Driver Speed Control Modeling for Predictive Braking Assistance System Based on Risk Potential in Intersections

<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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Human-Like Obstacle Avoidance Trajectory Planning and Tracking Model for Autonomous Vehicles That Considers the Driver’s Operation Characteristics

Sensors ◽

10.3390/s20174821 ◽

2020 ◽

Vol 20 (17) ◽

pp. 4821

Author(s):

Qinyu Sun ◽

Yingshi Guo ◽

Rui Fu ◽

Chang Wang ◽

Wei Yuan

Keyword(s):

Obstacle Avoidance ◽

Trajectory Planning ◽

Trajectory Tracking ◽

Potential Field ◽

Autonomous Vehicles ◽

Driving Simulator ◽

Planning Model ◽

Repulsive Potential ◽

Tracking Model ◽

Operation Characteristics

Developing a human-like autonomous driving system has gained increasing amounts of attention from both technology companies and academic institutions, as it can improve the interpretability and acceptance of the autonomous system. Planning a safe and human-like obstacle avoidance trajectory is one of the critical issues for the development of autonomous vehicles (AVs). However, when designing automatic obstacle avoidance systems, few studies have focused on the obstacle avoidance characteristics of human drivers. This paper aims to develop an obstacle avoidance trajectory planning and trajectory tracking model for AVs that is consistent with the characteristics of human drivers’ obstacle avoidance trajectory. Therefore, a modified artificial potential field (APF) model was established by adding a road boundary repulsive potential field and ameliorating the obstacle repulsive potential field based on the traditional APF model. The model predictive control (MPC) algorithm was combined with the APF model to make the planning model satisfy the kinematic constraints of the vehicle. In addition, a human driver’s obstacle avoidance experiment was implemented based on a six-degree-of-freedom driving simulator equipped with multiple sensors to obtain the drivers’ operation characteristics and provide a basis for parameter confirmation of the planning model. Then, a linear time-varying MPC algorithm was employed to construct the trajectory tracking model. Finally, a co-simulation model based on CarSim/Simulink was established for off-line simulation testing, and the results indicated that the proposed trajectory planning controller and the trajectory tracking controller were more human-like under the premise of ensuring the safety and comfort of the obstacle avoidance operation, providing a foundation for the development of AVs.

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Local Dynamic Path Planning for an Ambulance Based on Driving Risk and Attraction Field

Sustainability ◽

10.3390/su13063194 ◽

2021 ◽

Vol 13 (6) ◽

pp. 3194

Author(s):

Fang Zong ◽

Meng Zeng ◽

Yang Cao ◽

Yixuan Liu

Keyword(s):

Path Planning ◽

Potential Field ◽

Velocity Potential ◽

Attractive Potential ◽

Local Dynamic ◽

Repulsive Potential ◽

Ambulance Personnel ◽

Lane Changing ◽

Dynamic Path Planning ◽

Dynamic Path

Path planning is one of the most important aspects for ambulance driving. A local dynamic path planning method based on the potential field theory is presented in this paper. The potential field model includes two components—repulsive potential and attractive potential. Repulsive potential includes road potential, lane potential and obstacle potential. Considering the driving distinction between an ambulance and a regular vehicle, especially in congested traffic, an adaptive potential function for a lane line is constructed in association with traffic conditions. The attractive potential is constructed with target potential, lane-velocity potential and tailgating potential. The design of lane-velocity potential is to characterize the influence of velocity on other lanes so as to prevent unnecessary lane-changing behavior for the sake of time-efficiency. The results obtained from simulation demonstrate that the proposed method yields a good performance for ambulance driving in an urban area, which can provide support for designing an ambulance support system for the ambulance personnel and dispatcher.

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Driver Monitoring for a Driver-Centered Design and Assessment of a Merging Assistance System Based on V2V Communications

Sensors ◽

10.3390/s20195582 ◽

2020 ◽

Vol 20 (19) ◽

pp. 5582

Author(s):

Sofia Sánchez–Mateo ◽

Elisa Pérez–Moreno ◽

Felipe Jiménez

Keyword(s):

Driving Simulator ◽

Tracking System ◽

Road Transport ◽

Assistance System ◽

Internal Variables ◽

Mental Load ◽

V2v Communications ◽

Interface Definition ◽

System Prototype ◽

Alternative Solutions

Merging is one of the most critical scenarios that can be found in road transport. In this maneuver, the driver is subjected to a high mental load due to the large amount of information he handles, while making decisions becomes a crucial issue for their safety and those in adjacent vehicles. In previous works, it was studied how the merging maneuver affected the cognitive load required for driving by means of an eye tracking system, justifying the proposal of a driver assistance system for the merging maneuver on highways. This paper presents a merging assistance system based on communications between vehicles, which allows vehicles to share internal variables of position and speed and is implemented on a mobile device located inside the vehicle. The system algorithm decides where and when the vehicle can start the merging maneuver in safe conditions and provides the appropriate information to the driver. Parameters and driving simulator tests are used for the interface definition to develop the less intrusive and demanding one. Afterward, the system prototype was installed in a real passenger car and tests in real scenarios were conducted with several drivers to assess usability and mental load. Comparisons among alternative solutions are shown and effectiveness is assessed.

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Study on Autonomous Intelligent Drive System Based on Potential Field with Hazard Anticipation

Journal of Robotics and Mechatronics ◽

10.20965/jrm.2015.p0005 ◽

2015 ◽

Vol 27 (1) ◽

pp. 5-11 ◽

Cited By ~ 6

Author(s):

Ryosuke Matsumi ◽

◽

Pongsathorn Raksincharoensak ◽

Masao Nagai ◽

◽

...

Keyword(s):

Field Theory ◽

Computer Simulation ◽

Collision Avoidance ◽

Potential Field ◽

Drive System ◽

Urban Street ◽

Emergency Braking ◽

Collision Avoidance System ◽

Risk Potential ◽

Blind Spots

<div class=""abs_img""><img src=""[disp_template_path]/JRM/abst-image/00270001/01.jpg"" width=""300"" />Risk potential estimation</div> Pedestrians darting out from blind spots in driver vision are typical scenarios in urban street environments, and conventional autonomous emergency braking systems reach safety limits if sensors do not detect the pedestrian in time to prevent accident or injury. The system must be able to anticipate such potential hazards and to anticipate such pedestrian action. This paper focuses on a pedestrian collision avoidance system that has a “driving-intelligence"" model. The model was designed by applying potential field theory using hazard-anticipatory knowledge. The effectiveness of the proposed system is confirmed by computer simulation. </span>

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