Driverless technology is rapidly being adopted by many organisations worldwide, and Baidu is leading the charge in China. Announced in late 2019, Baidu plans to operate a driverless robotaxis throughout 18 cities in China by 2020.
This paper explores some major challenges that must be addressed before Baidu can successfully deploy their robotaxis – including legal issues, operational challenges and public acceptance. Given these challenges, this paper will discuss potential implications of a successful rollout for Baidu and other businesses seeking to enter driverless mobility markets.
Baidu to operate fully driverless robotaxis in China
Baidu’s ambition to operate fully driverless robotaxis in China has been ambitious and groundbreaking, yet it is not without its challenges. From generating appropriate mapping data to dealing with the country’s complex regulatory environment, many roadblocks need to be surmounted for achieving the goal.
Let us examine these challenges more closely.
Regulatory
Regulatory approval for driverless cars is one of Baidu’s main challenges. The Chinese government has yet to fully regulate and permit the operation of driverless robotaxis on public roads. Currently, Baidu can only operate its robotaxis in certain cities where local rules allow it. For instance, Changsha is the first city where Baidu has obtained approval from authorities to operate its driverless robotaxis without safety drivers onboard.
Additionally, several other unresolved safety issues have yet to be addressed at a government level before finally allowing such trials to be carried out on public roads with various obstacles. The relevant regulatory bodies must also discuss and clarify safety protocols such as insurance requirements and speed limits before any wider adoption. Only after comprehensive regulatory clarification will companies like Baidu be able to confidently deploy their fleets in major cities across China.
Technical
Baidu to operate fully driverless robotaxis in China presents significant technical challenges in terms of the physical hardware and the software applied. The hardware related challenges include the ability of the car to detect and identify objects in its surroundings and act accordingly when faced with a sudden change or environment input. In addition, car percepcion, mapping and navigation, car drivetrain reliability and cost, being able to guarantee a safe solution are all pressing technical dilemmas Baidu must face.
The software related challenges must also be considered. Software engineering solutions such as various AI techniques must be utilised to allow for effective decision-making during driving, such as changing lanes, speed control and traffic light identification with just name a few. This ongoing process will require leveraging powerful deep learning techniques combined with knowledge bases from diverse sources such as high definition maps combined with real-time inputs from sensors across different vehicles and external sources such as police/traffic records. Effectively managing this data type is essential for distributing intelligence across multiple vehicles within a fleet or other elements within Baidu’s mobility ecosystem. This ultimately allows for safe driverless transportation on public roads and private zones.
Safety
Safety remains the main challenge for Baidu’s driverless robotaxis in China. As the vehicles carry passengers, they must have advanced safety technology and systems to ensure passenger safety. The vehicles must be able to sense and recognize their environment and navigate obstacles and hazards. They must also be able to detect traffic signs and other road information to stay within legal boundaries while driving.
Vehicle-to-vehicle communication is also key for safely operating these robots on public roads. It will enable them to detect other nearby vehicles, which can help them determine appropriate routes safely and avoid collisions. Furthermore, a comprehensive anti-hacking system is needed for intrusion prevention for Baidu’s solutions to remain secure.
Public Acceptance
The public acceptance and trust of driverless robotic taxis has been a major challenge for China’s leading tech giant Baidu in its effort to operate fully driverless robotaxis in China. However, as the service is relatively new, there is still some hesitation from the public as people are wary of the safety of driverless vehicles. In addition, cultural differences between cities may affect Baidu’s adoption rate and opportunities.
To address potential concerns from Chinese consumers, Baidu is taking several steps towards providing safe and comfortable user experiences. For example, the company has partnered with local governments to promote their service in different cities, provide extra safety measures and develop a feedback mechanism allowing passengers to regularly provide feedback and suggestions on their experience with the service. Furthermore, Baidu aims to continually refine its technology by gathering data from operating robotaxis and utilising simulated scenarios to simulate real-world conditions such as snow, ice or traffic jams that the cars may encounter.
Despite these efforts, however, various questions related to public acceptance still have yet to be thoroughly addressed – such as how will people react when they first see a robotic taxi on the roads? Additionally, further research into areas such as geographies inclined or disinclined towards adopting driverless cars and international trends needs to be conducted for Baidu’s service model to succeed.
Solutions
To make its fully driverless robotaxis a reality, Baidu has to overcome several challenges. This section will explore potential solutions to Baidu’s issues, including technological, legal, and safety considerations.
With the right steps, Baidu can be the first in the world to launch a fleet of driverless robotaxis in China.
Regulatory
The primary challenge to operating fully driverless robotaxis in China is regulatory. Currently, there are no regulations governing the operations of autonomous vehicles, and it is unclear if existing laws will have to be modified or developed to accommodate the autonomous technology. Additionally, strict cybersecurity standards must be met for vehicles such as Baidu’s robotaxis to operate safely and securely.
Also, local governments may impose particular zoning regulations on certain roads where robotaxi testing would occur. In addition, cities may develop their regulatory framework for autonomous vehicles that conflicts with regional or national ones. This could cause operational difficulties should driverless taxis need to switch between different jurisdictions.
To ensure its success, Baidu will likely have to cooperate with relevant agencies across various levels of government. This includes negotiating terms concerning safety protocols, liability issues related to accidents or other unforeseen events, and potentially working out financial arrangements between local government units and technology providers like Baidu. In addition, to further clarify local regulations and make a unified approach more feasible, autonomous vehicle companies like Baidu need to work with municipal authorities and governing bodies across China at all levels of power.
Technical
Baidu is leveraging its experience in driverless car technology to launch the world’s first commercial driverless robotaxi service in China. To make this happen, Baidu is facing several technological challenges. One of these is ensuring that their cars can navigate complex urban environments. This implies building a high level of understanding about the environment and developing an efficient perception-prediction-planning system which allows computers to recognize and plan around different traffic situations.
Another challenge is locally detecting changing environmental conditions and providing a safe navigation system while allowing cars to travel at high speeds. To achieve this, Baidu’s sensors must capture ample information such as surrounding vehicles, pedestrians and other non-static objects while driving at high speeds.
In addition, Baidu has been researching environment simulations and reinforcement learning initiatives aimed at simulating various real road scenarios where automated vehicles can not only be physically trained but also mentally trained so that they can deal with different ethical dilemmas related to vehicle safety or legal regulations without any human intervention. Further advancements include AI motion controllers for autonomous vehicles which act as a central nervous system for robotic cars. These controllers use massive amounts of data from numerous built-in sensors for decision making on traffic conditions.
Safety
The safety of Baidu’s driverless robotaxis is an important area of concern. To ensure the safety of passengers, the cars must be able to detect, identify, and respond to anything that could be a potential risk, such as changing road conditions or other vehicles on the path. As well as this, during peak times, it must be able to anticipate sudden influxes of demand.
To accomplish this level of safety Baidu’s driverless robotaxis rely on highly specialised sensors such as LIDAR (Light Detection And Ranging) and radar systems. These systems collect data and generate a 3-D model of its immediate environment. Image recognition software and AI algorithms are then used to interpret this data allowing it to recognize obstacles and autonomously adjust the speed or steering profile accordingly. This allows for smooth navigation even in complex city environments that may change suddenly due to traffic flows.
Alongside these in-car systems, Baidu is also preparing for large scale deployment over entire cities through their Apollo platform which includes a large-scale cloud system that centralises all driverless car data from individual rides in real time. This allows for large-scale troubleshooting and remote updates when necessary ensuring that their system maintains its high standards for safety at scale storage times throughout their entire deployment process over entire cities.
Public Acceptance
Public acceptance is among the major challenges facing the success of Baidu’s plans for driverless robotaxis in China. The Chinese public’s perception of self-driving cars may be divided into safety awareness, reliability and convenience.
Safety awareness refers to the public’s understanding that autonomous vehicles must operate safely and consistently at all times to avoid injuries or fatalities. To ensure this, transparency and education are essential, as local governments and citizens need to be aware of how these vehicles can be expected to perform in their environment. Additional policies may also be needed in areas with challenging or restricted infrastructure like pedestrian zones, construction sites, etc.
Reliability refers to the public’s trust on whether these driverless cars work properly as intended without any breakdown. This entails a robust platform for feedback from users who have experienced Baidu’s self-driving car operations directly every day, warning them if unexpected issues occur due to road conditions or technical errors so that preventive measures can be taken promptly. Moreover, features like remote monitoring should be integrated onto the platform so that any issues can be attended to accurately by other cars within a short period with minimal disruption of service availability.
Lastly, convenience refers to streamlining processes such as verifying user accounts quickly prior to embarking on a ride so that users do not get distracted from their initial purpose when using Baidu’s autonomous taxi service due to added hoops for onboarding new passengers or user payment issues. In addition, by leveraging collaborative technologies like digital wallets or account authentication systems such as Alipay during user verification process; more effective collaborations can take place between mobile operators and vehicles through secure networks in a shorter amount time than before which could provide users with an extra layer of security when using Baidu’s driverless cars.
