scholarly journals Longitudinal Control for Connected and Automated Vehicles in Contested Environments

Electronics ◽  
2021 ◽  
Vol 10 (16) ◽  
pp. 1994
Author(s):  
Shirin Noei ◽  
Mohammadreza Parvizimosaed ◽  
Mohammadreza Noei
Keyword(s):  
Vehicle Dynamics ◽  
Dynamics Simulation ◽  
Simulation Tool ◽  
Reasonable Accuracy ◽  
Automated Vehicles ◽  
Automated Driving ◽  
Time Step ◽  
Longitudinal Control ◽  
Simulation Tools ◽  
Simulation Time

The Society of Automotive Engineers (SAE) defines six levels of driving automation, ranging from Level 0 to Level 5. Automated driving systems perform entire dynamic driving tasks for Levels 3–5 automated vehicles. Delegating dynamic driving tasks from driver to automated driving systems can eliminate crashes attributed to driver errors. Sharing status, sharing intent, seeking agreement, or sharing prescriptive information between road users and vehicles dedicated to automated driving systems can further enhance dynamic driving task performance, safety, and traffic operations. Extensive simulation is required to reduce operating costs and achieve an acceptable risk level before testing cooperative automated driving systems in laboratory environments, test tracks, or public roads. Cooperative automated driving systems can be simulated using a vehicle dynamics simulation tool (e.g., CarMaker and CarSim) or a traffic microsimulation tool (e.g., Vissim and Aimsun). Vehicle dynamics simulation tools are mainly used for verification and validation purposes on a small scale, while traffic microsimulation tools are mainly used for verification purposes on a large scale. Vehicle dynamics simulation tools can simulate longitudinal, lateral, and vertical dynamics for only a few vehicles in each scenario (e.g., up to ten vehicles in CarMaker and up to twenty vehicles in CarSim). Conventional traffic microsimulation tools can simulate vehicle-following, lane-changing, and gap-acceptance behaviors for many vehicles in each scenario without simulating vehicle powertrain. Vehicle dynamics simulation tools are more compute-intensive but more accurate than traffic microsimulation tools. Due to software architecture or computing power limitations, simplifying assumptions underlying convectional traffic microsimulation tools may have been a necessary compromise long ago. There is, therefore, a need for a simulation tool to optimize computational complexity and accuracy to simulate many vehicles in each scenario with reasonable accuracy. This research proposes a traffic microsimulation tool that employs a simplified vehicle powertrain model and a model-based fault detection method to simulate many vehicles with reasonable accuracy at each simulation time step under noise and unknown inputs. Our traffic microsimulation tool considers driver characteristics, vehicle model, grade, pavement conditions, operating mode, vehicle-to-vehicle communication vulnerabilities, and traffic conditions to estimate longitudinal control variables with reasonable accuracy at each simulation time step for many conventional vehicles, vehicles dedicated to automated driving systems, and vehicles equipped with cooperative automated driving systems. Proposed vehicle-following model and longitudinal control functions are verified for fourteen vehicle models, operating in manual, automated, and cooperative automated modes over two driving schedules under three malicious fault magnitudes on transmitted accelerations.

Linearization and Model Reduction of Contact Dynamics Simulation

2011 ◽  
Author(s):  
Jianxun Liang ◽  
Ou Ma ◽  
Caishan Liu
Keyword(s):  
Model Reduction ◽  
Multibody Systems ◽  
Reduction Method ◽  
Contact Dynamics ◽  
Dynamics Simulation ◽  
Dynamics Model ◽  
Time Step ◽  
Reduction Techniques ◽  
Proposed Model ◽  
Simulation Time

Finite element methods are widely used for simulations of contact dynamics of flexible multibody systems. Such a simulation is computationally very inefficient because the system’s dimension is usually very large and the simulation time step has to be very small in order to ensure numerical stability. A potential solution to the problem is to apply a model reduction method in the simulation. Although many model reduction techniques have been developed, most of them cannot be readily applied due to the high nonlinearity of the involved contact dynamics model. This paper presents a solution to the problem. The approach is based on a modified Lyapunov balanced truncation method. A numerical example is presented to demonstrate that, by applying the proposed model reduction method, the simulation process can be significantly speeded up while the resulting error caused by the model reduction is still within an acceptable level.

scholarly journals Extending the vehicular network simulator Artery in order to generate synthetic data for collective perception

2019 ◽  
Vol 17 ◽  
pp. 189-196 ◽  
Author(s):  
Christoph Allig ◽  
Gerd Wanielik
Keyword(s):  
Vehicle Dynamics ◽  
Synthetic Data ◽  
Current Approach ◽  
Network Simulator ◽  
Market Penetration ◽  
Automated Driving ◽  
Simulation Tools ◽  
Ego States ◽  
Sensor Models ◽  
Data Collections

Abstract. A fundamental for an automated driving car is the awareness of all its surrounding road participants. Current approach to gather this awareness is to sense the environment by on-board sensors. In the future, Vehicle-to-X (V2X) might be able to improve the awareness due to V2X's communication range superiority compared to the on-board sensors' range. Due to a limited amount of communication partners sharing their own ego states, current research focuses particularly on cooperative perception. This means sharing objects perceived by local on-board sensors of different partners via V2X. Data collections using vehicles, driving on real roads, is challenging, since there is no market introduction of cooperative perception yet. Using test cars, equipped with the required sensors are rather expensive and do not necessarily provide results representing the true potential of cooperative perception. Particularly, its potential is highly dependent on the market penetration rate and the amount of vehicles within certain vicinity. Therefore, we consider to create synthetic data for cooperative perception by a simulation tool. After reviewing suitable simulation tools, we present an extension of Artery and its counterpart SUMO by modelling realistic vehicle dynamics and probabilistic sensor models. The generated data can be used as input for cooperative perception.

Semialgebraic Regularization of Kinematic Loop Constraints in Multibody System Models

2011 ◽  
Vol 6 (4) ◽  
Author(s):  
Andreas Müller
Keyword(s):  
Multibody System ◽  
Dynamics Simulation ◽  
Time Step ◽  
Kinematic Loops ◽  
Low Dimensional ◽  
Kinematic Loop ◽  
Value Decomposition ◽  
Loop Constraints ◽  
Simulation Time

Redundant constraints in multibody system (MBS) models, reflected by a singular constraint Jacobian, impair the efficient dynamics simulation. In particular, kinematic loop constraints are often found to be permanently redundant. This problem is commonly attacked numerically by decomposing the constraint Jacobian either at every simulation time step or beforehand in an admissible assembly (assuming that the redundancy is permanent). This paper presents a method for the elimination of permanently redundant loop closure constraints, which, instead of numerically decomposing the constraints, relies on the geometric characterization of kinematic loops comprising lower kinematic pairs. In particular, the invariant vector space of velocities of a kinematic loop is taken into account, which can be determined as the sum of Lie (screw) algebras of two subchains of a kinematic loop. The actual reduction is achieved by restricting the constraints to this space. The presented method does not interfere with the actual generation of constraints but can be considered as a preprocessing step of MBS models. It is numerically robust and only uses a geometrically exact model. The method is able to completely eliminate redundant loop constraints for “nonparadoxical” single-loop mechanisms and applies conservatively to multiloop MBS. The presented method only requires information (vectors, matrices) that is readily available in any MBS simulation package. The only numerical operations involved are cross products and a singular value decomposition of a low dimensional matrix.

Model-matching control applied to longitudinal and lateral automated driving

2005 ◽  
Vol 219 (5) ◽  
pp. 583-598 ◽  
Author(s):  
Seong-Jin Kwon ◽  
Takehiko Fujioka ◽  
Ki-Yong Cho ◽  
Myung-Won Suh
Keyword(s):  
Vehicle Dynamics ◽  
Dynamics Simulation ◽  
System Stability ◽  
Model Matching ◽  
Automated Driving ◽  
Driving System ◽  
The Road ◽  
Vehicle System ◽  
Vehicle Mass ◽  
Road Gradient

Although there has been substantial research on longitudinal and lateral controllers for an automated driving system, stability issues with respect to the effect of uncertainties due to parameter variations (e.g. in the vehicle mass and the cornering stiffness) and disturbances or perturbations to the vehicle system (e.g. in the road gradient and the wind) still need to be addressed. Thus, an automated driving system needs to be made robust to those influences. For this purpose, the model-matching control applied to longitudinal and lateral automated driving is investigated by vehicle dynamics simulation. The design of the model-matching controller is obtained by using the characteristics of a two-degree-of-freedom controller. It can make various characteristics of automated driving vehicles equivalent to a specific transfer function, which is suggested as the reference model. The vehicle dynamics models including the model-matching controller are constructed for computer simulation. Then, simple examples of open-loop simulation and closed-loop simulation are solved to check the robustness of the model-matching controller. As a practical example, an automated driving system is adopted. It is proved that the model-matching control is effective and adequate for uncertainties due to parameter variation and disturbances or perturbations to the vehicle system, which are shown in the responses of the changes in the vehicle mass, the road gradient and the cornering stiffness.

Ethics of Artificial Intelligence in Transport

2020 ◽  
pp. 667-683
Author(s):  
Bryant Walker Smith
Keyword(s):  
Artificial Intelligence ◽  
Ethical Issues ◽  
Ethical Question ◽  
Power Dynamics ◽  
Automated Vehicles ◽  
Automated Driving ◽  
The U.S ◽  
Policy Solutions

This chapter highlights key ethical issues in the use of artificial intelligence in transport by using automated driving as an example. These issues include the tension between technological solutions and policy solutions; the consequences of safety expectations; the complex choice between human authority and computer authority; and power dynamics among individuals, governments, and companies. In 2017 and 2018, the U.S. Congress considered automated driving legislation that was generally supported by many of the larger automated-driving developers. However, this automated-driving legislation failed to pass because of a lack of trust in technologies and institutions. Trustworthiness is much more of an ethical question. Automated vehicles will not be driven by individuals or even by computers; they will be driven by companies acting through their human and machine agents. An essential issue for this field—and for artificial intelligence generally—is how the companies that develop and deploy these technologies should earn people’s trust.

scholarly journals Automated vehicles and the morality of post-collision behavior

2021 ◽  
Author(s):  
Sebastian Krügel ◽  
Matthias Uhl ◽  
Bryn Balcombe
Keyword(s):  
European Commission ◽  
Research Program ◽  
Collision Detection ◽  
Expert Group ◽  
Automated Vehicles ◽  
Automated Driving ◽  
Data Provision

AbstractWe address the considerations of the European Commission Expert Group on the ethics of connected and automated vehicles regarding data provision in the event of collisions. While human drivers’ appropriate post-collision behavior is clearly defined, regulations for automated driving do not provide for collision detection. We agree it is important to systematically incorporate citizens’ intuitions into the discourse on the ethics of automated vehicles. Therefore, we investigate whether people expect automated vehicles to behave like humans after an accident, even if this behavior does not directly affect the consequences of the accident. We find that appropriate post-collision behavior substantially influences people’s evaluation of the underlying crash scenario. Moreover, people clearly think that automated vehicles can and should record the accident, stop at the site, and call the police. They are even willing to pay for technological features that enable post-collision behavior. Our study might begin a research program on post-collision behavior, enriching the empirically informed study of automated driving ethics that so far exclusively focuses on pre-collision behavior.

scholarly journals Lane Departure Warning Estimation Using Yaw Acceleration

2020 ◽  
Vol 11 (1) ◽  
pp. 102-111
Author(s):  
Em Poh Ping ◽  
J. Hossen ◽  
Wong Eng Kiong
Keyword(s):  
Vehicle Dynamics ◽  
Dynamic Responses ◽  
Dynamics Simulation ◽  
Steering Wheel ◽  
Mathematical Representation ◽  
Vehicle Speed ◽  
Lane Departure Warning ◽  
Model Based ◽  
Lane Departure ◽  
Proposed Model

AbstractLane departure collisions have contributed to the traffic accidents that cause millions of injuries and tens of thousands of casualties per year worldwide. Due to vision-based lane departure warning limitation from environmental conditions that affecting system performance, a model-based vehicle dynamics framework is proposed for estimating the lane departure event by using vehicle dynamics responses. The model-based vehicle dynamics framework mainly consists of a mathematical representation of 9-degree of freedom system, which permitted to pitch, roll, and yaw as well as to move in lateral and longitudinal directions with each tire allowed to rotate on its axle axis. The proposed model-based vehicle dynamics framework is created with a ride model, Calspan tire model, handling model, slip angle, and longitudinal slip subsystems. The vehicle speed and steering wheel angle datasets are used as the input in vehicle dynamics simulation for predicting lane departure event. Among the simulated vehicle dynamic responses, the yaw acceleration response is observed to provide earlier insight in predicting the future lane departure event compared to other vehicle dynamics responses. The proposed model-based vehicle dynamics framework had shown the effectiveness in estimating lane departure using steering wheel angle and vehicle speed inputs.

scholarly journals A Review on Combination of Ab Initio Molecular Dynamics and NMR Parameters Calculations

2021 ◽  
Vol 22 (9) ◽  
pp. 4378
Author(s):  
Anna Helena Mazurek ◽  
Łukasz Szeleszczuk ◽  
Dariusz Maciej Pisklak
Keyword(s):  
Molecular Dynamics ◽  
Ab Initio ◽  
Small Amplitude ◽  
Ab Initio Molecular Dynamics ◽  
Quantum Mechanical ◽  
Time Step ◽  
Noticeable Effect ◽  
Nmr Parameters ◽  
Mechanical Methods ◽  
Simulation Time

This review focuses on a combination of ab initio molecular dynamics (aiMD) and NMR parameters calculations using quantum mechanical methods. The advantages of such an approach in comparison to the commonly applied computations for the structures optimized at 0 K are presented. This article was designed as a convenient overview of the applied parameters such as the aiMD type, DFT functional, time step, or total simulation time, as well as examples of previously studied systems. From the analysis of the published works describing the applications of such combinations, it was concluded that including fast, small-amplitude motions through aiMD has a noticeable effect on the accuracy of NMR parameters calculations.

scholarly journals Hydrogen Inter-Cage Hopping and Cage Occupancies inside Hydrogen Hydrate: Molecular-Dynamics Analysis

2020 ◽  
Vol 11 (1) ◽  
pp. 282
Author(s):  
Yogeshwaran Krishnan ◽  
Mohammad Reza Ghaani ◽  
Arnaud Desmedt ◽  
Niall J. English
Keyword(s):  
Molecular Dynamics ◽  
Energy Barrier ◽  
Guest Molecule ◽  
Arrhenius Equation ◽  
Dynamics Simulation ◽  
Type Ii ◽  
Large Cage ◽  
Guest Molecules ◽  
Simulation Time ◽  
Average Occupancy

The inter-cage hopping in a type II clathrate hydrate with different numbers of H2 and D2 molecules, from 1 to 4 molecules per large cage, was studied using a classical molecular dynamics simulation at temperatures of 80 to 240 K. We present the results for the diffusion of these guest molecules (H2 or D2) at all of the different occupations and temperatures, and we also calculated the activation energy as the energy barrier for the diffusion using the Arrhenius equation. The average occupancy number over the simulation time showed that the structures with double and triple large-cage H2 occupancy appeared to be the most stable, while the small cages remained with only one guest molecule. A Markov model was also calculated based on the number of transitions between the different cage types.

First encounter effects in testing of highly automated vehicles during two experimental occasions – The need for recurrent testing

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Jonas Andersson ◽  
Azra Habibovic ◽  
Daban Rizgary
Keyword(s):  
Driver Behavior ◽  
Added Value ◽  
Future Research ◽  
Gaze Behavior ◽  
Repeated Testing ◽  
Automated Vehicles ◽  
Automated Driving ◽  
Perceived Safety ◽  
Repeated Interaction ◽  
Over Time

Abstract To explore driver behavior in highly automated vehicles (HAVs), independent researchers are mainly conducting short experiments. This limits the ability to explore drivers’ behavioral changes over time, which is crucial when research has the intention to reveal human behavior beyond the first-time use. The current paper shows the methodological importance of repeated testing in experience and behavior related studies of HAVs. The study combined quantitative and qualitative data to capture effects of repeated interaction between drivers and HAVs. Each driver ( n = 8 n=8 ) participated in the experiment on two different occasions (∼90 minutes) with one-week interval. On both occasions, the drivers traveled approximately 40 km on a rural road at AstaZero proving grounds in Sweden and encountered various traffic situations. The participants could use automated driving (SAE level 4) or choose to drive manually. Examples of data collected include gaze behavior, perceived safety, as well as interviews and questionnaires capturing general impressions, trust and acceptance. The analysis shows that habituation effects were attenuated over time. The drivers went from being exhilarated on the first occasion, to a more neutral behavior on the second occasion. Furthermore, there were smaller variations in drivers’ self-assessed perceived safety on the second occasion, and drivers were faster to engage in non-driving related activities and become relaxed (e. g., they spent more time glancing off road and could focus more on non-driving related activities such as reading). These findings suggest that exposing drivers to HAVs on two (or more) successive occasions may provide more informative and realistic insights into driver behavior and experience as compared to only one occasion. Repeating an experiment on several occasions is of course a balance between the cost and added value, and future research should investigate in more detail which studies need to be repeated on several occasions and to what extent.

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