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Announcements Mar 27, 2020 12:00 am EqualOcean

Tusimple and ZF will collaborate on mass production of driverless truck systems

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Jul 2, 2020 11:22 am ·

TuSimple Launches World's First Autonomous Freight Network

Based in the US and China, autonomous truck company TuSimple has initiated the world's first Autonomous Freight Network (AFN) in the US. The network will roll out in stages, consisting of digitally mapped truck routes, strategically located terminals and an autonomous operations monitoring system. The three major US logistics service providers, UPS, Penske and US Xpress, will each work with the startup to bring the project to life over three phases.  The company plans to first begin service between the cities of Phoenix, Tucson, El Paso, Dallas, Houston and San Antonio, from this year to 2021. Phase 2 kicks off in 2022 and runs until 2023 when it plans to expand its autonomous service coast-to-coast with a Los Angeles-to-Jacksonville route. Coming into 2024, the plan is to roll out phase 3 and provide autonomous shipping services nationwide in a total of 48 states.  Up until now, TuSimple has provided services to shippers and third-party logistics in seven fixed routes for four cities in the country. The company also intends to finish establishing a logistics transportation center in Dallas so that it can better serve clients located in the Texas Triangle city group. With the long-term view of implementing safe and effective driverless freight services in both China and America, TuSimple is leading the roll out and operation management of the first commercial self-driving truck fleet at scale.    

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Jun 23, 2020 11:00 am ·

TuSimple: Start with the Low-Hanging Fruit

► Though the market size is relatively small, with an explicit application scene, an affordable technology, and a sound regulatory system, the autonomous truck is very likely to realize commercialization sooner than other self-driving vehicles. ► TuSimple aims to bring the most cost-effective autonomous truck solution to both Chinese and American shippers and logistics companies. ► The company’s backbone technology is a proprietary automotive-grade camera system co-developed with Sony Semiconductor, which unlike Waymo’s lidar-focus solutions, utilized customized HD cameras that are much cheaper than lidar. ► The dual-site deployment and the obsession with cost reduction put the company one step ahead of the commercialization process. A big opportunity in a small market IHS Automotive, the American automotive research firm, divides application scenarios for autonomous vehicles into four categories: last-mile delivery, autonomous trucks, fixed-route and Robotaxi. While the four businesses have the same core technology, they are very different in the commercialization process. Robotaxi has been the hottest in recent years. Many giant companies like Google, GM Cruise and Baidu are implementing their own Robotaxi fleets. Autonomous trucks, on the other hand, doesn’t share the same buoyancy. The once ambitious self-driving truck start-ups, including Otto and Starsky Robotics, were either acquired or declared bankruptcy. Even those who survived still don’t get as much support as Robotaxi operators do. Take for example Pony.ai and TuSimple, the two self-driving solution developers who both run their vehicles in both China and the US. Only the former has implemented Robotaxi, while the latter focuses on freight. While Pony.ai is still in the early rounds, its total funding exceeded TuSimple’s twice over. The vast gap could be the result of the dominant potential demand Robotaxi owns. According to Mobileye’s research, the market size of Robotaxi will be worth more than USD 16 billion by 2030, while the number by then will be USD 1,550 million for self-driving trucks, according to MarketsandMarkets.  But the size isn’t everything. While the self-driving taxi is expected to save operation companies 70%-80% of profit currently taken by the human drivers, according to WeRide’s research, in this stage, with the immature technology and stubbornly high R&D costs, the goal is not likely to be achieved soon.  Autonomous trucks, on the other hand, require easier technology and less costs. Since the trucks transport goods rather than humans, and run on highways mostly, they have lower bars on sensitivity and speed control, and thus cost way less than developing a self-driving passenger vehicle. Besides, according to the US Department of Labor, the median annual income for heavy truck drivers in the US is USD 42,480, surpassing the median annual income of USD 37,690 for all occupations in the nation. Two drivers are required in one truck during one trip. The autonomous truck can at least take one driver off the truck to save 50% of the expense.  Furthermore, fatigue driving problems still exist in freight companies. A report from the US Department of Transportation showed that, in 2016, fatal accidents related to heavy trucks in the US numbered 3,864, which is 11.2% of all vehicle fatalities during the year. Autonomous technology, however, will enable trucks to run safely for 24 hours nonstop, even in extreme weather, which can highly promote the efficiency and safety of freight while saving money.   The lower cost and tangible implementation have given the autonomous truck a great opportunity to achieve commercialization sooner than Robotaxis will. TuSimple intends to further speed up the process Founded in 2016, TuSimple, the Beijing and San Diego co-based autonomous driving company has been focusing on bringing the most cost-effective L4 autonomous driving solution for long-haul heavy trucks in both China and America. And it is leading on that track. Over the last five years, the company has secured a total of USD 298 million fundraising led by renowned capitals including Sina, Mando Corporation, CDH Investments and UPS, with a post-money valuation of over USD 1 billion.  In contrast with Tesla, which has again delayed its self-driving trucks’ time of delivery to 2021, TuSimple is the first and only to operate a fleet of autonomous heavy-duty semi-trailer trucks on pre-mapped shipping routes. It has provided door-to-door services to a total of more than 20 clients in the US, including UPS Express, Amazon and United States Postal Service (USPS). Three shipping terminals are implemented in Arizona, Tucson and Texas with three more under construction. The company is also running road tests in Fujian and Shanghai, China, even though the commercialization may come later due to regulatory restrictions. The Sina-backed company claimed that revenue reached USD 1 million per month in the second half of 2019. Still, it would only become profitable when the safety officers are no longer needed, and the company intends to go public at that time. The secret is the obsession for cost control One of the most significant reasons for TuSimple’s fast commercialization is its obsession with cost control. As known to all, lidar is an indispensable part of autonomous vehicles due to its excellent performance in ranging and resolution. It is the best solution for driverless cars to cope with complex road conditions. But the sensor, once exclusive to the military, also costs a considerable amount. The US lidar giant Velodyne sells its 64-channel lidar units for USD 80,000 each.  Faced with such a huge expense, TuSimple began to reflect on whether it is really necessary. And apparently, it’s not. Since the trucks spend 90% of operating hours on highways where they should face obstacle-free movement, the company realized that its truck doesn’t have to be so sensitive, but it has to see further than lidar because its long body requires a much longer safe braking distance. Unable to find a system on the market that fits its needs, the company leaders decided to create one by themselves. Partnered with Sony Semiconductor, TuSimple successfully produced its proprietary automotive-grade camera and vision system that can see 1000 meters away at night and in extreme weather, in May 2019. And most importantly, since the system is mostly based on HD cameras, it costs much less than lidar-oriented solutions. This integrated system started mass production since this April, jointly with ZF, the renowned German automotive supplier.  In addition, the company also did a good job on energy saving. A joint study by TuSimple and the University of California, San Diego shows that automated trucks can save up to 10% on fuel consumption with TuSimple’s self-driving system, and estimates that, if all medium-and-heavy-duty trucks in the US were equipped with the same system, USD 10 billion annual fuel cost would be saved. With a sound technology foundation, the company also benefited a lot from its duel-site operation strategy. While their cross-city trunk line shipping has already been commercialized in the US, they are also actively road testing in harbor roads and logistics parks in Shanghai,  to collect as much operation data from different road conditions as possible. The system is now refined by nearly 2000-hour and 30,000 miles of real-world road tests.  

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Dec 31, 2019 12:27 am · Sina technology

Tusimple completed China's first highway L4 driverless queue test

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Dec 30, 2019 12:00 am · TuSimple

Tusimpled completed China's first test of a driverless expressway queue

Announcement: Click here
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Nov 29, 2019 07:18 pm ·

WIM Salon | Future Mobility:Transportation and Mobility Revolution in China

Autonomous driving is a disruptive innovation that seems certain to change the automobile industry sometime in the near future. For some time now, there has been talk about how the global autonomous driving market is poised to stimulate dynamic growth – while obliging carmakers, owners and governments to adapt. Normally, the autonomous vehicle – or as many call it, the self-driving car is a vehicle that is capable of sensing its environment and moving safely on its own. On Nov 24, EqualOcean welcomed autonomous driving industry insiders and investors to WIM Salon, where they discussed the possibility of future mobility. Panel discussion The ‘mobility 4.0 revolution’ as a part of the 4th industrial revolution, is changing the rules of the transportation game and modern life. EqualOcean has combed the most-funded autonomous driving startups in China and we found that in China, both startups and the capital market have shown strong interest in this field since 2014. The discussion at our WIM Salon started with: How do you see china's revolution in the transportation and mobility industry? Co-founder and CEO of Lidar developer ZVISION Technologies Co., Ltd (北京一径科技有限公司), Mr. Shituo (石拓), said that transportation and mobility in the past 5 years have been impressive. Infrastructure has also improved, he added, which has helped accelerate this technology on the market. ZVISION is a Beijing-based company aiming at producing high-accuracy and performance lidar that everyone can deploy. Currently, it has completed three rounds of financing and is seeking to expand in Jiangsu to achieve mass production next year. As the General Partner of Vertex Ventures (祥峰投资), which has focused on AI, transportation, mobility and circulation industries since 2009, Mr. Xia Zhijin (夏志进) shared his opinion as an investor: “Autonomous driving will take longer to implement and commercialize in China or the US, but we are already seeing some of the startups in China doing well by providing ADAS or DMS solutions to OEMs. Personally, I am very optimistic." He also strengthened that regional diversity, such as the Mobike or Ofo story, cannot be easily copied in Europe, which means startups should think about the special situations that need to be solved based on local demand. Co-founder of Evoke Motorcycles, Mr. Sebastian Chrobok, also said that the revolution has been huge. He has been in China since 2005 and seen a huge expansion in last-mile transport and cross-country transport. Evoke is an OEM that makes cutting-edge motorcycles powered by battery. They found that the most interesting revolution in China is the speed of charging station growth. Enabling a car to run with little or no human input is much more complex than most people imagine, since the three key processes of an unmanned vehicle require advanced technologies. So how AI chips and algorithm has changed the autonomous driving in many ways? Mr. Shi: "I believe finally the massive deployment of AI in autonomous driving would be edge computing, which means all AI chips are deployed in the vehicles. So we also need to reduce the power comsumption of AI chips as we increase the computing power. In this way, I think the AI chip complexity should be simplified, while providing more computing power at lower power consumption for the massive applications in autonomous driving.” Mr. Xia: "We need more powerful chips in order to process the data that are generated by all the sensors. Therefore you need those chips in the car, not the cloud. Cloud computing takes 100s of milliseconds to process the data and send it back to the car, which is bad. Therefore we need an embedded system in the car to make the computing process instant. In the future, V2X infrastructure will become very important for autonomous driving. Roadside cameras, lights, etc. will be fed to your car which can help make decision making in terms of speed." Mr. Sebastian strengthened the importance of hardware; the majority has to happen in the hardware. “Vehicles in the past were still Windows 95 under the hood, and were not designed for mass computation. What they wanted to do at Evoke was take the internal computations of the car and put it into a bike. Therefore, the chipsets were not designed for the motorcycle conditions they wanted to put them in." In terms of the hardware, what are the pros and cons of lidar and camera? Mr. Shi believed that ultimately LiDar will be the future, especially for a higher level of autonomous driving: "Two campaigns are ongoing right now (Waymo vs. Tesla). They make their decisions based on the level of their autonomous solutions. Waymo needs to ensure 100% safety for passengers while Tesla takes less responsibility.  Mr. Xia thought that startups may not be able to become big players in autonomous driving as OEMs but can become OEMs’ suppliers: "we need capable hardware before we can have a sound autonomous driving system. It could take longer to see the commercialization of autonomous driving and is still very premature. It might still need 5 years to be able to see commercialization.”   Mr. Sebastian was not going to speculate for LiDAR or Camera: "They do very basic sensor technology. Autonomous driving, as a motorcycle rider, is scary because of how they are programmed and we need to be more concerned about 'what if' situations, like the acceleration rate of the motorcycle vs the autonomous software. Therefore, the human factor is the hardest to understand for these data-driven tech companies." Trucking or Robotaxi, which one will be the first form of automotive autonomy to take off commercially? Trucking and passenger Robotaxi are the most popular landing scenes for autonomous vehicles now – e.g. Waymo, the self-driving unit of Alphabet, which is focusing on ride-hailing, and TuSimple (图森未来) which focuses on developing Level-4 (SAE-standard) commercial autonomous driving truck solutions. The question of which will arrive earlier has been widely discussed. Mr. Xia thought that Robotaxi is the better choice and more feasible within cities because trucks face very different conditions on both highways and cities in China. Mr.  Shi believed other scenarios will commercialize even faster, such as delivery, road cleaning and trucks in harbors – those applications may ramp up in 2 years. Mr. Sebastian thought it will depend on the environment; the first arrival will happen in well-prepared industries with demand behind them.  Speed up the process Through 2018, we have seen a huge acceleration in investment in autonomous vehicle technology. According to KPMG, Europe and North America are more ready for this new mobility. The regional difference is huge, which shows the importance of testing, validation and homologation. The arrival of fully autonomous cars might be some years in the future, but companies are already making huge bets on what the ultimate archetype will look like. To speed up, we need more substantial progress on fundamental fronts – in the legal framework, infrastructure, investment and consumer acceptance, which will speed up the arrival of autonomous technologies. Another way to speed up the process, according to Mckinsey, would be to make the shift to integrated system development. Instead of the current overwhelming focus on components with specific uses, the industry needs to pay more attention to developing actual systems, especially given the huge safety issues surrounding autonomous vehicles.  World Innovators Meet (WIM) 2019 will kick off the automotive salon on Sunday, November 24th, 2019. The WIM Salon will then end with a big year-end party on Dec. 22, 2019.  Don't miss out and be sure to scan the QR below for more information!   

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