Baidu is among the dozens of companies developing full-stack hardware and software solutions for self-driving vehicles, and it’s making steady progress toward its goal of full autonomy. To that end, the Beijing-based tech giant today unveiled Apollo Lite, a vision-based framework that leverages multiple cameras to achieve level 4 autonomous driving — that is, operation with limited human oversight under select conditions as defined by the Society of Automotive Engineers.

According to Baidu, Apollo Lite can process “vast” amounts of data generated by 10 cameras to detect objects up to 700 feet away while delivering real-time, 360-degree sensing of the environment. In tests on public roads in Beijing, vehicles relying on Apollo Lite managed to drive sans lidar sensors, which measure the distance to target objects by illuminating them with laser light and measuring the reflected pulses. (Lidar forms the foundation of a number of autonomous car systems, including those from Uber and Lyft.)

A strictly vision-based approach to autonomous driving is one advocated by Intel’s Mobileye, which is developing a custom accelerator processor chip — EyeQ5 — that offers 360-degree coverage courtesy proprietary algorithms, cameras, and ultrasonic. Similarly, driverless semi truck startup TuSimple says its camera-based technology (which employs lidar largely for redundancy) has a 1,000-meter detection range.

“A robust vision-based system is critical to the safety of autonomous driving, especially in high-speed situations where real-time sensing is critical,” said Apollo’s technical committee head Liang Wang. “Apollo Lite further strengthens Baidu’s sensor fusion based level 4 autonomous driving system that leverages the capabilities of camera, lidar, and radar to achieve the ‘true redundancy’ necessary for a safe and fully autonomous driving experience.”

Apollo Lite’s reveal comes after the January launch of Apollo 3.5, the latest version of Baidu’s Apollo open source driverless car platform, and Apollo Enterprise, a suite of customizable autonomous driving products for vehicle fleets. Alongside them, Baidu open-sourced software and reference hardware for its vehicle-to-everything (V2X) Apollo Intelligent Vehicle Infrastructure Cooperative System platform.

Apollo — which has grown in digital footprint considerably to 400,000 lines of code, or more than double the 165,000 lines of code the company announced in January 2018 — is now being tested, contributed to, or deployed by Intel, Nvidia, NXP, and over 130 global partners. (That’s an uptick from 116 partners in July 2018.) According to Baidu, the number of developers who’ve sourced Apollo’s code from the project’s Github repository stands at 12,000, a 20% increase from mid-2018.

Among the growing body of collaborators is California-based Udelv, which in January said it would deploy up to 100 autonomous delivery vehicles developed on Apollo 3.5 to U.S. cities in 2019, including the San Francisco Bay Area. Other Apollo adoptees include Volvo and Ford, both of which have committed to testing Apollo-powered self-driving vehicles on Chinese roads in 2019.

Baidu is also working with Chinese automobile manufacturers Chery, BYD Auto, and Great Wall, in addition to Hyundai Kia, Ford, and VM Motori, to roll out Apollo Enterprise solutions to cars. FAW Group, which develops the Hongqi line of luxury cars, is another close partner — it last year announced plans to launch a “limited number” of Apollo vehicles across China in the next year.

Baidu intends to achieve “full autonomy” on highways and urban roads by 2020, but it has competition in Beijing-based Pony.ai, which has raised $214 million in venture capital to date and which in early April launched a driverless taxi pilot in Guangzhou. Meanwhile, Alphabet’s Waymo says it’s now servicing over 1,000 riders with a fleet of more than 600 cars, and GM’s Cruise Automation has been testing an autonomous taxi service for employees in San Francisco and plans to launch a public service this year. Other rivals include Tesla, Zoox, Aptiv, May Mobility, Pronto.ai, Aurora, and Nuro.