scholarly journals An Automatic Emergency Braking Model considering Driver’s Intention Recognition of the Front Vehicle

2020 ◽  
Vol 2020 ◽  
pp. 1-15
Author(s):  
Wei Yang ◽  
Jiajun Liu ◽  
Kaixia Zhou ◽  
Zhiwei Zhang ◽  
Xiaolei Qu
Keyword(s):  
Avoidance Performance ◽  
Vehicle Speed ◽  
Test Results ◽  
Collision Risk ◽  
Accelerator Pedal ◽  
Internet Of Vehicles ◽  
Emergency Braking ◽  
Intention Recognition ◽  
Braking Distance ◽  
Driver’S Intention

Driver’s intention of the front vehicle plays an important role in the automatic emergency braking (AEB) system. If the front vehicle brakes suddenly, there is potential collision risk for following vehicle. Therefore, we propose a driver’s intention recognition model for the front vehicle, which is based on the backpropagation (BP) neural network and hidden Markov model (HMM). The brake pedal, accelerator pedal, and vehicle speed data are used as the input of the proposed BP-HMM model to recognize the driver’s intention, which includes uniform driving, normal braking, and emergency braking. According to the recognized driver’s intention transmitted by Internet of vehicles, an AEB model for the following vehicle is proposed, which can dynamically change the critical braking distance under different driving conditions to avoid rear-end collision. In order to verify the performance of the proposed models, we conducted driver’s intention recognition and AEB simulation tests in the cosimulation environment of Simulink and PreScan. The simulation test results show that the average recognition accuracy of the proposed BP-HMM model was 98%, which was better than that of the BP and HMM models. In the Car to Car Rear moving (CCRm) and Car to Car Rear braking (CCRb) tests, the minimum relative distance between the following vehicle and the front vehicle was within the range of 1.5 m–2.7 m and 2.63 m–5.28 m, respectively. The proposed AEB model has better collision avoidance performance than the traditional AEB model and can adapt to individual drivers.

scholarly journals An Overview of Heavy Trucks/Buses Braking Performance

1991 ◽  
Vol 8 (1) ◽  
Author(s):  
Richard M. Ziernicki
Keyword(s):  
Statistical Data ◽  
Vehicle Speed ◽  
Test Results ◽  
Heavy Duty ◽  
Braking Performance ◽  
Emergency Braking ◽  
Heavy Trucks ◽  
Brake Performance ◽  
Drag Factor ◽  
Heavy Duty Vehicles

The writer discusses the performance of heavy duty vehicles during emergency braking. The paper reviews statistical data related to the trucking accidents, and discusses brake performance, tires, and the stopping ability of heavy duty vehicles. Relationships between drag factor, coefficient of friction, vehicle speed, type of tire, road surface, brake design, and brake temperature are discussed. Some of the test results performed on heavy trucks are presented. The discussion is general in order to make the presentation useful both to practicing reconstruction specialists, and to attorneys.

Testing and Analysis of Autonomous Emergency Braking Systems Using the Euro NCAP Vehicle Target

2014 ◽  
Author(s):  
Matthew L. Schwall ◽  
John D. Neal ◽  
Charles J. Retallack ◽  
Robert E. Larson ◽  
Graeme F. Fowler
Keyword(s):  
Sensor Data ◽  
Vehicle Speed ◽  
Test Results ◽  
Passenger Cars ◽  
Collision Warning ◽  
Euro Ncap ◽  
Emergency Braking ◽  
Collision Mitigation ◽  
The Subject ◽  
Forward Collision Warning

Passenger cars are increasingly available equipped with Autonomous Emergency Braking (AEB). AEB systems detect likely forward collisions and apply the vehicle’s brakes if the driver fails to do so, reducing vehicle speed in order to mitigate or potentially avoid a collision. The performance of these systems is experimentally evaluated in tests including those specified by the European New Car Assessment Program (Euro NCAP) and by the Insurance Institute for Highway Safety (IIHS). In both of these testing programs the subject vehicle is driven towards a Euro NCAP Vehicle Target, an inflatable device designed to have visual and radar reflective characteristics similar to the rear of a compact car. The results reported by Euro NCAP and the IIHS have revealed significant differences in the AEB test results achieved by various AEB-equipped vehicles. Such differences exist even between vehicles with similar sensing technologies, suggesting that the source of such disparities may be differences in sensor data processing methods or differences in collision mitigation and avoidance strategies. This paper details the performance of AEB as well as Forward Collision Warning (FCW) systems when tested with the Euro NCAP Vehicle Target. These results are analyzed, exploring the differences in the performance of these systems under the test conditions and discussing possible reasons for the observed disparities.

scholarly journals Collision Risk Mitigating System for Light Rail Vehicles(LRV)

2016 ◽  
Vol 38 (1) ◽  
pp. 50-56
Author(s):  
Bartosz Antkowiak
Keyword(s):  
Control System ◽  
Obstacle Detection ◽  
Light Rail ◽  
Vehicle Speed ◽  
Ambient Conditions ◽  
Collision Risk ◽  
System Operation ◽  
Rail Vehicles ◽  
Braking Distance ◽  
Vehicle Positioning

Abstract This piece is dedicated tothedescription of the development of collision risk mitigating system. The proposed concept of control system is designed to enhance safety ofpassengers, a driver and other people in vicinityof light rail vehicles (tramways).The requirements were fulfilled thanks to the application of lidar sensor and feature of vehicle positioning on the track map created basingon precise measurements with the use of satellite navigation systemReal Time Kinematic. The map allows to eliminate errors of system operation and to enhance resistance to unfavorable ambient conditions, i.e.temperature or fog. The system calculates work braking distance for particular vehicle speed. In case of obstacle detection which is closer to vehicle than the calculated braking distance, the driver is informed about a collision risk with a buzzer and optical signalization. The system has already been implemented and tested.

scholarly journals A Sensaptic ADAS Device Using Shape Memory Alloy Wires: Design and Control

Materials ◽  
2021 ◽  
Vol 14 (13) ◽  
pp. 3494
Author(s):  
Deivamoney Josephine Selvarani Ruth ◽  
Kaliaperumal Dhanalakshmi ◽  
Seung-Bok Choi
Keyword(s):  
Shape Memory Alloy ◽  
Shape Memory ◽  
Haptic Feedback ◽  
Reaction Force ◽  
Vehicle Speed ◽  
Accelerator Pedal ◽  
Integrated Sensor ◽  
Electronic Throttle ◽  
Position Sensing ◽  
Active Sensor

This paper presents an active accelerator pedal system based on an integrated sensor and actuator using shape memory alloy (SMA) for speed control and to create haptics in the accelerator pedal. A device named sensaptics is developed with a pair of bi-functional SMA wires instrumented in a synergistic configuration function as an active sensor for positioning the accelerator pedal (pedal position sensing) to control the vehicle speed through electronic throttle and as a variable impedance actuator to generate active force (haptic) feedback to the driver. The reaction force emanated from the pedal alerts the driver and takes appropriate control action by slowing down the vehicle, in harmony with the road’s condition. The design is developed as a proof-of-concept device and is tested and evaluated in a real-time common rail diesel system for rail pressure regulation and over speeding tests, and the responses and performances are found to be promising.

Improved AEB algorithm combined with estimating the adhesion coefficient of road ahead and considering the performance of EHB

2021 ◽  
pp. 095440702110261
Author(s):  
Dequan Zeng ◽  
Zhuoping Yu ◽  
Lu Xiong ◽  
Junqiao Zhao ◽  
Peizhi Zhang ◽  
...  
Keyword(s):  
Joint Probability ◽  
Principal Component ◽  
Test Results ◽  
Safe Distance ◽  
Adhesion Coefficient ◽  
The Road ◽  
Response Characteristics ◽  
Emergency Braking ◽  
Multiple Beams ◽  
Maximum Method

This paper proposes an improved autonomous emergency braking (AEB) algorithm intended for intelligent vehicle. Featuring a combination with the estimation of road adhesion coefficient, the proposed approach takes into account the performance of electronic hydraulic brake. In order for the accurate yet fast estimate of road ahead adhesion coefficient, the expectation maximization framework is applied depending on the reflectivity of ground extracted by multiple beams lidar in four major steps, which are the rough extraction of ground points based on 3 σ criterion, the accurate extraction of ground points through principal component analysis (PCA), the main distribution characteristics of ground as extracted using the expectation maximum method (EM) and the estimation of road adhesion coefficient via joint probability. In order to describe the performance of EHB, the response characteristics, as well as the forward and adverse models of both braking pressure and acceleration are obtained. Then, with two typical roads including single homogeneous road and fragment pavement, the safe distance of improved AEB is modeled. To validate the algorithm developed in this paper, various tests have been conducted. According to the test results, the reflectivity of laser point cloud is effective in estimating the road adhesion coefficient. Moreover, considering the performance of EHB system, the improved AEB algorithm is deemed more consistent with the practicalities.

scholarly journals Cost-Effective Resource Sharing in an Internet of Vehicles-Employed Mobile Edge Computing Environment

Symmetry ◽  
2018 ◽  
Vol 10 (11) ◽  
pp. 594 ◽  
Author(s):  
Tri Nguyen ◽  
Tien-Dung Nguyen ◽  
Van Nguyen ◽  
Xuan-Qui Pham ◽  
Eui-Nam Huh
Keyword(s):  
Video Streaming ◽  
Resource Sharing ◽  
Vehicular Network ◽  
Edge Computing ◽  
Mixed Integer ◽  
Mobile Users ◽  
Vehicle Speed ◽  
Mobile Edge Computing ◽  
Internet Of Vehicles ◽  
The Cost

By bringing the computation and storage resources close proximity to the mobile network edge, mobile edge computing (MEC) is a key enabling technology for satisfying the Internet of Vehicles (IoV) infotainment applications’ requirements, e.g., video streaming service (VSA). However, the explosive growth of mobile video traffic brings challenges for video streaming providers (VSPs). One known issue is that a huge traffic burden on the vehicular network leads to increasing VSP costs for providing VSA to mobile users (i.e., autonomous vehicles). To address this issue, an efficient resource sharing scheme between underutilized vehicular resources is a promising solution to reduce the cost of serving VSA in the vehicular network. Therefore, we propose a new VSA model based on the lower cost of obtaining data from vehicles and then minimize the VSP’s cost. By using existing data resources from nearby vehicles, our proposal can reduce the cost of providing video service to mobile users. Specifically, we formulate our problem as mixed integer nonlinear programming (MINP) in order to calculate the total payment of the VSP. In addition, we introduce an incentive mechanism to encourage users to rent its resources. Our solution represents a strategy to optimize the VSP serving cost under the quality of service (QoS) requirements. Simulation results demonstrate that our proposed mechanism is possible to achieve up to 21% and 11% cost-savings in terms of the request arrival rate and vehicle speed, in comparison with other existing schemes, respectively.

scholarly journals Development and Testing of a Collision Avoidance Braking System for an Autonomous Vehicle

2019 ◽  
Vol 8 (12) ◽  
pp. 703-709
Keyword(s):  
Autonomous Vehicle ◽  
Test Results ◽  
Correct Operation ◽  
Braking Performance ◽  
System Parameters ◽  
Emergency Braking ◽  
Braking System ◽  
Good Consistency ◽  
Main Development ◽  
Outdoor Experiments

The article describes the main development and testing aspects of an emergency braking function for an autonomous vehicle. The purpose of this function is to prevent the vehicle from collisions with obstacles, either stationary or moving. An algorithm is proposed to calculate deceleration for the automated braking, which takes into account the distance to the obstacle and velocities of both the vehicle and the obstacle. In addition, the algorithm adapts to deviations from the required deceleration, which are inevitable in the real-world practice due to external and internal disturbances and unaccounted dynamics of the vehicle and its systems. The algorithm was implemented as a part of the vehicle’s mathematical model. Simulations were conducted, which allowed to verify algorithm’s operability and tentatively select the system parameters providing satisfactory braking performance of the vehicle. The braking function elaborated by means of modeling then was connected to the solenoid braking controller of the experimental autonomous vehicle using a real-time prototyping technology. In order to estimate operability and calibrate parameters of the function, outdoor experiments were conducted at a test track. A good consistency was observed between the test results and simulation results. The test results have proven correct operation of the emergency braking function, acceptable braking performance of the vehicle provided by this function, and its capability of preventing collisions.

scholarly journals Comparisons Between Braking Experiments and Longitudinal Train Dynamics Using Friction Coefficient and Braking Pressure Modeling in a Freight Train

2020 ◽  
Vol 14 (1) ◽  
pp. 154-163
Author(s):  
Don Bum Choi ◽  
Rag-Gyo Jeong ◽  
Yongkook Kim ◽  
Jangbom Chai
Keyword(s):  
Friction Coefficient ◽  
Time Integration ◽  
Expansion Method ◽  
Dynamics Simulation ◽  
Dynamic Simulations ◽  
Freight Train ◽  
Emergency Braking ◽  
Braking Distance ◽  
Train Dynamics ◽  
Simulation Results

Background: This paper describes the predictions and validation of the pneumatic emergency braking performance of a freight train consisting of a locomotive and 20 wagons, generally operated in Korea. It suggests the possibility of replacing the expensive and time-consuming train running tests with longitudinal train dynamic simulations. Methods: The simulation of longitudinal train dynamics of a freight train uses the time integration method of EN 14531. For reasonable simulation results, the characteristics of the train and brake equipment must be considered. For the train characteristics, specifications provided by the vehicle manufacturer are used. The braking characteristics are analyzed by friction coefficient tests and a braking pressure model. The friction coefficients of a locomotive and wagons are tested with a dynamo test bench and statistically expanded to account for variability. Freight trains should take into account the braking delay time. To reflect this in the simulation, the brake cylinder pressure pattern model uses pressures and exponential empirical equations measured at selective positions in a train of 50 vehicles. The simulation results are validated in comparison with those of the braking tests of a freight train consisting of 1 locomotive and 20 wagons. Results: The results of the longitudinal dynamics simulation show very similar results to the running test results based on the speed profile and braking distance. Conclusion: In particular, the statistical expansion method of the friction coefficient enables robust prediction of the distribution of the braking distance. The simulation can reduce or make up for costly and time-consuming repeated braking tests and reduce the risks that may arise during testing.

Intelligent Correction of Shift Schedule for Dual Clutch Transmissions Based on Different Driving Conditions

2011 ◽  
Vol 121-126 ◽  
pp. 3982-3987
Author(s):  
Yong Gang Liu ◽  
Da Tong Qin ◽  
Zhen Zhen Lei ◽  
Rui Ding
Keyword(s):  
Fuzzy Logic ◽  
Real Time ◽  
Time Shift ◽  
Correction Coefficient ◽  
Vehicle Speed ◽  
Shift Schedule ◽  
Shift Control ◽  
Driving Condition ◽  
Driving Conditions ◽  
Driver’S Intention

This paper focuses on intelligent correction of shift schedule for dual clutch transmissions based on different driving conditions. The problem of standard shift schedule has been presented, and the strategy has also been proposed to avoid shift hunting and unexpected shift. The driver’s intention and driving environment have been unified recognized as different driving conditions. A fuzzy logic technology has been used in driver’s attention recognition based on the throttle opening and its derivative. The standard shift schedule has been intelligently corrected at different driving condition separately. An algorithm based on correction coefficient of throttle opening and vehicle speed is proposed for intelligent correction. The corrected shift schedule can be directly used in real time shift control with suitable correction coefficient.

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