Path Tracking on Autonomous Vehicle for Severe Maneuvre

Autonomous vehicle consists self-learning process consists recognizing environment, real time localization, path planning and motion tracking control. Path tracking is an important aspect on autonomous vehicle. The main purpose path tracking is the autonomous vehicle have an ability to follow the predefined path with zero steady state error. The non-linearity of the vehicle dynamic cause some difficulties in path tracking problems. This paper proposes a path tracking control for autonomous vehicle. The controller consists of a relationship between lateral error, longitudinal velocity, the heading error and the reference yaw rate. In addition, the yaw rate controller developed based on the vehicle and tyre model. The effectiveness of the proposed controller is demonstrated by a simulation

A systematic review on the autonomous emergency steering assessments and tests methodology in ASEAN

Safety should be the top priority for any automaker - because traffic accidents roughly killed 1.4 million people worldwide, ranking tenth on the World Health Organization's list of leading causes of death. Two decades ago, the focus was on passive safety, where it helps vehicle occupants to survive the crash. However, the frontier in safety innovation has moved beyond airbags and side-impact protection. Today, the frontier is active safety for preventing collisions before they occur. In Euro NCAP 2025 Roadmap, this active safety frontier falls under the primary safety and has become one of the overall safety rating initiatives toward safer cars. The primary safety features four technologies to be assessed, including driver monitoring (2020), automatic emergency steering (2020, 2022), autonomous emergency braking (2020, 2022), and V2x (2024). However, this initiative is partially encapsulated in the ASEAN NCAP Roadmap 2021-2025 under – 'Safety Assist' technological feature. For instance, in the new roadmap, ASEAN NCAP only focuses on Auto Emergency Braking (AEB) technology. This AEB is a feature to alert drivers to an imminent crash and help them use the car's maximum capacity. Therefore, as benchmarked to the EURO NCAP, this paper comprehensively reviews the AES demand, assessments, control, and testing methodology and can be further developed to consolidate for the ASEAN NCAP safety rating schemes

Multiple vehicle cooperation and collision avoidance in automated vehicles : Survey and an AI‑enabled conceptual framework

Prospective customers are becoming more concerned about safety and comfort as the automobile industry swings toward automated vehicles (AVs). A comprehensive evaluation of recent AVs collision data indicates that modern automated driving systems are prone to rear-end collisions, usually leading to multiple-vehicle collisions. Moreover, most investigations into severe traffic conditions are confined to single-vehicle collisions. This work reviewed diverse techniques of existing literature to provide planning procedures for multiple vehicle cooperation and collision avoidance (MVCCA) strategies in AVs while also considering their performance and social impact viewpoints. Firstly, we investigate and tabulate the existing MVCCA techniques associated with single-vehicle collision avoidance perspectives. Then, current achievements are extensively evaluated, challenges and flows are identified, and remedies are intelligently formed to exploit a taxonomy. This paper also aims to give readers an AI-enabled conceptual framework and a decision-making model with a concrete structure of the training network settings to bridge the gaps between current investigations. These findings are intended to shed insight into the benefits of the greater efficiency of AVs set-up for academics and policymakers. Lastly, the open research issues discussed in this survey will pave the way for the actual implementation of driverless automated traffic systems

Piecewise trajectory replanner for highway collision avoidance systems with safe-distance based threat assessment strategy and nonlinear model predictive control

This paper proposes an emergency Trajectory Replanner (TR) for collision avoidance (CA) which works based on a Safe-Distance Based Threat Assessment Strategy (SDTA). The contribution of this work is the design of a piecewise-kinematic based TR, where it replans the path by avoiding the invisible rectangular region created by SDTA. The TR performance is measured by assessing its ability to yield a maneuverable path for lane change and lane keeping navigations of the host vehicle. The reliability of the TR is evaluated in multi-scenario computational simulations. In addition, the TR is expected to provide a reliable replanned path during the increased nonlinearity of high-speed collisions. For this reason, Nonlinear Model Predictive Control (NMPC) is adopted into the design to track the replanned trajectory via an active front steering and braking actuations. For path tracking strategy, comparisons with benchmark controllers are done to analyze NMPC’s reliability as multi-actuators nonlinear controller of the architecture to the CA performance in high-speed scenario. To reduce the complexity of the NMPC formulation, Move Blocking strategy is incorporated into the control design. Results show that the CA system performed well in emergency situations, where the vehicle successfully replanned the obstacle avoidance trajectory, produced dependable lane change and lane keeping navigations, and at the same time no side-collision with the obstacle’s edges occurred. Moreover, the multi-actuators and nonlinear features of NMPC as the PT strategy gave a better tracking performance in high-speed CA scenario. Assimilation of Move Blocking strategy into NMPC formulation lessened the computational burden of NMPC. The system is proven to provide reliable replanned trajectories and preventing multi-scenario collision risks while maintaining the safe distance and time constraints

Piecewise Trajectory Replanner for Highway Collision Avoidance Systems with Safe-Distance Based Threat Assessment Strategy and Nonlinear Model Predictive Control

This paper proposes an emergency Trajectory Replanner (TR) for collision avoidance (CA) which works based on a Safe-Distance Based Threat Assessment Strategy (SDTA). The contribution of this work is the design of a piecewise-kinematic based TR, where it replans the path by avoiding the invisible rectangular region created by SDTA. The TR performance is measured by assessing its ability to yield a maneuverable path for lane change and lane keeping navigations of the host vehicle. The reliability of the TR is evaluated in multi-scenario computational simulations. In addition, the TR is expected to provide a reliable replanned path during the increased nonlinearity of high-speed collisions. For this reason, Nonlinear Model Predictive Control (NMPC) is adopted into the design to track the replanned trajectory via an active front steering and braking actuations. For path tracking strategy, comparisons with benchmark controllers are done to analyze NMPC’s reliability as multi-actuators nonlinear controller of the architecture to the CA performance in high-speed scenario. To reduce the complexity of the NMPC formulation, Move Blocking strategy is incorporated into the control design. Results show that the CA system performed well in emergency situations, where the vehicle successfully replanned the obstacle avoidance trajectory, produced dependable lane change and lane keeping navigations, and at the same time no side-collision with the obstacle’s edges occurred. Moreover, the multi-actuators and nonlinear features of NMPC as the PT strategy gave a better tracking performance in high-speed CA scenario. Assimilation of Move Blocking strategy into NMPC formulation lessened the computational burden of NMPC. The system is proven to provide reliable replanned trajectories and preventing multi-scenario collision risks while maintaining the safe distance and time constraints

Space station systems: A bibliography with indexes (supplement 9)

This bibliography lists 1,313 reports, articles, and other documents introduced into the NASA scientific and technical information system between January 1, 1989 and June 30, 1989. Its purpose is to provide helpful information to researchers, designers and managers engaged in Space Station technology development and mission design. Coverage includes documents that define major systems and subsystems related to structures and dynamic control, electronics and power supplies, propulsion, and payload integration. In addition, orbital construction methods, servicing and support requirements, procedures and operations, and missions for the current and future Space Station are included