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The successful and commercial use of self-driving/driverless/unmanned/automated car will make human life easier. The paper aims to discuss this issue.

This paper reviews the key technology of a self-driving car. In this paper, the four key technologies in self-driving car, namely, car navigation system, path planning, environment perception and car control, are addressed and surveyed. The main research institutions and groups in different countries are summarized. Finally, the debates of self-driving car are discussed and the development trend of self-driving car is predicted.

This paper analyzes the key technology of self-driving car and illuminates the state-of-art of the self-driving car.

The main research contents and key technology have been introduced. The research progress as well as the research institution has been summarized.

Marketing, new product launch and innovations.

Postgraduate students.

Maruti Suzuki India Ltd. (MSIL), established in February 1981, formerly known as MarutiUdyog Limited, is a subsidiary of Japanese automobile Manufacturer Suzuki. It has a market share of 37 per cent in passenger car segment in India. Its product portfolio ranges from entry-level Alto to hatchbacks like A-Star, Zen Estilo, etc. to sedans like SX 4 to sports utility vehicles like Grand Vitara. MSIL is always known for delivering value on these lines – low cost of acquisition, high fuel economy, less maintenance hassles and wide service network. MSIL is planning to launch its much awaited hatchback Celerio with revolutionary auto gear shift technology for the first time in India at an affordable price. Promotional campaign is yet to be completed. Online trends reflect the consumer trends of any country. During the Auto Expo Week, Maruti Suzuki Celerio became the most searched hatchback on Google in the subcontinent according to a report published by the Indian Express citing the Google Trends Report. One of the key success factor is communicating the right message to the customers so as to attract them. So, MSIL's challenge is to plan a product launch so as to spread awareness.

To discuss the ways in which the product may be differentiated, to acquaint students with the process of developing a slogan for the introduction of Celerio to the existing market, to explain the concept of segmentation to the students, to familiarize students with communication mix and to give the students an idea about need of digital communication to promote the product.

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Although digital transformation (DT) has emerged as an important phenomenon for both research and practices, the influences remain inconclusive and inadequate. The emerging artificial intelligence (AI) technologies further complicate the understanding and practices of DT while understudied yet. To address these concerns, this study takes a process perspective to empirically investigate when and how digital-intelligence transformation can improve firm performance, aiming to enrich the literature on digital-intelligence transformation and strategic information systems (IS) field.

Drawing on the dynamic capability view and business agility, we took a process perspective to conceptualize and empirically examine the influence of digital-intelligence transformation and the process characteristics. Taking a continuous panel dataset of listed Chinese firms covering 2007 to 2020, we investigated digital-intelligence transformation’s effect on firm performance and the moderating roles of three strategic aspects: pace, scope and rhythm.

This study found that digital-intelligence transformation positively affects firm performance and is moderated by the characteristics of transformation processes (i.e. pace, scope and rhythm). Specifically, the high-paced and rhythmic transformation processes facilitate the positive relationship, while the large scope undermines the benefits of transformation. These relationships hold across various endogeneity and heterogeneity analyses.

Our findings provide valuable implications for digital-intelligence transformation and strategic IS field. First, this study enriches existing literature on digital-intelligence transformation by empirically investigating the influence from a process perspective. Moreover, this study provides insights into a comprehensive understanding of the complexity of digital-intelligence transformation and the influences of AI. Finally, this study provides practical implications on how to make digital-intelligence transformation to benefit firm performance.

Level 3 automated driving, which has been defined by the Society of Automotive Engineers, may cause driver drowsiness or lack of situation awareness, which can make it difficult for the driver to recognize where he/she is. Therefore, the purpose of this study was to conduct an experimental study with a driving simulator to investigate whether automated driving affects the driver’s own localization compared to manual driving.

Seventeen drivers were divided into the automated operation group and manual operation group. Drivers in each group were instructed to travel along the expressway and proceed to the specified destinations. The automated operation group was forced to select a course after receiving a Request to Intervene (RtI) from an automated driving system.

A driver who used the automated operation system tended to not take over the driving operation correctly when a lane change is immediately required after the RtI.

This is a fundamental research that examined how the automated driving operation affects the driver's own localization. The experimental results suggest that it is not enough to simply issue an RtI, and it is necessary to tell the driver what kind of circumstances he/she is in and what they should do next through the HMI. This conclusion can be taken into consideration for engineers who design automatic driving vehicles.

This study aims to develop an automatic lane-change mechanism on highways for self-driving articulated trucks to improve traffic safety.

The authors proposed a novel safety lane-change path planning and tracking control method for articulated vehicles. A double-Gaussian distribution was introduced to deduce the lane-change trajectories of tractor and trailer coupling characteristics of intelligent vehicles and roads. With different steering and braking maneuvers, minimum safe distances were modeled and calculated. Considering safety and ergonomics, the authors invested multilevel self-driving modes that serve as the basis of decision-making for vehicle lane-change. Furthermore, a combined controller was designed by feedback linearization and single-point preview optimization to ensure the path tracking and robust stability. Specialized hardware in the loop simulation platform was built to verify the effectiveness of the designed method.

The numerical simulation results demonstrated the path-planning model feasibility and controller-combined decision mechanism effectiveness to self-driving trucks. The proposed trajectory model could provide safety lane-change path planning, and the designed controller could ensure good tracking and robust stability for the closed-loop nonlinear system.

This is a fundamental research of intelligent local path planning and automatic control for articulated vehicles. There are two main contributions: the first is a more quantifiable trajectory model for self-driving articulated vehicles, which provides the opportunity to adapt vehicle and scene changes. The second involves designing a feedback linearization controller, combined with a multi-objective decision-making mode, to improve the comprehensive performance of intelligent vehicles. This study provides a valuable reference to develop advanced driving assistant system and intelligent control systems for self-driving articulated vehicles.

The single recent event that has most significantly changed the way in which automotive transmission fluids are defined took place in 1990 when General Motors published its Dexron HE specification. This represented the first major modification of General Motors' Automatic Transmission Fluid (ATF) specifications since July 1978. (The original Dexron II specification was first published in 1973.) The driving force behind the timing for the introduction of this specification was the launch, in 1991, of the Buick Park Avenue with a newly redesigned, electronically‐controlled version of the older Hydramatic 440‐T4 Front‐Wheel‐Drive (FWD) automatic transaxle. This unit was designated the 4T‐60E. The majority of designers of computer‐controlled transmissions use electro‐hydraulic solenoid valves to open and close hydraulic circuits to make the transmission shift. For this reason, many of the new transmission designs require ATFs to have superior low‐temperature fluidity properties. Dexron IIE calls for fluids having a −40°C Brookfield viscosity of less than 20,000 cP, compared with the 50,000 cP requirement of the Dexron II. Only fluids approved to the new specification will be officially endorsed by GM from January 1993.