Wireless safety personnel radio device for collision avoidance system of autonomous vehicles

2002 ◽  
Author(s):  
You Chung Chung ◽  
S.L. Olsen ◽  
L. Wojcik ◽  
Zhen Song ◽  
Chenghong He ◽  
...  
Keyword(s):  
Collision Avoidance ◽  
Autonomous Vehicles ◽  
Collision Avoidance System ◽  
Radio Device ◽  
Safety Personnel

scholarly journals An Investigation into the Appropriateness of Car-Following Models in Assessing Autonomous Vehicles

Sensors ◽  
2021 ◽  
Vol 21 (21) ◽  
pp. 7131
Author(s):  
Akito Higatani ◽  
Wafaa Saleh
Keyword(s):  
Collision Avoidance ◽  
Autonomous Vehicles ◽  
Full Range ◽  
Detection Range ◽  
Car Following ◽  
Car Following Model ◽  
System Module ◽  
Time Gap ◽  
Collision Avoidance System ◽  
Almost All

The dramatic progress of Intelligent Transportation Systems (ITS) has made autodriving technology extensively emphasised. Various models have been developed for the aim of modelling the behaviour of autonomous vehicles and their impacts on traffic, although there is still a lot to be researched about the technology. There are three main features that need to be represented in any car-following model to enable it to model autonomous vehicles: desired time gap, collision avoidance system and sensor detection range. Most available car-following models satisfy the first feature, most of the available car-following models do not satisfy the second feature and only few models satisfy the third feature. Therefore, conclusions from such models must be taken cautiously. Any of these models could be considered for updating to include a collision avoidance-system module, in order to be able to model autonomous vehicles. The Helly model is car-following model that has a simple structure and is sometimes used as the controller for Autonomous Vehicles (AV), but it does not have a collision avoidance concept. In this paper, the Helly model, which is a very commonly used classic car-following model is assessed and examined for possible update for the purpose of using it to model autonomous vehicles more efficiently. This involves assessing the parameters of the model and investigating the possible update of the model to include a collision avoidance-system module. There are two procedures that have been investigated in this paper to assess the Helly model to allow for a more realistic modelling of autonomous vehicles. The first technique is to investigate and assess the values of the parameters of the model. The second procedure is to modify the formula of that model to include a collision avoidance system. The results show that the performance of the modified full-range Auto Cruising Control (FACC) Helly model is superior to the other models in almost all situations and for almost all time-gap settings. Only the Alexandros E. Papacharalampous’s Model (A.E.P.) controller seems to perform slightly better than the (FACC) Helly model. Therefore, it is reasonable to suggest that the (FACC) Helly model be recommended as the most accurate model to use to represent autonomous vehicles in microsimulations, and that it should be further investigated.

scholarly journals Driving and steering collision avoidance system of autonomous vehicle with model predictive control based on non-convex optimization

2021 ◽  
Vol 13 (6) ◽  
pp. 168781402110276
Author(s):  
Yuho Song ◽  
Kunsoo Huh
Keyword(s):  
Convex Optimization ◽  
Collision Avoidance ◽  
Autonomous Vehicles ◽  
Autonomous Vehicle ◽  
Lane Changes ◽  
Vehicle Communication ◽  
Rapid Control ◽  
Rapid Control Prototyping ◽  
Predictive Controller ◽  
Collision Avoidance System

A planar motion control system is proposed for autonomous vehicles not only to follow the lanes, but also to avoid collisions by braking, accelerating, and steering. The supervisor is designed first to determine the desired speed and the risk of the maneuvering due to road boundaries and obstacles. In order to allow lane changes on multi-lane roads, the model predictive controller is formulated based on the probabilistic non-convex optimization. The micro-genetic algorithm is applied to calculate the target speed and target steering angle in real time. A software-in-the-loop unit is constructed with the Rapid Control Prototyping device in the vehicle communication environment. The performance of the proposed system is verified for various collision avoidance scenarios and the simulation results demonstrate the safe and effective driving performance of autonomous vehicles with no collision on multi-lane road.

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