Exclusive: Cognata’s new strategy

Cognata Company from Rehovot, Israel, has announced few weeks ago the appointment of Dr. Gahl Berkooz as Chief Data Officer and President, Americas. This is a new function in the company, and staffing it with a senior, experienced figure reveals new Cognata’s strategy to move from supplying a simulator towards complete procedural solution intended for both development and validation of ADAS and autonomous driving systems. The goal of this platform is to cover all the phases – starting at creating and managing data and ending at executing verification processes that are obliged throughout product lifecycle.  

Nowadays, smart vehicle is conceptualized as a computer on wheels, an instrument that produces enormous amounts of data that needs to be managed and utilized in the form of analytics and monetization. However, when Berkooz joined Ford in 2004, the field of connected vehicle was in  its infancy, and the interface between cars, data and computers was far less natural. In a  conversation with Techtime, Berkooz, who holds a Ph.D. in Applied Mathematics from Cornell  University, says: “The data area among major vehicle manufacturers was a mess. As the connected car field evolved, it was clear that we need a new approach regarding data management and the  way we can utilize it”. 

During his time at Ford, Berkooz was in charge of establishing the Information Management and Analytics at the OEM, both organizational data and data that is produced and consumed by drivers.  He was the one who formulated the way data is collected and standartized to produce analytics and monetization. Later, he moved to General Motors as Chief of Analytics for General Motors’ Global  Connected Customer Experience (OnStar) Division, where he led similar processes between 2016- 2018. 

Berkooz arrived at Cognata through his third career’s milestone, German Tier-1 ZF, where he established the ZF Digital Venture Accelerator, building technology start-ups for ZF. Cognata and ZF  are collaborating for several years. “I was introduced to Cognata through ADAS development startup who worked in collaboration with Cognata. This cooperation emphasized the need of reducing ADAS verification costs”, said Berkooz. 

The way to autonomy is paved with endless milage 

At the beginning of the technological journey towards autonomy, AV developers based their testing mainly on test drives, intended to train the systems and verify their reliability in recognizing the environment and decisions making. However, car industry quickly realized that these road tests have limited efficiency.  

Berkooz: “Road tests are an expensive operation, and it is hard to ‘catch’ rare scenarios. Car industry is trying to form the most efficient and proper way of validating ADAS. As the level of autonomy is higher, the range of validation is increased, and in a non-linear manner, since the more the vehicle is responsible for more driving aspects, more scenarios should be evaluated, and the coverage must be greater accordingly”. 

As of today, the focus in ADAS development and verification is moving from road tests to simulators. Cognata’s simulator creates virtual environment that imitates the road in detail, starting at the exact  street mapping, drivers and cars behavior and ending at small, unexpected items such as road flaws, trash cans, signs, trees and even a cat suddenly running into the road. Cognata’s simulator is capable  of systematically producing driving scenarios’ clusters, which evaluate the functionality of sensors and computing units at every situation they may encounter in the jungle called “the road”. 

From simulation company to data company 

However, although using a simulator significantly accelerates the development and test processes, one can not based the verification of a safety system solely om simulator, since simulation is  eventually only an approximation of reality.  

Dr. Gahl Berkooz

According to Berkooz, Cognata is now formulating a strategy where the simulator is just another  instrument in a complete ecosystem of processes and solutions for developing and validating ADAS. “The simulator  is not the center, the data are. Eventually, the simulator is an instrument for generating data to be  used by development, training and validating processes. Cognata is striving to position itself as a  data company, whether it is data generated by simulator in virtual environment or actual data  collected by sensors and road tests. Our algorithms provide us with the capability of taking road test’s data and alter parameters such as sight angle. We take the data and make it meta-data that generates additional data”.

Berkooz explains the validation processes are currently decentralized, and there is a need for a  platform to concentrate all the processes, the same way it’s done in the PLM plaforms. “We are moving towards focusing on developing data tools and assets. OEMs generate a lot of data during road tests, but they have no methodology that enable them to make use of this data as part of their future development efforts. The goal is to provide a unified platform that supports data from simulations as well as from actual sensors. This will help reducing verification and road tests costs. This synergy opens a whole new world of possibilities.” 

IDF choose Coganta’s rough terrain simulator

IDF, through the Department of Production and Procurement in the Ministry Of Defense, purchased Coganta’s simulator, which simulate terrain driving. IDF will use the simulator to validate and train autonomous driving algorithms, as part of the development of autonomous vehicles (AV) and advanced driver assistance systems (ADAS) for military usage.

 Coganta’s AV Off-road simulator is a new platform, intended for training and testing of autonomous vehicles driving in difficult terrain conditions on unpaved roads, to include military vehicles such as unmanned tools and remotely operated vehicles (ROV). The system simulates many scenarios, to include off-road driving on unpaved roads, narrow trails, steep slopes, muddy or sandy ground, as well as obstacles along the path such as rocks or vegetation, and driving in poor visibility conditions like darkness or limited view angles.   

Simulating terrain driving features complex challenges. Unlike public road, where the driving route is clear and regulated, in maneuvering in rough terrain the AV need to consistently estimate the possible route without rolling over or encountering an impassable obstacle. Shay Rootman, Director of Business Development at Coganta, explains to Techtime that the main challenge is simulating the physic of the rough terrain driving: “In the field, there are no predefined driving outlines. One of the major physical aspects that have to be taken into account in rough terrain driving is the friction generated between ground and road conditions and between the autonomous vehicle – whether it is muddy, sandy or bumpy ground. The vehicles have to get pretty good estimation of the road conditions in order to adjust the speed and the angle of its approach and whether the obstacle in front is passable”.

In recent years, using unmanned military vehicles became more and more common in military forces around the world. It is mainly used for reconnaissance missions, mine clearance and lanes opening in situations where human’s presence might be dangerous. For example, the US Army develops autonomous transport trucks that can move independently in a convoy.

In addition, Israeli defense companies are also investing in developing autonomous vehicles in the recent years. The Israel Aerospace Industries (IAI) develops a variety of combat instruments such as autonomous robotic patrol for detecting and evacuating Improvised explosive devices (IEDs), and autonomous bulldozers for carrying out complex Combat Engineering missions in threatened areas. Elbit also started in recent years to develop unmanned vehicles to be used in routine security missions. In 2016, together with the IDF, the company has developed the “Border Keeper”, spanned along the Gaza Strip border and the border with Egypt.

“The military autonomous robotics area is boosting. When we started to work with the IDF and the Ministry of Defense, we noticed that simulators are required in AV world in the same way it required in the civil AV world”, says Rootman.

Coganta’s flagship product is a simulator system for training and testing autonomous vehicles. The simulator generates realistic imaging of complete cities – to include streets, trees, road obstacles, cars, human beings and more. It also generates information derived from various sensors such as cameras, infra-red systems and LiDAR. The system allows for generation of multiple scenarios and using it shortens the R&D and verification processes schedules and reduce the number of test drives. In recent years Coganta developed simulators for different types of AV’s such as agricultural tools, mining logistic tools and vehicles intended for rough terrain transportation.

Adasky to establish in-house manufacturing facility

The israeli start-up Adasky announced that it has secured a $15M investment from existing shareholders, the Japanese Kyocera and Sungwoo-Hitech from South-Korea, as part of a series B investment round. Adasky stated that the funds will support the commercialization of the thermal sensor it has developed for the automotive industry and other applications. Adasky intends to establish an in-house end-to-end manufacturing and assemnly line.

Adasky’s first product, Viper, is comprised of a high-performing thermal camera and state-of-the-art machine vision algorithms, together in one complete solution, that can be added to any autonomous vehicle to enable it to see better and analyze its surroundings. Viper passively collects FIR signals through detection of thermal energy radiated from objects and their body heat. AdaSky’s algorithms process the signals collected by the camera to provide accurate object detection and scene analysis, giving the vehicle the ability to precisely detect pedestrians at a few hundreds of meters, allowing more distance in which to react to driving decisions.

Viper is the first high-resolution, thermal camera for autonomous vehicles with minimal size, weight and power consumption and no moving parts – at a price suited for mass market. Viper generates a new layer of information, originated from a different band of the electromagnetic spectrum, significantly increasing performance for classification, identification, and detection of objects and of vehicle surroundings, both near and far range.

AV, Covid-19 detection and Smart City

Based on its core technology, Adasky has released three product lines: thermal sensor for ADAS and AV systems, a customized system recently developed to monitor body temprature of passersby in crowded spaces, to detect persons potentially infected with Covid-19, and a thermal system for smart city applications. In March, Adasky announced on a first agreement with an EV manufacturer to integrate its sensor in a Level 4 AV car model.