Journal articles: 'Autonomous braking'

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Kobiela, Fanny, and Arnd Engeln. "Autonomous emergency braking." ATZautotechnology 10, no. 5 (September 2010): 38–43. http://dx.doi.org/10.1007/bf03247187.

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Horri, Nadjim, Olivier Haas, Sheng Wang, Mathias Foo, and Manuel Silverio Fernandez. "Mode Switching Control Using Lane Keeping Assist and Waypoints Tracking for Autonomous Driving in a City Environment." Transportation Research Record: Journal of the Transportation Research Board 2676, no. 3 (November 13, 2021): 712–27. http://dx.doi.org/10.1177/03611981211056636.

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This paper proposes a mode switching supervisory controller for autonomous vehicles. The supervisory controller selects the most appropriate controller based on safety constraints and on the vehicle location with respect to junctions. Autonomous steering, throttle and deceleration control inputs are used to perform variable speed lane keeping assist, standard or emergency braking and to manage junctions, including roundabouts. Adaptive model predictive control with lane keeping assist is performed on the main roads and a linear pure pursuit inspired controller is applied using waypoints at road junctions where lane keeping assist sensors present a safety risk. A multi-stage rule based autonomous braking algorithm performs stop, restart and emergency braking maneuvers. The controllers are implemented in MATLAB® and Simulink™ and are demonstrated using the Automatic Driving Toolbox™ environment. Numerical simulations of autonomous driving scenarios demonstrate the efficiency of the lane keeping assist mode on roads with curvature and the ability to accurately track waypoints at cross intersections and roundabouts using a simpler pure pursuit inspired mode. The ego vehicle also autonomously stops in time at signaled intersections or to avoid collision with other road users.

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Vaibhav, R., N. Amutha Prabha, V. Indragandhi, M. Bharathidasan, S. Vasantharaj, and J. Sam Alaric. "Autonomous Braking System Using Linear Actuator." Journal of Sensors 2022 (November 22, 2022): 1–8. http://dx.doi.org/10.1155/2022/7707600.

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The most frequent cause of vehicle accidents (car, bike, truck, etc.) is the unexpected existence of barriers while driving. An automated braking system will assist and minimize such collisions and save the driver and other people’s lives and have a substantial influence on driver safety and comfort. An autonomous braking system is a complicated mechatronic system that incorporates a front-mounted ultrasonic wave emitter capable of creating and transmitting ultrasonic waves. In addition, a front-mounted ultrasonic receiver is attached to gather ultrasonic wave signals that are reflected. The distance between the impediment and the vehicle is determined by the reflected wave. Then, a microprocessor is utilized to control the vehicle’s speed depending on the detected pulse information, which pushes the brake pedal and applies the vehicle’s brakes extremely hard for safety. For work-energy at surprise condition for velocity 20 km/hr, the braking distance is 17.69 m, and for velocity 50 km/hr, the braking distance is 73.14.

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Rahman, Ataur, and Sany Izan Ihsan. "Autonomous Braking System: for Automobile Use." MIST INTERNATIONAL JOURNAL OF SCIENCE AND TECHNOLOGY 9 (December 23, 2021): 01–06. http://dx.doi.org/10.47981/j.mijst.09(02)2021.316(01-06).

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Road fatality and injury are a worldwide issue in the transportation industry. Road traffic accidents are becoming increasingly significant due to higher mortality, injury, and disability across the world, particularly in developing and transitional economies. Eighty-five percent of the total road traffic fatalities occur in developing nations, with Asia-Pacific accounting for roughly half of them. A variety of factors influence road safety, including technological, physical, social, and cultural factors. The purpose of this research was to design an autonomous braking system (AuBS). Using the Adaptive Neuro-Fuzzy Intelligent System (ANFIS), a DC motor, sensors, and SAuBS have been developed to customize the traditional hydraulic braking system. The genetic algorithm has been developed to simulate the fundamental characteristics of the automotive braking system. The AuBS system goal is to slow the car without the driver's help infrequent braking when the vehicle is moving at slower speeds. When the ANFIS performance is compared to that of the AuBS model, it is discovered that the ANFIS performs roughly 15% better.

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Rosén, Erik, Jan-Erik Källhammer, Dick Eriksson, Matthias Nentwich, Rikard Fredriksson, and Kip Smith. "Pedestrian injury mitigation by autonomous braking." Accident Analysis & Prevention 42, no. 6 (November 2010): 1949–57. http://dx.doi.org/10.1016/j.aap.2010.05.018.

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Hwang, Myeong Hwan, Gye Seong Lee, Eugene Kim, Hyeon Woo Kim, Seungha Yoon, Teressa Talluri, and Hyun Rok Cha. "Regenerative Braking Control Strategy Based on AI Algorithm to Improve Driving Comfort of Autonomous Vehicles." Applied Sciences 13, no. 2 (January 10, 2023): 946. http://dx.doi.org/10.3390/app13020946.

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Recent studies on autonomous vehicles focus on improving driving efficiency and ignore driving comfort. Because acceleration and jerk affect driving comfort, we propose a comfort regenerative braking system (CRBS) that uses artificial neural networks as a vehicle-control strategy for braking conditions. An autonomous vehicle driving comfort is mainly determined by the control algorithm of the vehicle. If the passenger’s comfort is initially predicted based on acceleration and deceleration limits, the control strategy algorithm can be adjusted, which would be helpful to improve ride comfort in autonomous vehicles. We implement numerical analysis of the control strategy, ensuring reduced jerk conditions. In addition, backward propagation was applied to estimate the braking force limits of the regenerative braking systems more accurately. The developed algorithm was verified through the Car Sim and MATLAB/Simulink simulations by comparing them with the conventional braking system. The proposed CRBS offers effective regenerative braking within limits and ensures increased driving comfort to passengers.

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Li, Guo Qiang, and Xing Ye Wang. "Research on Electronic Pneumatic Steering and Braking Control Technology for Autonomous Tracked Vehicles." Applied Mechanics and Materials 577 (July 2014): 359–63. http://dx.doi.org/10.4028/www.scientific.net/amm.577.359.

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To realize the autonomous driving of a certain tracked vehicle, the paper has a research on its steering and braking control technology. According to the steering and braking device’s structure and work principle on the original vehicle, the paper design an electronic pneumatic steering and braking control system before analyzing the design request of the system and introduce the system’s work principle. Applying this system to the original vehicle’s autonomous transformation, a test was conducted on the vehicle, the test prove that the electronic pneumatic steering and braking control system can well satisfied the tracked vehicles’ request of steering and braking.

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Binshuang, Zheng, Chen Jiaying, Zhao Runmin, and Huang Xiaoming. "Skid resistance demands of asphalt pavement during the braking process of autonomous vehicles." MATEC Web of Conferences 275 (2019): 04002. http://dx.doi.org/10.1051/matecconf/201927504002.

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As the main operationality of AVs, the braking property is directly related to traffic safety. Major traffic accidents are often related to the braking distance, the side slip and hydroplaning during the emergency braking, which depends on the pavement skid resistance. Therefore, the estimation to relate AVs braking distance requirements with pavement peak friction coefficient to ensure a safe driving condition on expressway is of high practical significance. In this paper, the effect of AVs on braking performance parameters and dynamic friction on tire-pavement interaction are investigated. Based on the field test of the Coastal highway in Jiangsu province of China, this paper proposes an algorithm to determine time-dependent braking distance of AVs considering pavement frictional properties. According to the algorithm, an AVs braking system is provided to reach the maximum braking force for improving the AVs traffic safety. Furthermore, it revises the braking distance formula of Design Specification for Highway Alignment and the skid resistance threshold adopted by Technical Specifications for Maintenance of Highway Asphalt Pavement.

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Badea, Gabriel, Marius Toma, Dan Alexandru Micu, Gheorghe Frăţilă, and Ştefan Saragea. "Modelling and simulation automatic braking systems for vehicles." IOP Conference Series: Materials Science and Engineering 1235, no. 1 (March 1, 2022): 012033. http://dx.doi.org/10.1088/1757-899x/1235/1/012033.

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Abstract An automatic braking system is an important future step in attending the autonomous vehicle. This system increases the active safety of a vehicle, significantly reducing road accidents, and lowering the effects of accidents. The paper will present the steps that will develop the autonomous braking systems in conformity with the Society of Automotive Engineers (SAE) from the USA. As well the paper will present the modelling and simulating of the automatic braking systems of a vehicle from the middle class using LMS Amesim software.

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WHEATLEY, Greg, and Robiul Islam RUBEL. "AN AUTONOMOUS BRAKING CONTROL SYSTEM FOR A 2017 YAMAHA GRIZZLY 700." Scientific Journal of Silesian University of Technology. Series Transport 115 (June 30, 2022): 211–26. http://dx.doi.org/10.20858/sjsutst.2022.115.15.

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Weed control is an important issue for environmental protection all around the world. Traditional hand weed control is laborious whereas chemical control is costly and a threat to the atmosphere. A chemical patch weed control system is an optimized system but lacks cheap technical equipment. This research outlines a design process and test of a braking system that can be applied during the designing of an autonomous braking system for a 2017 Yamaha Grizzly 700. The system is intended to be used as an autonomous weed chemical spraying. A bolt-on approach that did not require any manipulation of the stock, an internal braking system was followed to reduce the complexity and installation time of multiple systems. Three different types of autonomous braking system solutions were initially investigated, with the linear actuator solution being decided on through the assistance of a weighted decision matrix. The system was designed around a 30 kg hand force; however, a spare actuator of approximately 20 kg of force was repurposed and used instead. Finite element analysis concluded that all major components within the proposed system were suitable for a lifetime of at least 1,000,000 cycles with a mild steel yield stress failure criterion of 370 MPa. A stationary test for the system was conducted to determine the success of the system, which pushed the brake lever approximately 25% of its disengaged handlebar to lever length. The resulting system met the requirements of the expectation and could be used to apply the ATV’s brakes autonomously while retracting the gear interlocking mechanism enough to change gears.

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Kobiela, Fanny, and Arnd Engeln. "Autonomous Emergency Braking Studies on Driver Behaviour." Auto Tech Review 1, no. 8 (August 2012): 34–38. http://dx.doi.org/10.1365/s40112-012-0106-9.

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12

Milanés, V., C. González, J. E. Naranjo, E. Onieva, and T. De Pedro. "Electro-hydraulic braking system for autonomous vehicles." International Journal of Automotive Technology 11, no. 1 (February 2010): 89–95. http://dx.doi.org/10.1007/s12239-010-0012-6.

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Kobiela, Fanny, and Arnd Engeln. "Autonomous emergency braking studies on driver behaviour." ATZ worldwide 112, no. 10 (October 2010): 4–8. http://dx.doi.org/10.1007/bf03225144.

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N, Nagendran, Rani K S, Punitha P, Vaishnav V P, Balaji V, and Na nagendran@gmail com S. "Reactive Braking System." International Journal of Engineering & Technology 7, no. 3.34 (September 1, 2018): 372. http://dx.doi.org/10.14419/ijet.v7i3.34.19229.

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This paper is based on the simplifying technique of the existing technology called Autonomous Emergency Braking (AEB) by using a simple electronic setup which can be easily installed in all the existing four-wheelers without changing its existing working system. By using this technology, the number of accidents due to human errors can be avoided in large scale for both the drivers and the pedestrians. This project aims to reduce the errors caused by the improper braking of the driver.

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Li, Tao, Shuo Zhang, Gang Xiao, Minqi Wang, Hanwen Zhong, and Jianghua Feng. "Brake Instability Dynamic Model and Active Control Strategy for a Multiunit Articulated Rubber-Wheel Autonomous Rail Rapid Transit System." Sustainability 14, no. 21 (November 4, 2022): 14531. http://dx.doi.org/10.3390/su142114531.

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Due to the particularity of the structure, the dynamic properties of multiunit articulated rubber-wheel autonomous rail rapid transit system are very complex, which increases the difficulty of studying its braking stability. In this paper, a dynamic analysis model for the emergency braking of a multiunit articulated rubber-wheel autonomous rail rapid transit system is established by introducing the axle load transfer, suspension deformation compatibility equation, articulation force relationship equations, etc. Based on an in-depth analysis of the risks of the lateral swing instability and their formation mechanisms, an active control strategy for the multiunit articulated rubber-wheel autonomous rail rapid transit system under emergency braking conditions is innovatively proposed to ensure the stability of the vehicle, with the shortest braking distance as the optimization goal. Through simulation and experimentation, the established dynamic model is confirmed to approach the real vehicle well, and the feasibility of the active control strategy is proved.

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Min, Kyunghan, Gyubin Sim, Seongju Ahn, Inseok Park, Seungjae Yoo, and Jeamyoung Youn. "Multi-Level Deceleration Planning Based on Reinforcement Learning Algorithm for Autonomous Regenerative Braking of EV." World Electric Vehicle Journal 10, no. 3 (September 16, 2019): 57. http://dx.doi.org/10.3390/wevj10030057.

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A smart regenerative braking system, which is an advanced driver assistance system of electric vehicles, automatically controls the regeneration torque of the electric motor to brake the vehicle by recognizing the deceleration conditions. Thus, this autonomous braking system can provide driver convenience and energy efficiency by suppressing the frequent braking of the driver brake pedaling. In order to apply this assistance system, a deceleration planning algorithm should guarantee the safety deceleration under diverse driving situations. Furthermore, the planning algorithm suppresses a sense of heterogeneity by autonomous braking. To ensuring these requirements for deceleration planning, this study proposes a multi-level deceleration planning algorithm which consists of the two representative planning algorithms and one planning management. Two planning algorithms, which are the driver model-based planning and optimization-based planning, generate the deceleration profiles. Then, the planning management determines the optimal planning result among the deceleration profiles. To obtain an optimal result, planning management is updated based on the reinforcement learning algorithm. The proposed algorithm was learned and validated under a simulation environment using the real vehicle experimental data. As a result, the algorithm determines the optimal deceleration vehicle trajectory to autonomous regenerative braking.

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Garrosa, María, Ester Olmeda, Sergio Fuentes del Toro, and Vicente Díaz. "Holistic Vehicle Instrumentation for Assessing Driver Driving Styles." Sensors 21, no. 4 (February 18, 2021): 1427. http://dx.doi.org/10.3390/s21041427.

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Nowadays, autonomous vehicles are increasing, and the driving scenario that includes both autonomous and human-driven vehicles is a fact. Knowing the driving styles of drivers in the process of automating vehicles is interest in order to make driving as natural as possible. To this end, this article presents a first approach to the design of a controller for the braking system capable of imitating the different manoeuvres that any driver performs while driving. With this aim, different experimental tests have been carried out with a vehicle instrumented with sensors capable of providing real-time information related to the braking system. The experimental tests consist of reproducing a series of braking manoeuvres at different speeds on a flat floor track following a straight path. The tests distinguish between three types of braking manoeuvre: maintained, progressive and emergency braking, which cover all the driving circumstances in which the braking system may intervene. This article presents an innovative approach to characterise braking types thanks to the methodology of analysing the data obtained by sensors during experimental tests. The characterisation of braking types makes it possible to dynamically classify three driving styles: cautious, normal and aggressive. The proposed classifications allow it possible to identify the driving styles on the basis of the pressure in the hydraulic brake circuit, the force exerted by the driver on the brake pedal, the longitudinal deceleration and the braking power, knowing in all cases the speed of the vehicle. The experiments are limited by the fact that there are no other vehicles, obstacles, etc. in the vehicle’s environment, but in this article the focus is exclusively on characterising a driver with methods that use the vehicle’s dynamic responses measured by on-board sensors. The results of this study can be used to define the driving style of an autonomous vehicle.

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Zheng, Binshuang, Xiaoming Huang, Junyao Tang, Jiaying Chen, Runmin Zhao, Zhengqiang Hong, Tao Tang, and Meiling Han. "Evaluation on Braking Stability of Autonomous Vehicles Running along Curved Sections Based on Asphalt Pavement Adhesion Properties." Journal of Advanced Transportation 2022 (May 29, 2022): 1–20. http://dx.doi.org/10.1155/2022/7348554.

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As the main objective influencing factor on the brake safety of autonomous vehicles, pavement texture information is directly related to road surface antiskid performance. However, in the brake system of autonomous vehicles, the influence of road surface adhesion characteristics on braking stability is seldomly considered. To study the braking stability of autonomous vehicles on curved sections under different road conditions, the advanced close-range photogrammetry system was utilized to extract the road surface texture information. Thereafter, the power spectral density (PSD) of the road surface was calculated by MATLAB to obtain the pavement adhesion coefficient curves based on the Persson friction theory model under different road conditions. Considering the pavement adhesion characteristics, the braking model of autonomous vehicles was built in Simulink, and then, the braking performance on curved sections was analyzed with CarSim/Simulink cosimulation. The results indicate that, according to the adhesion coefficient of different asphalt pavement types under different road conditions, the ranking order is open-grade friction course (OGFC) > stone matrix asphalt (SMA) > dense-graded asphalt concrete (AC). In addition, both the maximum lateral offset distances and the maximum lateral forces of the tires decrease as the curve radius gradually increases under different road conditions. It can also be found that there is a relatively uniform vertical forces distribution of the tire when the curve radius is no less than 100 m, and the limit speed of the vehicle varies parabolically with increasing in curve radius. Compared with dry road, the reduction of vehicle braking deceleration is more significant and the yaw rate is greater on wet road. Last but not least, the braking comfort with a radius of 200 m is the best according to the comfort index (CI) in International Standard ISO, in which the comfort level can be sorted into six levels.

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Gounis, Konstantinos, and Nick Bassiliades. "Intelligent momentary assisted control for autonomous emergency braking." Simulation Modelling Practice and Theory 115 (February 2022): 102450. http://dx.doi.org/10.1016/j.simpat.2021.102450.

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Ezawa, Kazuhiro, Pongsathorn Raksincharoensak, and Masao Nagai. "Hazard Anticipatory Autonomous Braking Control System Based on 2-D Pedestrian Motion Prediction." Journal of Robotics and Mechatronics 27, no. 6 (December 18, 2015): 636–44. http://dx.doi.org/10.20965/jrm.2015.p0636.

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<div class=""abs_img""><img src=""[disp_template_path]/JRM/abst-image/00270006/05.jpg"" width=""300"" /> The focused scenario</div>This paper discusses 2-dimensional (2-D) pedestrian motion prediction and autonomous braking control for enhancing the collision avoidance performance of an active safety system. The paper targets a typical scenario involving a pedestrian walking toward a parked vehicle on a crowded urban road. The pedestrian is not expected to continue walking in a straight line. Conventional first-order motion prediction accuracy alone is not enough to predict the pedestrian motion because prediction is based on the pedestrian’s current position and velocity within a finite time. We formulated a 2-D pedestrian motion model of the parked vehicle based on learning the measured trajectory of pedestrians in the same scenario. We then designed an autonomous braking control system based on whether the vehicle will overtake a pedestrian. We evaluated the validity of the proposed autonomous braking control system in simulation experiments.

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Zheng, Binshuang, Zhengqiang Hong, Junyao Tang, Meiling Han, Jiaying Chen, and Xiaoming Huang. "A Comprehensive Method to Evaluate Ride Comfort of Autonomous Vehicles under Typical Braking Scenarios: Testing, Simulation and Analysis." Mathematics 11, no. 2 (January 16, 2023): 474. http://dx.doi.org/10.3390/math11020474.

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To highlight the advantages of autonomous vehicles (AVs) in modern traffic, it is necessary to investigate the sensing requirement parameters of the road environment during the vehicle braking process. Based on the texture information obtained using a field measurement, the braking model of an AV was built in Simulink and the ride comfort under typical braking scenarios was analyzed using CarSim/Simulink co-simulation. The results showed that the proposed brake system for the AV displayed a better performance than the traditional ABS when considering pavement adhesion characteristics. The braking pressure should be controlled to within the range of 4 MPa~6 MPa on a dry road, while in wet road conditions, the pressure should be within 3 MPa~4 MPa. When steering braking in dry road conditions, the duration of the “curve balance state” increased by about 57.14% compared with wet road conditions and the recommended curve radius was about 100 m. The slope gradient had a significant effect on the initial braking speed and comfort level. Overall, the ride comfort evaluation method was proposed to provide theoretical guidance for AV braking strategies, which can help to complement existing practices for road condition assessment.

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Yang, Wei, Xiang Zhang, Qian Lei, and Xin Cheng. "Research on Longitudinal Active Collision Avoidance of Autonomous Emergency Braking Pedestrian System (AEB-P)." Sensors 19, no. 21 (October 28, 2019): 4671. http://dx.doi.org/10.3390/s19214671.

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The AEB-P (Autonomous Emergency Braking Pedestrian) system has the functional requirements of avoiding the pedestrian collision and ensuring the pedestrian’s life safety. By studying relevant theoretical systems, such as TTC (time to collision) and braking safety distance, an AEB-P warning model was established, and the traffic safety level and work area of the AEB-P warning system were defined. The upper-layer fuzzy neural network controller of the AEB-P system was designed, and the BP (backpropagation) neural network was trained by collected pedestrian longitudinal anti-collision braking operation data of experienced drivers. Also, the fuzzy neural network model was optimized by introducing the genetic algorithm. The lower-layer controller of the AEB-P system was designed based on the PID (proportional integral derivative controller) theory, which realizes the conversion of the expected speed reduction to the pressure of a vehicle braking pipeline. The relevant pedestrian test scenarios were set up based on the C-NCAP (China-new car assessment program) test standards. The CarSim and Simulink co-simulation model of the AEB-P system was established, and a multi-condition simulation analysis was performed. The results showed that the proposed control strategy was credible and reliable and could flexibly allocate early warning and braking time according to the change in actual working conditions, to reduce the occurrence of pedestrian collision accidents.

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Kim, Taewoo, Seulgi Heo, Kyongsu Yi, Kyong Chan Min, and Jae Kon Shin. "Robust Autonomous Emergency Braking Algorithm for Vulnerable Road Users." Transactions of the Korean Society of Mechanical Engineers - A 42, no. 7 (July 31, 2018): 611–19. http://dx.doi.org/10.3795/ksme-a.2018.42.7.611.

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Mimura, Yasuhiro, Ryosuke Ando, Keiichi Higuchi, and Jia Yang. "Recognition on trigger condition of autonomous emergency braking system." Journal of Safety Research 72 (February 2020): 239–47. http://dx.doi.org/10.1016/j.jsr.2019.12.018.

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Kim, Hyunkyu, Kyungsik Shin, Iljoon Chang, and Kunsoo Huh. "Autonomous Emergency Braking Considering Road Slope and Friction Coefficient." International Journal of Automotive Technology 19, no. 6 (December 2018): 1013–22. http://dx.doi.org/10.1007/s12239-018-0098-9.

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Duan, Jingliang, Renjie Li, Lian Hou, Wenjun Wang, Guofa Li, Shengbo Eben Li, Bo Cheng, and Hongbo Gao. "Driver braking behavior analysis to improve autonomous emergency braking systems in typical Chinese vehicle-bicycle conflicts." Accident Analysis & Prevention 108 (November 2017): 74–82. http://dx.doi.org/10.1016/j.aap.2017.08.022.

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Begizhonov, Shakhrom, Polina Buyvol, Irina Makarova, and Eduard Tsybunov. "Parameterization of the ABS electronic control unit for increasing the autonomous trucks’ active safety." MATEC Web of Conferences 341 (2021): 00026. http://dx.doi.org/10.1051/matecconf/202134100026.

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The article is devoted to the issue of improving the autonomous vehicles safety. The anti-lock braking system was chosen as the object of the study, since it is one of the components of the vehicle active safety during emergency braking. Its functioning varies depending on parameters such as vehicle type, transmission type, external and internal steering wheel angles. It is necessary to parameterize correctly the electronic control unit of the anti-lock braking system depending on the specific values of these parameters. For this, a software module was developed that reads the values of the vehicle parameters from a file and sends their array to the electronic control unit. Then we can check the result: how the block responded to the sent request -positively or negatively. All this will speed up the parameterization process, increase its accuracy, preventing the occurrence of operator errors during its implementation.

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Cassese, Giovanni, Cosimo Lucci, Giovanni Savino, and Niccolò Baldanzini. "Analysis of the rider’s body movement during the intervention of the Autonomous Emergency Braking system for Motorcycles (MAEB)." IOP Conference Series: Materials Science and Engineering 1214, no. 1 (January 1, 2022): 012047. http://dx.doi.org/10.1088/1757-899x/1214/1/012047.

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Abstract Among the rider assistance systems for powered-two-wheelers (PTWs) that are currently in the developing stage, autonomous emergency braking (identified by the acronym MAEB - Motorcycle Autonomous Emergency Braking) was shown to be promising to significantly improve the safety of such vehicles. This system, which is already available on passenger cars and trucks (known as AEB), reduces the vehicle speed in the event of a forthcoming collision. The lack of implementation of AEB on standard motorcycles is due to the characteristic capsize instability of PTWs and their complex dynamics, which is, strongly influenced by the motion of the rider. In a recent field-test campaign within the EU funded project “PIONEERS”, tests were conducted with common riders as participants to evaluate the intervention of MAEB in urban riding scenarios. A combined analysis of the data recorded from the vehicle, data related to the movement of the rider’s body measured through an inertial measurement unit and videos recorded during the test, allowed characterizing the different behaviours of the rider’s body in response to the activation of the automatic braking system in straight riding conditions. The results showed that body movement can be used as an indicator of the riders’ ability to control the vehicle under automatic braking conditions. In addition, in tests conducted with 0.5 g automatic decelerations, riders showed to be able to recover to natural riding position within the timeframe of the automatic braking activation event. This study defined an innovative method for evaluating the response of motorcyclists to the braking intervention and provides insights into the applicability of MAEB on standard vehicles.

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Li, Ning, Jiarao Yang, Junping Jiang, Feng Hong, Yang Liu, and Xiaobin Ning. "Study on Speed Planning of Signalized Intersections with Autonomous Vehicles Considering Regenerative Braking." Processes 10, no. 7 (July 20, 2022): 1414. http://dx.doi.org/10.3390/pr10071414.

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In order to reduce the energy consumption caused by the frequent braking of vehicles at signalized intersections, an optimized speed trajectory control method is proposed, based on braking energy recovery efficiency (BERE) in connection with an automated system for vehicle real-time interaction with roadside facilities and regional central control. Our objectives were as follows; firstly, to establish the simulation model of the hybrid energy regenerative braking system (HERBS) and to verify it by bench test. Secondly, to build up the genetic algorithm (GA) optimization model for the deceleration stopping of the HERBS. Then, to obtain signal light status and timing information to be the constraints; the BERE is to be the optimized objective, resulting in optimization for the speed trajectory under the deceleration stopping condition of a single signalized intersection. Finally, vehicle simulations in ADVISOR software are utilized to validate the optimization results. The results show that the BERE during deceleration stopping at a single signalized intersection after the speed trajectory optimization is 36.21% higher than that of inexperienced drivers, and 7.82% higher than that of experienced drivers.

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Singh, Gaurav, and Pravin Kumar Singh. "Automatic Braking System with Bumper Actuation." Journal of Mechanical and Construction Engineering (JMCE) 2, no. 1 (April 11, 2022): 1–15. http://dx.doi.org/10.54060/jmce/002.01.002.

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For most people nowadays, driving is a common activity. Technology has undergone significant modifications, resulting in an increase in speed. However, high speed contributes to traffic accidents. When the driver is not attentive, ordinary braking is insufficient to prevent accidents. The braking system must be improved further in order to brake a vehicle when the driver is unable to do so, which may necessitate the use of an automatic braking system. The vehicle may brake without the driver's assistance using this autonomous braking technology. An automated braking system is an important aspect of car safety technology. It's a sophisticated system that's designed to avoid colliding with another vehicle or an obstacle of some sort. These systems use sensors like radar, video, infrared, and ultrasonic to scan for potential obstacles in front of the car and then use brake control to avoid a collision if the object is found.

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Santos, Carlos Renato Borges dos. "Simulação de frenagem de veículos com motoristas, veículos autônomos e veículos colaborativos." ForScience 10, no. 1 (June 24, 2022): e00905. http://dx.doi.org/10.29069/forscience.2022v10n1.e905.

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Os desafios enfrentados pelos veículos autônomos nos quesitos localização, navegação, detecção de obstáculos e segurança ainda necessitam de soluções, permitindo um vasto campo para estudos e pesquisas. A gradual inserção de veículos autônomos nas vias de trânsito aumentará o número de encontros entre esses veículos, tornando viável a comunicação entre os mesmos, designada V2V (vehicle to vehicle). Este trabalho realiza uma revisão bibliográfica sobre a colaboração veicular e mostra os resultados da simulação de cenários de frenagem, com o objetivo de comparar os efeitos do tempo de reação de veículos comuns, veículos autônomos eveículos colaborativos. Utilizou-se o Matlab para realizar simulações de pelotões de veículos andando em fila única. Os resultados de simulação mostram a influência do tempo de reação e de transmissão da mensagem na tentativa de evitar colisões. Palavras-chave: Colaboração veicular. Frenagem de emergência. Simulação. Veículos autônomos. Simulation of braking vehicles with drivers, autonomous vehicles and collaborative vehicles Abstract The challenges faced by autonomous vehicles in terms of location, navigation, detection of obstacles and safety still need solutions, allowing a vast field for studies and research. The gradual insertion of autonomous vehicles on traffic routes will increase the number of encounters between these vehicles, making communication between them viable, known as V2V (vehicle to vehicle). This work performs a literature review on vehicular collaboration and shows the simulation results of braking scenarios, in order to compare the reaction time effects of common vehicles, autonomous vehicles and collaborative vehicles. Matlab was used to carry out vehicles platoon simulations traveling in a single file. The simulation results show the influence of reaction time and message transmission in an attempt to avoid collisions. Keywords: Autonomous vehicles. Emergency braking. Simulation. Vehicular collaboration.

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Kim, Changwon, Joonho Seo, Dongkyu Lee, Jun-uk Chu, and Ohwon Kwon. "Deep Learning based Customized Autonomous Emergency Braking System Parameter Extraction." Journal of Institute of Control, Robotics and Systems 25, no. 8 (August 31, 2019): 671–76. http://dx.doi.org/10.5302/j.icros.2019.19.0111.

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TSUCHIYA, Kouichi, Hiroshi MOURI, and Masao NAGAI. "2201 Development of Head-on Collision Avoidance Autonomous Braking Control." Proceedings of the Transportation and Logistics Conference 2014.23 (2014): 115–18. http://dx.doi.org/10.1299/jsmetld.2014.23.115.

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Gwehenberger, Johann, Isabella Ostermaier, and Marcel Borrack. "Effectiveness of Autonomous Emergency Braking Systems and Automated Driving Functions." ATZ worldwide 121, no. 7-8 (July 2019): 48–53. http://dx.doi.org/10.1007/s38311-019-0072-9.

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Kavitha, C., B. Ashok, K. Nanthagopal, Rohan Desai, Nisha Rastogi, and Siddhanth Shetty. "Braking distance algorithm for autonomous cars using road surface recognition." IOP Conference Series: Materials Science and Engineering 263 (November 2017): 062034. http://dx.doi.org/10.1088/1757-899x/263/6/062034.

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Funkhouser, Kelly, and Frank Drews. "Putting the Brakes on Autonomous Vehicle Control." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 60, no. 1 (September 2016): 1859–63. http://dx.doi.org/10.1177/1541931213601424.

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The assimilation of automation in commuter vehicles is rapidly increasing, as too are the concerns with these technologies. Human interaction with autonomous vehicles must be thoroughly researched to understand the quantification and qualification of interactive behaviors with these systems. We developed a study using a high-fidelity driving simulator to mimic probable breakdowns with these systems to better understand the subsequent human responses and to explore the necessary technological requirements to overcome potential problems. 30 participants engaged in a driving scenario switching between manual and autonomous vehicle control. We accounted for individual differences in braking reaction time while simultaneously engaging in a secondary cognitive task during times of autonomous vehicle control. Results show the average RT for baseline scenarios without the cognitive task was 832.1 milliseconds while the average RT for baseline scenarios with the cognitive task was 908.4 milliseconds; a 9.17% significant increase. The average RT for the autonomous scenario was 1357.0 milliseconds; a significant increase of 49.38% over the baseline scenario with the cognitive task that can be attributed to the addition of automation. We found a positive linear correlation of time spent in autonomous control and subsequent braking reaction time. Additionally, cognitive task difficulty, attention allocation, self-reported mental demand, fatigue, and heart rate affect reaction time when cued to take control of the vehicle.

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Carabulea, Laurentiu, Claudiu Pozna, Csaba Antonya, Călin Husar, and Alexandra Băicoianu. "The influence of the Advanced Emergency Braking System in critical scenarios for autonomous vehicles." IOP Conference Series: Materials Science and Engineering 1220, no. 1 (January 1, 2022): 012045. http://dx.doi.org/10.1088/1757-899x/1220/1/012045.

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Abstract This paper proposes use indications for an Advanced Emergency Braking System (AEBS) module developed in Matlab and included in a Simcenter Prescan simulation. The analysed indications depend on a Long-Range Radar (LRR) and Short-Range Radar (SRR) beam range, on the speed of the autonomous vehicle and on the time between the detection of the obstacle in front of the autonomous vehicle and the time the obstacle starts to move. The simulated scenario consists of an autonomous vehicle that travels at a certain speed, where another vehicle starts to move from a bus station after a sudden stop, challenging the autonomous vehicle to stop in a safe manner and in a short time.

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Veneroso, L., F. Alfatti, C. Annicchiarico, and R. Capitani. "Modelling, testing and validation of an innovative AEB control logic on a Hardware-in-the-loop test bench." IOP Conference Series: Materials Science and Engineering 1275, no. 1 (February 1, 2023): 012041. http://dx.doi.org/10.1088/1757-899x/1275/1/012041.

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Abstract AEB, autonomous emergency braking, is an active safety system designed to prevent vehicle frontal collision. The most diffused AEB systems are based on simple Bang Bang control logic, which could often avoid, or at least mitigate collision effects, but their effectiveness can still be improved by increasing system repeatability. The aim of this study is to model and test an innovative AEB control logic that will increase system reliability by compensating for the non-immediate response of the braking system to braking requests. Using a hardware-in-the-loop test bench with two different braking systems implemented, the new controller was tested simulating the CCRs and CCRm scenarios, used by Euro NCAP for AEB system assessment. By compensating for the delay introduced by the response of two different braking systems, the innovative control logic stops the VUT, Vehicle Under Test, at the desired safety distance from the GVT, Global Vehicle Target.

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Fuentes del Toro, Sergio, Silvia Santos-Cuadros, Ester Olmeda, and José Luis San Román. "Study of the Emergency Braking Test with an Autonomous Bus and the sEMG Neck Response by Means of a Low-Cost System." Micromachines 11, no. 10 (October 13, 2020): 931. http://dx.doi.org/10.3390/mi11100931.

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Nowadays, due to the advances and the increasing implementation of the autonomous braking systems in vehicles, the non-collision accident is expected to become more common than a crash when a sudden stop happens. The most common injury in this kind of accident is whiplash or cervical injury since the neck has high sensitivity to sharp deceleration. To date, biomechanical research has usually been developed inside laboratories and does not entirely represent real conditions (e.g., restraint systems or surroundings of the experiment). With the aim of knowing the possible neck effects and consequences of an automatic emergency braking inside an autonomous bus, a surface electromyography (sEMG) system built by low-cost elements and developed by us, in tandem with other devices, such as accelerometers or cameras, were used. Moreover, thanks to the collaboration of 18 participants, it was possible to study the non-collision effects in two different scenarios (braking test in which the passenger is seated and looking ahead while talking with somebody in front of him (BT1) and, a second braking test where the passenger used a smartphone (BT2) and nobody is seated in front of him talking to him). The aim was to assess the sEMG neck response in the most common situations when somebody uses some kind of transport in order to conclude which environments are riskier regarding a possible cervical injury.

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Wasilewski, Piotr, Krystian Chojnowski, and Rafał Grądzki. "Autocalibration of gyroscope based two-step regulator for autonomous vehicles." MATEC Web of Conferences 182 (2018): 01030. http://dx.doi.org/10.1051/matecconf/201818201030.

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In this article was presented an auto calibration algorithm based on a two-step regulator and gyroscope readings. Unable to use PID, as the PWM signal causes the motors to overheat, it was decided to introduce a two-step algorithm. This type of controller reaches the setpoint much faster, though an error is present. Gyroscope is used to sample angular speed and then integrate these values to get the angle. To calibrate the offsets the robot performs a calibration run during which it measures and averages the error on each gyroscope axis while no movement is present. Afterwards it makes a characteristics of braking angle and angular speed. Interpolated polynomial from 13 samples allows to designate the point in time where the braking has to start to achieve the desired angle. The calibration aims for adjusting the parameters of movement depending on the surface it runs on. Additional check is made using encoders to estimate the accuracy of gyroscope output.

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Alsuwian, Turki, Rana Basharat Saeed, and Arslan Ahmed Amin. "Autonomous Vehicle with Emergency Braking Algorithm Based on Multi-Sensor Fusion and Super Twisting Speed Controller." Applied Sciences 12, no. 17 (August 24, 2022): 8458. http://dx.doi.org/10.3390/app12178458.

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The automobile revolution and growth in the number of cars produced several issues, and vehicle accidents remain one of the most serious road-related issues. Human mistakes and a failure to brake quickly are the main causes of accidents. There may be serious outcomes to driving when distracted. To address the aforementioned issues, an autonomous emergency braking system (AEBS) was developed. To support such an AEBS, scalable, reliable, secure, fault-tolerant, and interoperable technologies are required. An advanced emergency braking system (EBS) with sensor fusion is proposed in this paper that can autonomously identify a probable forward collision and activate the vehicle braking system to brake the vehicle to avoid or mitigate a collision. Additionally, it provides a non-linear speed controller that facilitates the AEBS to apply the brakes in an emergency. Sensor fusion using lidar, radar, and vision sensors makes the AEBS more efficient and more reliable to detect vehicles or obstacles and decreases the chance of collision to a minimum level. A MATLAB/Simulink environment was used for simulation experiments and the results demonstrated the stable operation of the AEBS to avoid forward collisions in the event of an error in the measurement of any one sensor while any vehicle is detected. The presented work establishes that the EBS sensor fusion unit is a highly reliable solution for detecting the leading vehicle at the proper time and the AEBS controller can apply the brake in the situation of forwarding obstacle detection.

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Wu, Tong, Jing Li, and Xuan Qin. "Braking performance oriented multi–objective optimal design of electro–mechanical brake parameters." PLOS ONE 16, no. 5 (May 19, 2021): e0251714. http://dx.doi.org/10.1371/journal.pone.0251714.

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Excellent braking performance is the premise of safe driving, and improve the braking performance by upgrading structures and optimizing parameters of braking systems has become the pursuit of engineers. With the development of autonomous driving and intelligent connected vehicle, new structural schemes such as electro–mechanical brakes (EMBs) have become the future of vehicle braking systems. Meanwhile, many scholars have dedicated to the research on the parameters optimization of braking systems. While, most of the studies focus on reducing the brake size and weight, improving the brake responses by optimizing the parameters, almost not involving the braking performance, and the optimization variables are relatively single. On these foundations, a multi–objective optimal design of EMB parameters is proposed to enhance the vehicle’s braking performance. Its objectives and constraints were defined based on relevant standards and regulations. Subsequently, the decision variables were set, and optimal math model was established. Furthermore, the co–simulation platform was constructed, and the optimal design and simulation analyses factoring in the crucial structural and control parameters were performed. The results confirmed that the maximum braking pressure response time of the EMB is decreased by approximately 0.3 s, the stopping distance (SD) of 90 km/h–0 is shortened by about 3.44 m. Moreover, the mean fully developed deceleration (MFDD) is increased by 0.002 g, and the lateral displacement of the body (LD) is reduced by about 0.037 m. Hence, the vehicle braking performance is improved.

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Woo, Joo, Ji-Hyeon Baek, So-Hyeon Jo, Sun Young Kim, and Jae-Hoon Jeong. "A Study on Object Detection Performance of YOLOv4 for Autonomous Driving of Tram." Sensors 22, no. 22 (November 21, 2022): 9026. http://dx.doi.org/10.3390/s22229026.

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Recently, autonomous driving technology has been in the spotlight. However, autonomous driving is still in its infancy in the railway industry. In the case of railways, there are fewer control elements than autonomous driving of cars due to the characteristics of running on railways, but there is a disadvantage in that evasive maneuvers cannot be made in the event of a dangerous situation. In addition, when braking, it cannot be decelerated quickly for the weight of the body and the safety of the passengers. In the case of a tram, one of the railway systems, research has already been conducted on how to generate a profile that plans braking and acceleration as a base technology for autonomous driving, and to find the location coordinates of surrounding objects through object recognition. In pilot research about the tram’s automated driving, YOLOv3 was used for object detection to find object coordinates. YOLOv3 is an artificial intelligence model that finds coordinates, sizes, and classes of objects in an image. YOLOv3 is the third upgrade of YOLO, which is one of the most famous object detection technologies based on CNN. YOLO’s object detection performance is characterized by ordinary accuracy and fast speed. For this paper, we conducted a study to find out whether the object detection performance required for autonomous trams can be sufficiently implemented with the already developed object detection model. For this experiment, we used the YOLOv4 which is the fourth upgrade of YOLO.

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Satav, Aalhad, and Nishigandha Patel. "User Interface and AI Navigation System for Autonomous Vehicle." International Journal of Recent Technology and Engineering (IJRTE) 11, no. 2 (July 30, 2022): 122–27. http://dx.doi.org/10.35940/ijrte.b7151.0711222.

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The issue of vehicle accidents due to human error and behavior (rash driving, drink and drive, etc.) is on rising resulting into fatality and economical loss. In order to overcome these issues, the autonomous vehicle is being explored as a probable solution. Driver will be replaced by AI based autonomous system; The main objective is to convert the manual operated EV into autonomous vehicle. The project work is divided into three main parts i.e., Control System for Vehicle Control, AI (Artificial Intelligence) and UI (User Interface). The main objective of User Interface is to give information regarding vehicles health i.e. battery remaining, charging time, distance to be covered, etc. AI will be use as decision making system or we can say brain of the autonomous vehicle. System Control or Vehicle Control System is to control the vehicle’s steering, acceleration and braking system with the help of PID controller while the vehicle is being operated in autonomous mode. The main purpose is to make an autonomous EV for the passengers to go to their selected destination with a single click by selecting destination on display (UI). So the vehicle control is responsible for the vehicle’s steering i.e., at what desired angle the vehicle need to turn, during acceleration the factors that are considered are; at what speed the vehicle needs to move in an straight path or during a turn and the braking system is operated with the help of LIDAR where if it detects an object at what distance it needs to apply the brakes and when to release the brakes. All the factors and conditions required in developing the autonomous vehicle will be considered, as use cases to improve the accuracy of autonomous vehicle, resulting into achieving desired objective of safe travel.

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Raksincharoensak, Pongsathorn, Yuta Akamatsu, Katsumi Moro, and Masao Nagai. "Driver Speed Control Modeling for Predictive Braking Assistance System Based on Risk Potential in Intersections." Journal of Robotics and Mechatronics 26, no. 5 (October 20, 2014): 628–37. http://dx.doi.org/10.20965/jrm.2014.p0628.

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<div class=""abs_img""><img src=""[disp_template_path]/JRM/abst-image/00260005/12.jpg"" width=""300"" />Predictive braking assistance system</div> This paper describes the assessment of a predictive braking assistance system, which is done using a driving simulator that reconstructs near-miss incident scenarios relevant to pedestrians. An autonomous braking assistance algorithm for collision avoidance is designed based on pedestrian movement prediction and an artificial risk potential field. A virtual spring connecting the vehicle and the pedestrian is used to determine the repulsive potential field and the intensity of the deceleration. The feasibility of the proposed braking assistance algorithm is examined through experiments using the driving simulator and a comparison to actual driving data. Near-miss incident data relevant to pedestrians in intersections are analyzed to get the basic parameters of a crash scenario model relevant to pedestrians. Driving simulator experiments are used to verify the effectiveness of the proposed system. </span>

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Žuraulis, Vidas, Vytenis Surblys, and Eldar Šabanovič. "TECHNOLOGICAL MEASURES OF FOREFRONT ROAD IDENTIFICATION FOR VEHICLE COMFORT AND SAFETY IMPROVEMENT." Transport 34, no. 3 (May 27, 2019): 363–72. http://dx.doi.org/10.3846/transport.2019.10372.

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This paper presents the technological measures currently being developed at institutes and vehicle research centres dealing with forefront road identification. In this case, road identification corresponds with the surface irregularities and road surface type, which are evaluated by laser scanning and image analysis. Real-time adaptation, adaptation in advance and system external informing are stated as sequential generations of vehicle suspension and active braking systems where road identification is significantly important. Active and semi-active suspensions with their adaptation technologies for comfort and road holding characteristics are analysed. Also, an active braking system such as Anti-lock Braking System (ABS) and Autonomous Emergency Braking (AEB) have been considered as very sensitive to the road friction state. Artificial intelligence methods of deep learning have been presented as a promising image analysis method for classification of 12 different road surface types. Concluding the achieved benefit of road identification for traffic safety improvement is presented with reference to analysed research reports and assumptions made after the initial evaluation.

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Yuan, Tian, Rui Liu, Xuan Zhao, Qiang Yu, Xichan Zhu, and Shu Wang. "Analysis of Normal Stopping Behavior of Drivers at Urban Intersections in China." Journal of Advanced Transportation 2022 (July 14, 2022): 1–17. http://dx.doi.org/10.1155/2022/7588589.

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Driving behavior analysis plays an important role in improving the human-like driving capability of the Advanced Driver Assistance System (ADAS) and autonomous driving technologies. In this study, 906 data of drivers stopping normally at urban intersections were extracted from natural driving data to study reaction characteristics and braking characteristics of drivers in real road traffic. The effects of traffic state and traffic density on approach speed and reaction distance were studied using one-way ANOVA, and the relationships between maximum deceleration, average deceleration, braking duration, and influencing factors were analyzed using hierarchical multiple regression. The main results indicate the following: (1) compare with free driving, the approach speed in the following state was lower, and following traffic also caused drivers with higher speeds to further increase reaction distance in high-density traffic. (2) Traffic density only affected the approach speed in the free-driving condition. High-density traffic caused drivers to reduce speed. (3) There was a clear correlation between approach speed and reaction distance: the greater the approach speed, the longer the reaction distance. (4) The braking characteristics were mainly affected by the self-vehicle motion state. Drivers braked to a stop with greater average deceleration and maximum deceleration in a shorter time when the approach speed was higher or the reaction distance was shorter. (5) Both traffic state and traffic density had an influence on the braking characteristics. Drivers reduced average deceleration and increased braking duration in the following state and high-density traffic. (6) When following a preceding vehicle to stop, the braking characteristics of drivers were no longer influenced by the traffic density but were related to the relative motion state with the preceding vehicle. In addition to the driving behavior analysis, the identification method of traffic participants and ranging method used in this study will also advance the development of autonomous driving technologies and driver assistance systems.

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Falcone, Paolo, H. Eric Tseng, Jahan Asgari, Francesco Borrelli, and Davor Hrovat. "INTEGRATED BRAKING AND STEERING MODEL PREDICTIVE CONTROL APPROACH IN AUTONOMOUS VEHICLES." IFAC Proceedings Volumes 40, no. 10 (2007): 273–78. http://dx.doi.org/10.3182/20070820-3-us-2918.00038.

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Zanelli, Federico, Marco Mauri, Francesco Castelli-Dezza, Edoardo Sabbioni, Davide Tarsitano, and Nicola Debattisti. "Energy Autonomous Wireless Sensor Nodes for Freight Train Braking Systems Monitoring." Sensors 22, no. 5 (February 27, 2022): 1876. http://dx.doi.org/10.3390/s22051876.

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Nowadays, railway freight transportation is becoming more and more crucial since it represents the best alternative to road transport in terms of sustainability, pollution, and impact on the environment and on public health. Upgrading the potentiality of this kind of transportation, it would be possible to avoid delays in goods deliveries due to road accidents, traffic jams, and other situation occurring on roads. A key factor in this framework is therefore represented by monitoring and maintenance of the train components. Implementing a real time monitoring of the main components and a predictive maintenance approach, it would be possible to avoid unexpected breakdowns and consequently unavailability of wagons for unscheduled repair activities. As highlighted in recent statistical analysis, one of the elements more critical in case of failure is represented by the brake system. In this view, a real time monitoring of pressure values in some specific points of the system would provide significant information on its health status. In addition, since the braking actions are related to the load present on the convoy, thanks to this kind of monitoring, it would be possible to appreciate the different behavior of the system in case of loaded and unloaded trains. This paper presented an innovative wireless monitoring system to perform brake system diagnostics. A low-power system architecture, in terms of energy harvesting and wireless communication, was developed due to the difficulty in applying a wired monitoring system to a freight convoy. The developed system allows acquiring brake pressure data in critical points in order to verify the correct behavior of the brake system. Experimental results collected during a five-month field test were provided to validate the approach.

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Savino, Giovanni, Marco Pierini, Matteo Rizzi, and Richard Frampton. "Evaluation of an Autonomous Braking System in Real-World PTW Crashes." Traffic Injury Prevention 14, no. 5 (July 4, 2013): 532–43. http://dx.doi.org/10.1080/15389588.2012.725878.

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Journal articles on the topic 'Autonomous braking'

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