Automated Vehicles and its Safety Concerns Ronald R Mourant

Question: Discuss about theAutomated Vehicles and its Safety Concerns Ronald R Mourant. Answer: Talal-al-Shihabi and Ronald R Mourant In this article, the authors have done a research on human like driving behavior model. The framework of the model consists of a Perception unit, Emotions unit, Decision making unit and Decision implementation unit. All these units are interconnected. The Perception unit perceives the environment with the help of input data which is processed with fuzzy variables which assigns degree of truth values to the data and responds accordingly. The Emotions unit responds emotionally and plays an important role in defining the driving task as a reflective one. The Decision making unit investigates a state to find an action by looking through all possible options. The Decision implementation unit tries to implement the decisions by interfacing with Dynamic model. The separation between decision making and implementation comes from the fact that real drivers do not normally implement decisions as they make. The deployment of autonomous vehicles with human like driving characteristics would make make the driving more realistic and less predictable. The important parameters like steering factor, reaction time factor and alertness factor should be determined appropriately to avoid accidents. Fuzzy variables provide better depiction of human behavior and is used extensively in modeling each units. The four units help in building concrete human-like driver behavior models which depicts variation with same class but different driving behavior like aggressive, conservative and drunk drivers. Reference 2: Kathryn Seargeant (2017) The author of this article talks about Risk management issues and concerns related to autonomous vehicles. Factors considered are of cyber security, shift in liability and issue of control. Self driving cars requires smart road with build-in sensors and cameras involving extensive communication networks that would be vulnerable to cyber attack. The vehicles can be used as tools to track and study personal driving habits which maybe used by hackers backing for ransoms. Cyber-liability policies should assist with protection of such information. Cases of shift in liabilities is where owners distraction or negligence is ignored to that of automotive functionalities like navigation, electronics, camera etc. National Highway Traffic Safety Administration report on fatal accident of Model S of Tesla reads that some situations are extraordinary and beyond the autopilot system capabilities which requires full driver engagement at all times. The author pens down some of the benefits of autonom ous vehicles such as reduced emissions, fuel consumptions and fatal accidents at the same time points out challenges such as security vulnerabilities and liability shifts which should be noted to mitigate the risks associated with owning autonomous vehicles. Reference 3: Mitchell Cunningham, Michael A Regan The authors in this article describes the human factor challenges associated with transition from manually driven to self driven vehicles. National Highway Traffic Safety Administration (NHTSA) distinguishes five different levels of vehicle automation. Level 4 is of self driving automation where vehicle performs all functions and monitors roadway conditions. Human factor issues associated with self-driving vehicles are Driver inattention and distraction, Reduction in situational awareness, Over-reliance and trust, Skill degradation and Motion skickness. This leads to reduced vigilance which may pose problems for drivers when manual intervention during critical failures is required. Human factor research needs to be in areas of (HMI) Human machine interface and Driver state Assessment (DSA) technology which helps in keeping the driver involved in driving task and monitors drivers alertness in real time. NHTSA stresses the need to educate drivers to resume control the car in the event where it cannot operate automatically. The vehicles may become confused by unexpected events reminds the fact that this technology is not completely safe and reliable. Assignment 1: Part B (Abstract) Abstract: This case study gives an overview of driverless vehicle which is about to make in large fleets in near future. The advantages of self-driven cars can be seen as in reduction of emissions, fuel consumption and fatal accidents. But as the car is human centric so key decision making power should be left with human which may arise in situations like sensory degradation of self-driven cars in poor weather conditions leading to inability of on-board computer algorithms to make safe decisions. The use of HMI maintains situational awareness of the driver and also reduces his passive fatigue and thus the driver is always kept in loop. HMI signals with visual-auditory effects are found to be more efficient which helps in safer re-engagement. Legal liability policies in case of accidents and cyber security in cases of hacking also needs to be given its due importance. Diversity and personalisation of automated systems with respect to its driver also needs to be notified to maintain the emotiona l levels of the driver. Driver State Assessment technology should be properly researched. It is initially a costly affair for the state as it is required to provide smart roads with cameras and sensors in build which directly communicates with the vehicle. As self-driven cars seems to be the future so all the concerned parties i.e State, car company and the owners must be in loop during decision making process. Reference List Talal Al-Shihabi and Ronald R Mourant. A framework for Modeling Human-like Driving behaviours for Autonomous Vehicles in Driving simulators. https://pdfs.semanticscholar.org/ca37/cc15863662191250b382c637017472a7db7c.pdf Kathryn Sergeant. (2017). Autonomous Vehicles: Risk Management Issues and Concerns. https://www.lockton.com/whitepapers/Sergeant_Autonomous_Cars_Feb_2017-LR.pdf Mitchell Cunningham and Michael A. Regan. Autonomous Vehicles: Human Factors Issues and Future Research. https://acrs.org.au/files/papers/arsc/2015/CunninghamM%20033%20Autonomous%20vehicles.pdf