automotive

Why artificial intelligence is disrupting both the automotive sector and its suppliers   Artificial intelligence will soon enable vehicles to control more driving scenarios, monitor driver attention and alert drivers to danger with reliability. These are some pretty major updates for an industry that hasn’t changed much in the last few decades. “A front-facing camera can discern where the driver is looking or, more importantly, where the driver is not looking,” said Tim Wong, one of the session’s speakers and a technical... [Lire la suite]

Developing HMI Systems to Integrate ADAS Functions The reality of fully autonomous vehicles is drawing ever closer, and increasingly sophisticated driver assistance technologies are permeating the industry. Today’s ‘semi-autonomous’ cars feature a range of support functions such as lane assist and automatic braking, and the sector has become a hotbed of innovation as OEMs scramble to be the first to market with new technology. Equally, infotainment and connected services have also been subject to rapid development, with connectivity... [Lire la suite]

Latin American automotive business boosted by new mobility applications The Latin American market is rapidly embracing new mobility business models with a focus on an on-demand, integrated, multi-modal mobility network, driven by changing demographics, preferences, and technology. Frost & Sullivan finds that converging trends will lead to a paradigm shift from vehicle ownership to vehicle usage. Mobility solutions such as eHailing, bike sharing, and integrated mobility are experiencing significant growth following... [Lire la suite]

Automotive revolution – perspective towards 2030 How the convergence of disruptive technology-driven trends could transform the auto industry ? Today’s economies are dramatically changing, triggered by development in emerging markets, the accelerated rise of new technologies, sustainability policies, and changing consumer preferences around ownership. Digitization and new business models have revolutionized other industries, and automotive will be no exception. For the automotive sector, these forces are giving rise to four... [Lire la suite]

Free Space detection in real time on standard architectures such as smartphones Here is the demo of RoadNex free space detection on a regular smartphone. Free space is detected in real time. On this version, "distant  sidewalks" are integrated into free space (it is an option) because sidewalks without pedestrians may be a option to avoid accident if it is not possible to brake as short as need and is the street is full of users. No need for a NVIDIA heavy computing architecture, no need for a MOBILEYE chip, etc ... Only the... [Lire la suite]

Smart, Social and Autonomous The automotive industry is undergoing rapid transformation because of changing demographics, lifestyles and new ownership models. An avalanche of intelligent technologies such as ADAS, in-vehicle electronics, autonomous driving features and rapid innovation in the ecosystem are redefining the pre-purchase, driving and transition experience.    There are a number of key trends that will influence the connected vehicle market in the next 3 to 5 years including the following... [Lire la suite]

5 Ways Artificial Intelligence is Impacting the Automotive Industry Finding applications of artificial intelligence in the automotive industry requires only a scant reading of news headlines. From IBM Watson’s partnership with the General Motors OnStar platform to Toyota’s $1 billion investment in AI-based self-driving technology, the marriage of AI with automotive technology has surely been consummated. It seems that every stakeholder in the automotive industry is looking for a way to capitalize on recent advances in AI technology. ... [Lire la suite]

China says half of its new cars will be AI-powered by 2020 SHANGHAI (Reuters) – China aims to implement artificial intelligence technology in at least half of all its new cars by 2020 and cover 90% of its big cities and highways with a wireless network that can support smart vehicles, its top state planner said on Friday. These goals are part of a draft for a national smart car strategy that the National Development and Reform Commission (NDRC) wants to seek public feedback for, it said in a statement. China is aiming to become... [Lire la suite]

DEEP LEARNING FOR ONBOARD APPLICATIONS: HIDDEN TRAP Now Deep Learning is used in onboard detection and pattern recognition applications. NEXYAD for instance uses Deep Learning in RoadNex (road detection without need of markings + detection of free space), and ObstaNex (obstacles detection). But if you do not analyse your INDUSTRIAL project in detail, you may have bad surprises : everone thinks he/she knows that the more numerous the training examples, the most accurate the KPIs. Let's say you used 1 billion km to train and... [Lire la suite]

5 Ways Artificial Intelligence is Impacting the Automotive Industry Finding applications of artificial intelligence in the automotive industry requires only a scant reading of news headlines. From IBM Watson’s partnership with the General Motors OnStar platform to Toyota’s $1 billion investment in AI-based self-driving technology, the marriage of AI with automotive technology has surely been consummated. It seems that every stakeholder in the automotive industry is looking for a way to capitalize on recent advances in AI technology. ... [Lire la suite]