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How Artificial Intelligence is Driving the Memory Market for Autonomous and Connected Vehicles


How Artificial Intelligence is Driving the Memory Market for Autonomous and Connected Vehicles

One of the important technologies that have emerged over the past few is that of artificial intelligence (AI). The technology is being utilized in various industries for making processes and operations simpler. Just like other industries, AI is also being widely utilized in the automotive industry for making vehicles safer and more secure. The technology is being utilized in infotainment systems that are now serving as personal assistants, aiding the driver by offering efficient navigational support, and responding to voice commands. This increasing utilization of AI is creating wide data storage capacity.

Autonomous and connected cars are generating large amounts of data, since they are extensively making use of electronic functions for providing greater efficiency, greater safety, driver assist capabilities, richer telemetric and entertainment functions, and communication between local networks and vehicles. Owing to these factors, the global memory market for autonomous and connected vehicles generated a revenue of $4,310.8 million in 2019 and is predicted to advance at a 23.9% CAGR during the forecast period (2020–2030), as per a report by P&S Intelligence. The major applications of the memory market in the automotive industry are telematics, navigation, and infotainment.

Out of these, the largest amount of data was generated by navigation features in the past, which can majorly be attributed to the surging adoption of these systems in vehicles. Navigation systems generate data related to alternative routes, shortest route, and traffic or checkpoints on the road, and need efficient storage mechanism. Apart from this, the telematics application is also predicted to make create demand for data storage capacity in the coming years, which is particularly because of the increasing preference for autonomous and connected vehicles. The system captures data via sensors, radars, and cameras.

Different types of memories in the automotive industry are NOT-AND (NAND) flash, dynamic random-access memory (DRAM), and static random-access memory (SRAM). Among all these, the demand for DRAM has been the highest up till now, owing to their effective storage of data and relatively low cost. Both commercial and passenger vehicles generate data, thereby creating a need for memory; however, the largest demand for memory was created by passenger cars in the past. This is because of the fact that passenger vehicles are produced more than commercial vehicles. Furthermore, new technologies are first implemented in passenger vehicles for testing purposes in the automotive industry.

In the past, North America emerged as the largest memory market for autonomous and connected vehicles, and the situation is predicted to be the same in the coming years as well. This can be ascribed to the presence of a large number of automotive technology companies and increasing sales of connected and autonomous vehicles in the region. Moreover, the disposable income in people in North America is high as well, owing to which, they are able to spend more on luxury vehicles that are equipped with advanced, connectivity, safety, and autonomous features.

Hence, the demand for memory in autonomous and connected vehicles is growing due to the increasing demand for safety features in vehicles.

Source: P&S Intelligence



Last mile delivery is the most expensive part of the delivery chain, often representing more than 50 percent of the overall cost. This is mainly because it is the least productive and automated step. As such, many are seeking to bring automation into the last mile. In recent years, many companies around the world have been innovating to utilize autonomous mobile robots, drones, and autonomous vehicle technology.

Various autonomous robots and vehicles (sometimes called pods) are being developed around the world. These come in a variety of shapes and forms, reflecting the diversity and breadth of design and technology choices which must be made to create such products.

Drone Delivery: a Game Changer in Instant Fulfilment?

My new IDTechEx report, “Mobile Robots, Autonomous Vehicles, and Drones in Logistics, Warehousing, and Delivery 2020-2040,” covers the use of mobile robots, drones, and autonomous vehicles in delivery, warehousing and logistics—and suggests these could create a $1 billion market by 2030. That shows how far we have come since a previous IDTechEx report, “Mobile Robots and Drones in Material Handling and Logistics 2017-2037,” which analyzed the technologies that were then emerging in the last mile delivery space, including drones and autonomous mobile ground robots (or droids).

Several players, big and small, have entered the drone delivery game since then, but at the time of the 2017 report, the idea of drone delivery was sharply dividing commentator opinion, with some dismissing it as a mere publicity stunt.

Indeed, drone delivery must be viewed within the context of the emerging drone industry, which has grown to a more than $1.5 billion industry. In the ensuing years, consumer drones’ hardware platform became rapidly commoditized with prices falling.

The idea of drone delivery entered the mainstream media in late 2013. Around that time, drone delivery of e-commerce parcels was first demonstrated in parallel with drones successfully delivering medicine to remote areas. Since then numerous deliveries have been made, partnerships announced, and substantial sums invested.

Fleet Operation to Compensate for Poor Individual Drone Productivity?

Drone delivery faced critical challenges in 2017. Individual drones offer limited productivity compared to traditional means of delivery (e.g., consider a van delivering 150 parcels in an eight-hour shift). They can only carry small payloads and battery technology limits their flight duration, constraining them to around 30 minutes radius of their base while further lowering their productivity due to the downtime needed for re-charging/re-loading.

The limited productivity, in our view, is not a showstopper. This is because fleet operation can compensate for poor individual drone productivity. The unit cost of drones will be substantially lower than, say, a van, enabling the conversation of a few, highly-productive vehicles into many small drones with high productivity at the fleet level. This will require a further major reduction in hardware costs for commercial drones, but if the past is to be our guide, this will be inevitable.

Limited payload is also not a showstopper because, according to Amazon statistics, some 85 percent of packages weigh 5 pounds or fewer. Furthermore, the fall in delivery costs and time for customers is changing purchasing habits: frequent orders of small items is replacing that big infrequent order. This matches well to the strong points of drones.

The limited range is also not a showstopper even in suburban areas where customers do not live close to a distribution point. It will, however, mandate a gradual yet wholesale change in the location of warehouses with more placed closer to end customers or the use of large mobile drone carrier vans. The former is already happening in the background, while the latter has also been demonstrated at the proof-of-concept level.

Sidewalk Last-Mile Delivery Robots: a Billion-Dollar-Market by 2030?

Sidewalk robots are often designed to travel slowly at 4-6 km/hr (or 2.5-3.7 mph). This is to increase safety, to give robots more thinking time, to give remote teleoperators the chance to intervene, and to enable categorizing the robot as a personal device (vs. a vehicle), thus easing the legislative challenges.

However,  sidewalk robots are still far from being totally autonomous. First, they are often deployed in environments such as U.S. university campuses where there is little sidewalk traffic and where the sidewalks are well-structured. Many robots are also restricted to daylight and perception-free conditions. Critically, the suppliers also have remote teleoperator centers. The ratio of operators to robots will need to be kept to an absolute minimum if such businesses are to succeed.

There is still much work to do to improve the navigation technology. The robots will need to learn to operate in more complex and varied environments with minimal intervention. Furthermore, capital is also essential. The end markets are also highly competitive, imposing tough price constraints.

In general, we forecast a 200,000-unit fleet size until 2035 (accounting for replacement). The inflection point will not occur until around the 2025 period given the readiness level of the technology. This suggests both a large robot sales market and an even larger annual delivery services market provided asset utilization can be high (the services income could reach $1.6 billion by 2035 in a reasonable scenario).

Sidewalk Delivery Robots vs. Autonomous Delivery Vans

These robots, pods and vehicles are mainly designed from scratch to be unmanned. They are also almost always battery-powered and electrically-driven. This is for various reasons, including: (1) electronic drive gives better control of motion, especially when each wheel can be independently controlled; (2) the interface between the electronic control system and the electrical drive train is simpler, eliminating the need for complex by-wire systems found in autonomous ICE vehicles; and (3) their production process needs to handle vastly fewer parts, and as such could be taken on by smaller manufacturers.

Another key technology and business choice is where to navigate. Many robots are designed to travel on sidewalks and pedestrian pavements, while the van-looking pods and vehicles are often designed to be road-going. This choice of where to travel has determining consequences for the design, technology choice, target markets and business model.

Sidewalk robots are an interesting proposition. They come with various hardware choices. For example, some are few-wheeled while many are six-wheeled. Some include a single small-payload compartment, while others carry larger multi-item storage compartments. The key choice, however, is in what perception sensors to use.

Navigation Technology Choices

Mobile robots come with various hardware choices, e.g., number of motor-controlled wheels, payload size and compartment design, battery size, etc. Almost all have HD cameras around the robot to give teleoperators the ability to intervene All also have IMUs and GPS and most have ultrasound sensors for near-field sensing.

A critical choice is whether to use lidar-only, stereo-vision-only, or hybrid. Lidar can give excellent 360deg ranging information with spatial resolution and a dense point cloud which enables good signal processing. Lidars, however, are expensive and can have near-field (a few cm) blindspot. Therefore, the choice to use lidars will represent a bet for the cost of lidar technology to dramatically fall.

Most robots deploying lidars use 16-channel RoboSense or Velodyne lidars. These are mechanical rotating lidars, giving surround viewing. The technology of lidars is evolving with the likes of MEMS or OPA emerging. These could enable cost reduction but will reduce FoV (field of view), thus mandating the use of more lidar units per robot.

We project that the cost of lidars is to significantly fall over the coming years. This has the potential to put such robots on the path towards business viability. The other challenge is near-field blindspots. This is not an issue with cars, but can be in a sidewalk, where many low-lying objects can reside closely to the robot. To resolve these, complementary sensors will be needed.

The other approach is to go lidar-free, using stereo camera as the main perception-for-navigation sensor. This will require the development of camera-based algorithms for localization, object detection, classification, semantic segmentation, and path planning.

No off-the-shelf software solution exists. Indeed, no labeled training dataset exists that would allow training lidar-based, camera-based or hybrid deep neutral networks (DNNs) for sidewalk navigation. The sidewalk environment is vastly different to that of the on-road vehicles. As such, companies will need to collect, calibrate, and meticulously label their own datasets. Furthermore, the datasets will require great diversity to accommodate different light, perception, and local conditions. Deployments in many sites even as pilot programs are essential in further improving the robots and can indeed represent a competitive advantage.

The robots are energy-constrained. As such, the number of on-board processors and GPUs should be kept to a minimum, and heavy-duty computational tasks such as 3D map-making and edge-extraction should be carried off-line in powerful services. This almost always happens when robots are deployed to a new environment: They are walked around to capture data, the data is sent to servers for processing so it can be converted into a suitable map, earmarking edges, many classes of fixed objects, drivable paths, and so on.

Long Road to Profitability Lies Ahead

In general, there is still much work to do to improve navigation technology. The robots will need to learn to operate in more complex and varied environments with minimal intervention. This requires extensive investment in software development. This ranges from gathering data, defining object classes, labeling the data, and training the DNNs in many environments and conditions. It also requires writing algorithms for the many challenges the robots encounter in their autonomous operation.

Furthermore, capital is also essential. The businesses are heavy on development costs, especially software costs. The end markets are also highly competitive, imposing tough price constraints. The hardware itself is likely to be commoditized and many will outsource manufacturing once they have settled on a suitable final design. The payback for many will be having a large fleet to offer robots as a delivery service.

Future Outlook: Significant Robot Sale and Delivery Services Opportunity

Sales and delivery firms are likely to have a long road ahead of them before they reach profitability. They should improve the robots to work in more scenarios beyond well-structured neighborhoods and campuses, to extend their operation to all-day and all-weather conditions, and to extend autonomous operation with little error to nearly all scenarios to drive down the remote operator-to-fleet size ratio.

The deployed fleet size will need to dramatically increase to expand income from delivery services and allow the amortization of the software development costs over many units sold.

We have analyzed all the key companies and technologies in this emerging field. We have also constructed a forecast model, considering how the productivity of last-mile mobile robots is likely to evolve over the years. We have developed various scenarios, assessing the current and future addressable market size in terms of total accumulated fleet size. Our fleet deployment forecasts and penetration rate forecasts are based upon on reasonable market and technology assessments and roadmaps.

Consequently, our forecasts suggest, that despite the upfront technology and market challenges, the market will grow and those who plant their seeds today will reap the benefits tomorrow.


Dr. Khasha Ghaffarzadeh is the research director at IDTechEx, where he has helped deliver more than 50 consulting projects across the world. The projects have covered custom market research, technology scouting, partnership/customer development, technology road mapping, product positioning, competitive analysis and investment due diligence.

His report “Mobile Robots, Autonomous Vehicles, and Drones in Logistics, Warehousing, and Delivery 2020-2040” covers the use of mobile robots, drones, and autonomous vehicles in delivery, warehousing and logistics. It provides a comprehensive analysis of all the key players, technologies and markets, covering automated as well as autonomous carts and robots, automated goods-to-person robots, autonomous and collaborative robots, delivery robots, mobile picking robots, autonomous material handling vehicles such as tuggers and forklifts, autonomous trucks, vans, and last mile delivery robots and drones. You can find the report here:

You can find his report “Mobile Robots and Drones in Material Handling and Logistics 2017-2037” here:

IDTechEx guides strategic business decisions through its Research, Consultancy and Event products, helping clients profit from emerging technologies. For more information on IDTechEx Research and Consultancy, contact or visit

How Technology can Improve your Logistics Operations

Like most other industries, the logistics industry faces a gradual transformation towards adapting to the internet age. The advent of new technologies invalidates age-old approaches and processes, creating the need for modernization. And with the logistics industry being as massive as it is, it’s understandable that it can be notably lucrative. Between risk mitigation and automation, there are many ways in which adaptive technology can benefit this $4 trillion industry. With that said, let us explore just how technology can improve your logistics operation.

The significance of efficiency

Before delving into specifics, it is vital to note the undisputed value of efficiency in the logistics industry.

As mentioned before, this 4$ trillion industry is massive, and its interconnectivity with other industries is apparent. Thus, efficient logistics operations can yield considerable productivity gains across the board. Not only can they provide a competitive advantage, but they can also guarantee better overall operation cohesion. Logistics software can greatly enhance one’s control and oversight of supply chains, increasing response times to potential disruptions. After all, customers of all industries value a swift delivery of goods and services, as well as quality customer support. Such software can augment all of those aspects, ensuring that potential challenges are easier to overcome.

Shipment Tracking Systems and Radio Frequency Identification (RFID)

A technology that has already caught on, albeit to varying degrees, is shipment tracking. As customers would previously be unaware of their order’s status, shipment tracking systems have rectified this somewhat. With 24/7 access to shipment status information, customers can rest assured that their order is indeed underway. Some tracking systems even offer additional information and shipment notifications for additional insights and convenience. This solution can indeed improve your logistics too, no less than customer experience. Constant monitoring can save your time and money, as well as unclog your customer service channels.

Likewise, on the front of cargo management, RFID technology has also seen use in recent years. In essence, RFID tags or sensors allow companies to keep track of their inventory. Both labor-saving and cost-effective, RFID tags are often used in distribution warehouses as a means of monitoring containers. Such industries as the apparel industry are also using RFID technology for tracking purposes, with very notable success. Should you be contemplating how technology can improve your logistics operation, RFID solutions could be a reasonable step to take.

Automation and robotics

On the subject of warehouse optimization, then, technology has provided another asset; automation. Naturally, automation can yield many benefits to many industries, but logistics is unquestionably one of them. From increased performance to reduced labor costs, automation is undoubtedly a valuable asset.

Automation offers to improve operational efficiency in machines, and has already seen effective use in such trade hubs as Holland’s Port of Rotterdam. Namely, its use of fully-automated terminals allows it to reap the aforementioned benefits in terms of unloading cargo. It’s estimated that this approach increases overall productivity by as much as 30 percent – a very notable net benefit.

Similarly, robots have facilitated the rapid growth of online sales across many industries. While they are quite dissimilar from automation in many regards, they too can automate operations and thus decrease labor costs. Most notably, as far as e-commerce is concerned, Amazon has been innovative in this front. Its use of Kiva robots has reduced the company’s expenses by as much as 20 percent. A notable feat, enough so that other companies also seek to employ robots in their warehouses.

Drones and autonomous vehicles

In much the same way as automation and robotics, technology has provided logistics companies with drones and autonomous vehicles. Similar in function, both can be fine examples of how technology can improve your logistics operation.

Drones have seen surges in functionality in recent times, elevated from a niche solution to one with potentially global applications. This development was understandably followed by an array of eager high-profile adopters, such as UPS. A potential innovation in terms of product delivery indeed, drones can expand delivery options to both urban and rural areas. More fortunately still, their nature allows them to also improve logistics, by removing the factor of human error.

Likewise, autonomous vehicles can offer similar convenience. In part due to relatively lower regulations and easier testing, self-driving vehicles have been an accessible technological advancement for many logistics operations. Of course, it’s notable that this technology is currently mostly limited to warehouse management, such as autonomous forklifts and trucks. However, with rapid advancements, it may not be long before autonomous trucks can traverse the world’s highways. Both in their current and potential future forms, autonomous vehicles can quite possibly be a massive asset to any company.


As technology makes rapid strides, one can realistically expect vast logistics optimization potential. From warehouse management and monitoring to shipment tracking and delivery, the possibilities seem endless. When contemplating how technology can improve your logistics operation, both the present and the future hold much promise. And as supply chains expand and grow, it will be vital to adapt to such technologies to remain competitive.


James Clarkson is a freelance web designer and author. He often writes analyses of the shipping and moving industries, and of the SEO needs of both. He’s a frequent writer for Verified Movers, as well as other companies.