
Author(s):  
Nicholas S. Johnson ◽  
Hampton C. Gabler
Keyword(s):  
Stability Control ◽  
Electronic Stability Control ◽  
Loss Of Control ◽  
The Road ◽  
Passenger Vehicles ◽  
Fatal Crashes ◽  
Light Trucks ◽  
On The Road ◽  
Model Year ◽  
Injury Outcomes

Electronic stability control (ESC) is a vehicle safety system designed to keep vehicles moving in the direction commanded by the driver and thereby prevent loss-of-control crashes. Previous research has shown that ESC has been highly effective at reducing road departures related to loss of control. ESC is mandatory in all U.S. passenger vehicles manufactured from model year 2012 onward; by a 2014 estimate, ESC is in approximately one-third of passenger vehicles on the road. The proliferation of ESC may therefore alter benefit-to-cost ratios for roadside barriers. The objective of this analysis was to determine the effect of ESC on fatal crashes with roadside barriers. This objective was a first step toward determining whether ESC reduced the overall rate of crashes with roadside barriers and whether ESC had any effect on impact conditions or injury outcomes in barrier crashes. For cars, ESC reduced the odds of fatal crashes with roadside barriers by about 50% and reduced the odds of fatal rollovers that occurred in association with roadside barriers by about 45%. For light trucks and vans, ESC reduced barrier fatality odds by about 40% and barrier-associated rollover fatality odds by about 55%. By 2028, when an estimated 75% of passenger vehicles will have electronic stability control, ESC will have the potential to prevent about 410 out of an estimated 1,180 possible barrier-related fatalities per year. In the long term, once installed in every U.S. passenger vehicle, ESC could prevent about 550 of those same 1,180 possible barrier-related fatalities each year.

scholarly journals Road Roughness Estimation Based on the Vehicle Frequency Response Function

Actuators ◽  
2021 ◽  
Vol 10 (5) ◽  
pp. 89
Author(s):  
Qingxia Zhang ◽  
Jilin Hou ◽  
Zhongdong Duan ◽  
Łukasz Jankowski ◽  
Xiaoyang Hu
Keyword(s):  
Frequency Response ◽  
Response Function ◽  
Frequency Response Function ◽  
Gaussian White Noise ◽  
Estimation Method ◽  
Time Shift ◽  
Ride Quality ◽  
The Road ◽  
Road Roughness ◽  
Measured Response

Road roughness is an important factor in road network maintenance and ride quality. This paper proposes a road-roughness estimation method using the frequency response function (FRF) of a vehicle. First, based on the motion equation of the vehicle and the time shift property of the Fourier transform, the vehicle FRF with respect to the displacements of vehicle–road contact points, which describes the relationship between the measured response and road roughness, is deduced and simplified. The key to road roughness estimation is the vehicle FRF, which can be estimated directly using the measured response and the designed shape of the road based on the least-squares method. To eliminate the singular data in the estimated FRF, the shape function method was employed to improve the local curve of the FRF. Moreover, the road roughness can be estimated online by combining the estimated roughness in the overlapping time periods. Finally, a half-car model was used to numerically validate the proposed methods of road roughness estimation. Driving tests of a vehicle passing over a known-sized hump were designed to estimate the vehicle FRF, and the simulated vehicle accelerations were taken as the measured responses considering a 5% Gaussian white noise. Based on the directly estimated vehicle FRF and updated FRF, the road roughness estimation, which considers the influence of the sensors and quantity of measured data at different vehicle speeds, is discussed and compared. The results show that road roughness can be estimated using the proposed method with acceptable accuracy and robustness.

scholarly journals An Alternative Promotion Time Cure Model with Overdispersed Number of Competing Causes: An Application to Melanoma Data

Mathematics ◽  
2021 ◽  
Vol 9 (15) ◽  
pp. 1815
Author(s):  
Diego I. Gallardo ◽  
Mário de Castro ◽  
Héctor W. Gómez
Keyword(s):  
Estimation Method ◽  
Selection Criterion ◽  
Likelihood Method ◽  
Simulation Studies ◽  
Cure Rate ◽  
Nested Models ◽  
Proposed Model ◽  
The Em Algorithm ◽  
Competing Causes ◽  
The One

A cure rate model under the competing risks setup is proposed. For the number of competing causes related to the occurrence of the event of interest, we posit the one-parameter Bell distribution, which accommodates overdispersed counts. The model is parameterized in the cure rate, which is linked to covariates. Parameter estimation is based on the maximum likelihood method. Estimates are computed via the EM algorithm. In order to compare different models, a selection criterion for non-nested models is implemented. Results from simulation studies indicate that the estimation method and the model selection criterion have a good performance. A dataset on melanoma is analyzed using the proposed model as well as some models from the literature.

The Stability Control of Soft Soil Foundations of Urban Roads According to the Surface Subsidence Monitoring Data

2013 ◽  
Vol 859 ◽  
pp. 222-227
Author(s):  
Hong Jun Liu ◽  
Jin Hua Tan ◽  
Xue Wen Su ◽  
Hao Wu
Keyword(s):  
Soft Soil ◽  
Stability Control ◽  
Surface Subsidence ◽  
Monitoring Data ◽  
Research Results ◽  
The Road ◽  
Future Design ◽  
Left And Right ◽  
Soil Foundation ◽  
The Stability

Two typical monitoring sections are selected for obtaining the change law of the surface subsidence and the settlement after construction of soft soil foundations, and determining the reasonable unloading time. The research results show that the surface settlement rate is large during the filling stage, the rate decreases after the loading and gradually stabilized. The embankment midline settlement is larger than the settlement of the road shoulder which is concluded from the fact that the subsidence of the middle settlement plate is larger than those of the left and right plate. The surface subsidence rate is less than 5mm per month during the two month before unloading according to the data in the tables. The settlement after construction presumed from the middle plate is more significantly larger than that of left and right sides, hence, as the unloading basis of preloading drainage method in soft soil foundation treatment the settlement after construction which is calculated from the midline monitoring data of the road is appropriate. After 6 months the calculated post-construction settlements of the two sections are in the scope of the design requirement since they decrease with preloading time. The reliable basis is provided for the future design and construction of soft foundation in this area through the research results.

Modeling and Estimation of Headway Distributions

1997 ◽  
Vol 1591 (1) ◽  
pp. 14-22 ◽  
Author(s):  
Serge P. Hoogendoorn ◽  
Hein Botma
Keyword(s):  
Estimation Method ◽  
Simulation Models ◽  
Independent Random Variables ◽  
Microscopic Simulation ◽  
Simple Analysis ◽  
Rural Roads ◽  
The Road ◽  
Road Capacity ◽  
Measurement Location ◽  
Fourier Series Analysis

A simple analysis to derive Branston’s generalized queueing model for (time-) headway distributions is presented. It is assumed that the total headway is the sum of two independent random variables: the empty zone and the free-flowing headway. The parameters of the model can be used to examine various characteristics of both the road (e.g., capacity) and driver-vehicle combinations (e.g., following behavior). Furthermore, the model can be applied to vehicle generation in microscopic simulation models and to safety analysis. To estimate the different parameters in the model, a new estimation method is proposed. This method, which was developed on the basis of Fourier-series analysis, was successfully applied to measurements collected on two-lane rural roads. The method was found to be both computationally less demanding and more robust than traditional parameter techniques procedures, such as maximum likelihood. In addition, the method provides more accurate results. Parameters in the model were examined with the developed estimation method. Estimates of these parameters at a specific period and a specific measurement location were to some extent transferable to other periods and locations. Application of the method to road capacity estimation is discussed.

Road Adhesion Coefficient Estimation Based on the Steering Wheel Rebound After Steering

2018 ◽  
Author(s):  
Liangyao Yu ◽  
Sheng Zheng ◽  
Xiaohui Liu ◽  
Jinghu Chang ◽  
Fei Li
Keyword(s):  
Stability Control ◽  
Front Wheel ◽  
Intelligent Vehicles ◽  
Steering Wheel ◽  
Adhesion Coefficient ◽  
The Road ◽  
Whole Process ◽  
Friction Moment ◽  
Stability Control System ◽  
The Coefficient Of Friction

Accurately estimating road adhesion coefficient is very important for vehicle stability control system. In this paper, an innovation method to estimate the road adhesion coefficient is proposed. This method can be used in vehicles without additional sensors. And this method is especially suitable to be used in the intelligent vehicle equipped with steer-by-wire (SBW) system. When vehicle steers, releasing the steering wheel suddenly will result in rebound to a certain angle. When the steer wheel turns the same angle on different road whose adhesion coefficients are different, the front wheel rebound angles are different. The friction moment between the road and tire is the main factor to prevent the tire from turning back, and the coefficient of friction is equal to road adhesion coefficient when the vehicle is stationary. In this paper, the detailed dynamical models describing the whole process of the front wheel and tire rebound are established. Furthermore, the Luenberger reduced-order disturbance observer is established to estimate the friction moment, and then the adhesion coefficient is estimated. The SBW system which is usually equipped in intelligent vehicles can control the steer moment and steer angle accurately. When the steer wheel turns to certain angle, the SBW system is able to stop outputting torque quickly and timely, which is important for improving the experiment accuracy. In this paper, the SBW system is used to conduct an experiment on different roads. The experiment results demonstrate the validity of this method.

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