Decision-Making Self-Driving Car Control Algorithms: Intelligent Transportation Systems, Sensing and Computing Technologies, and Connected Autonomous Vehicles.

• Author: Slaby, Cheryl

1. Introduction

   The driving tasks will possibly be the entire accountability of self-driving cars concerning road environment perception, decision-making and sensorimotor monitoring. (Bellet et al., 2019) Sensory technology in self-driving cars should cut down motor vehicle accidents. (Woods, 2019) Highly automated vehicles may positively determine traffic safety by essentially altering the networking and communication between car users and vehicles, and how both of them gather and process data from their setting. (Ryerson et al., 2019)

2. Conceptual Framework and Literature Review

   As highly autonomous vehicle software is introduced, car users should advance precise mental patterns of it (De Gregorio Hurtado, 2017; Kral et al., 2018; McQuay, 2018; Nica, 2017; Sion, 2018) so as to perform adequately. (Endsley, 2019) A self-driving car can detect the setting and operate without the driver's input, by harnessing diverse sensing techniques (e.g. computer vision, localization, ultrasound, radar, and lidar), in addition to groundbreaking monitoring techniques (Katz, 2018; Massey et al., 2018; Meila, 2018; Popescu et al., 2018; Stroe, 2018) that can investigate the sensory information, so as to design and attain the preferred route to the intended destination. (You et al., 2019) Risk preference is quite pertinent to autonomous vehicle adoption as both autonomous vehicle technology and its networking with mobility systems are fraught with danger. (Wang and Zhao, 2019) The harnessing of groundbreaking driver assistance systems and the shift designed to meet the needs of semi-autonomous vehicles will result in a decreased prevalence of motor accidents while shaping the automobile insurance sector. (Perez-Marin and Guillen, 2019)

3. Methodology and Empirical Analysis

   Using and replicating data from AAA, ANSYS, Atomik Research, Axios, Ipsos, BCG, Capgemini Research Institute, and Schoettle & Sivak (2014), I performed analyses and made estimates regarding consumer attitudes toward autonomous vehicles and similar technology (%), consumer willingness to buy autonomous cars (%), and top 5 activities that urban/suburban and millennial consumers would like to engage in while in a self-driving car (%). Data were analyzed using structural equation modeling.

4. Results and Discussion

   Self-driving-cars may refashion transportation networks and thoroughly reorganize urban design strategies. (Stone et al., 2019) The smart car-to-car and car-to-infrastructure data transfer will invalidate the efficiency of any human over-ride involvement. (Hancock, 2019) Autonomy software will improve, its performance being inherently confined by its capacity to comparably grasp and predict the operations of other road users. (Endsley, 2019) In distinction to human-driven cars, connected and autonomous vehicles provide users...