scholarly journals Holistic Vehicle Instrumentation for Assessing Driver Driving Styles

Sensors ◽  
2021 ◽  
Vol 21 (4) ◽  
pp. 1427
Author(s):  
María Garrosa ◽  
Ester Olmeda ◽  
Sergio Fuentes del Toro ◽  
Vicente Díaz
Keyword(s):  
Autonomous Vehicles ◽  
Autonomous Vehicle ◽  
Experimental Tests ◽  
Dynamic Responses ◽  
Emergency Braking ◽  
Braking System ◽  
Hydraulic Brake ◽  
Driving Scenario ◽  
Real Time Information ◽  
Time Information

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.

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.

MoVE: A Mobility Virtual Environment for Autonomous Vehicle Testing

2019 ◽  
Author(s):  
Marc Compere ◽  
Garrett Holden ◽  
Otto Legon ◽  
Roberto Martinez Cruz
Keyword(s):  
Open Source ◽  
Virtual Environment ◽  
Autonomous Vehicles ◽  
Autonomous Vehicle ◽  
Time History ◽  
Experimental Tests ◽  
Coordinate Frame ◽  
Medical Evacuation ◽  
Post Process ◽  
Common Framework

Abstract Autonomous vehicle researchers need a common framework in which to test autonomous vehicles and algorithms along a realism spectrum from simulation-only to real vehicles and real people. The community needs an open-source, publicly available framework, with source code, in which to develop, simulate, execute, and post-process multi-vehicle tests. This paper presents a Mobility Virtual Environment (MoVE) for testing autonomous system algorithms, vehicles, and their interactions with real and simulated vehicles and pedestrians. The result is a network-centric framework designed to represent multiple real and multiple virtual vehicles interacting and possibly communicating with each other in a common coordinate frame with a common timestamp. This paper presents a literature review of comparable autonomous vehicle softwares, presents MoVE concepts and architecture, and presents three experimental tests with multiple virtual and real vehicles, with real pedestrians. The first scenario is a traffic wave simulation using a real lead vehicle and 3 real follower vehicles. The second scenario is a medical evacuation scenario with 2 real pedestrians and 1 real vehicles. Real pedestrians are represented using live-GPS-followers streaming GPS position from mobile phones over the cellular network. Time-history and spatial plots of real and virtual vehicles are presented with vehicle-to-vehicle distance calculations indicating where and when potential collisions were detected and avoided. The third scenario highlights the avoid() behavior successfully avoiding other virtual vehicles and 1 real pedestrian in a small outdoor area. The MoVE set of concepts and interfaces are implemented as open-source software available for use and customization within the autonomous vehicle community. MoVE is freely available under the GPLv3 open-source license at gitlab.com/comperem/move.

scholarly journals An Integrated Model for User State Detection of Subjective Discomfort in Autonomous Vehicles

Vehicles ◽  
2021 ◽  
Vol 3 (4) ◽  
pp. 764-777
Author(s):  
Dario Niermann ◽  
Alexander Trende ◽  
Klas Ihme ◽  
Uwe Drewitz ◽  
Cornelia Hollander ◽  
...  
Keyword(s):  
Autonomous Vehicles ◽  
Linear Models ◽  
Driving Simulator ◽  
Autonomous Vehicle ◽  
The Road ◽  
Novel Approach ◽  
Driving Scenario ◽  
On The Road ◽  
Using Data ◽  
Subjective Discomfort

The quickly rising development of autonomous vehicle technology and increase of (semi-) autonomous vehicles on the road leads to an increased demand for more sophisticated human–machine-cooperation approaches to improve trust and acceptance of these new systems. In this work, we investigate the feeling of discomfort of human passengers while driving autonomously and the automatic detection of this discomfort with several model approaches, using the combination of different data sources. Based on a driving simulator study, we analyzed the discomfort reports of 50 participants for autonomous inner city driving. We found that perceived discomfort depends on the driving scenario (with discomfort generally peaking in complex situations) and on the passenger (resulting in interindividual differences in reported discomfort extend and duration). Further, we describe three different model approaches on how to predict the passenger discomfort using data from the vehicle’s sensors as well as physiological and behavioral data from the passenger. The model’s precision varies greatly across the approaches, the best approach having a precision of up to 80%. All of our presented model approaches use combinations of linear models and are thus fast, transparent, and safe. Lastly, we analyzed these models using the SHAP method, which enables explaining the models’ discomfort predictions. These explanations are used to infer the importance of our collected features and to create a scenario-based discomfort analysis. Our work demonstrates a novel approach on passenger state modelling with simple, safe, and transparent models and with explainable model predictions, which can be used to adapt the vehicles’ actions to the needs of the passenger.

scholarly journals Parameterization of the ABS electronic control unit for increasing the autonomous trucks’ active safety

2021 ◽  
Vol 341 ◽  
pp. 00026
Author(s):  
Shakhrom Begizhonov ◽  
Polina Buyvol ◽  
Irina Makarova ◽  
Eduard Tsybunov
Keyword(s):  
Autonomous Vehicles ◽  
Electronic Control Unit ◽  
Control Unit ◽  
Steering Wheel ◽  
Active Safety ◽  
Electronic Control ◽  
Software Module ◽  
Emergency Braking ◽  
Braking System ◽  
Vehicle Active Safety

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.

scholarly journals Autonomous Driving in Roundabout Maneuvers Using Reinforcement Learning with Q-Learning

Electronics ◽  
2019 ◽  
Vol 8 (12) ◽  
pp. 1536 ◽  
Author(s):  
Laura García Cuenca ◽  
Enrique Puertas ◽  
Javier Fernandez Andrés ◽  
Nourdine Aliane
Keyword(s):  
Reinforcement Learning ◽  
Autonomous Vehicles ◽  
Learning Algorithm ◽  
Autonomous Vehicle ◽  
Autonomous Driving ◽  
Simulation Environment ◽  
Q Learning ◽  
Driving Scenario

Navigating roundabouts is a complex driving scenario for both manual and autonomous vehicles. This paper proposes an approach based on the use of the Q-learning algorithm to train an autonomous vehicle agent to learn how to appropriately navigate roundabouts. The proposed learning algorithm is implemented using the CARLA simulation environment. Several simulations are performed to train the algorithm in two scenarios: navigating a roundabout with and without surrounding traffic. The results illustrate that the Q-learning-algorithm-based vehicle agent is able to learn smooth and efficient driving to perform maneuvers within roundabouts.

Co-simulation model coupling of flexible rope hoisting system and hydraulic braking system for a mine hoist

2021 ◽  
pp. 095440892110535
Author(s):  
Song Ziyu ◽  
Wang Xiaona ◽  
Li Yajing ◽  
Guo Yu ◽  
Hao Huimin ◽  
...  
Keyword(s):  
Simulation Model ◽  
Coupling Effect ◽  
Steel Wire ◽  
Joint Modeling ◽  
System Model ◽  
Emergency Braking ◽  
Braking System ◽  
Hydraulic Brake ◽  
Hoisting System ◽  
Mine Hoist

The hoist is an important equipment in the mine pit. Since the containers are lifted or lowered with flexible steel wire ropes, there are shocks and vibrations during operation, especially in the emergency braking stage, the shocks and vibration will be more severe. Mine hoist is a complex system; therefore, it is difficult to obtain all its dynamics information only by investigating the flexible hoisting subsystem or hydraulic brake subsystem. Therefore, it is very necessary to establish an accurate model to predict these characteristics of the hoist, this will provide useful tools for hoist design and maintenance. Therefore, a joint modeling methodology is proposed and implemented in this paper. A hoisting system model considering the non-linear factors such as contact characteristics and flexibility was established in RecurDyn. The hydraulic braking system model and control system model were established in AMESim, and the co-simulation model was constructed by the interface module. In this co-simulation model, not only the flexible hoisting subsystem and hydraulic brake subsystem are included, but also the coupling effect of subsystems is considered. Finally, taking the lifting condition as an example, execute emergency braking research on the hoisting system under experiment, mathematical model, and co-simulation model, respectively. Comparing the co-simulation model with the mathematical dynamics model, and the experimental test results, research indicates that the joint simulation model of coupled hoisting system and hydraulic braking system can effectively reflect the dynamic characteristics of the actual hoisting system. It provides an effective tool for hoist design, optimization, performance analysis, and operating condition simulation. In addition, the methods and techniques used in the co-simulation modeling procedure are portable. Therefore, the paper is of significance for the mine hoist.

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