AUTONOMOUS CARS NEED TO OVERCOME MAJOR HURDLES BEFORE THEY BECOME MAINSTREAM
In an exclusive interaction with Dataquest, Ram Ramaseshan, Senior VP and Head, Automotive and Industrials BUs, Sasken Technologies, talks about the challenges faced by autonomous cars in India and how can India speed up towards Autonomous driving. Excerp
What is so special about your offerings and how does it help your clients? Sasken’s offerings help our customers accelerate time-to-market, enabling adoption of technologies demanded by consumers, and achieve cost advantage so that these solutions can be brought to emerging markets at competitive price points. Towards this, Sasken is focusing on the following offers:
Cockpit domain controller using Virtualization:
Increasing customer demand to bring consumer electronics features to passenger cars is leading to proliferation of ECUs and exponential increase in complexity of the car’s cockpit design. Number of ECUs in high-end cars has increased from close to 40 during late 2000 to 100+ in recent times. This has decelerated the rate of innovation and feature introduction, increased R&D costs and chances of failures for both Auto OEMs and Tier1s.
ECU consolidation is an emerging trend that allows multiple ECUs to be consolidated into a single SoC leading to cost advantage of high end cockpit Domain system.
ADAS validation
Sasken is building a simulation framework for validation of Advance Driver assist systems. Currently testing of vision-based ADAS systems requires huge amount of annotated video data for comprehensive scenario coverage. The generation of this video content for various geographies, terrain and weather conditions and traffic scenarios and the subsequent manual annotation of the same for algorithm validation is a pain point in the industry today
Sasken’s solution will enable generation of test video data based on a scenario description along with simulated sensor signals to test vision-based and sensor fusion algorithms against. The solution will also compare the algorithm output against the scenario description for accuracy and latency of detection. Sasken’s parameterized solution allows modelling of various drive scenarios with combination of various drive condition parameters (e.g., brightness, environmental conditions, pedestrians, obstacle, etc.) This helps create a rich test bed video that can be used for validation of the ADAS algorithms.
What are the challenges faced by autonomous car industry?
Autonomous cars have some major hurdles to overcome before they become part of the transportation landscape. There are following key challenges faced by autonomous car industry in today’s world: Cost: How to achieve economies of scale so that technology moves to mid tier segments where volumes are there
Standardization: Lack of interoperability for Radar, Lidar, Vision data in car network
Regulatory: Regulation for Autonomous cars are evolving. There is no clear standards for testing, certification of autonomous cars, safety regulations, definition on “Who is liable in case of a mishap…”
Validation: lengthy validation cycles. As per the report from Rand corporation titled, “How Many Miles of Driving Would It Take to Demonstrate Autonomous Vehicle Reliability?”, it would take 275 million miles/12.5 years of driving to demonstrate with 95% confidence that the failure rate is at most 1.09 fatalities/100 million miles. This is a long validation cycles and there is a need to adapt non-traditional ways to accelerate validation of autonomous vehicles.
According to you, by when can we expect autonomous cars in India? What security measures do companies take while building these cars? And how safe are these cars for the passengers?
Autonomous cars have multiple challenges in India as follows:
Infrastructure: The Road infrastructure is evolving and still no way comparable to what’s found in western world. Autonomous vehicle require high speed connectivity which is restricted to urban centres since the Quality of service in hinterland is still patchy
Economics: The primary driver for movement towards autonomous vehicles in west is towards Ride hailing and ride sharing applications. The cost of hiring a driver is expensive in these geographies. Contrast this with India It is Still in-expensive to hire a driver. The cost of the vehicles incorporating these technologies has to be competitive for adoption in high growth markets like India.
Network effect: Autonomous vehicle will be successful only if there a network of autonomous vehicles and an evolved eco-system that co-operatively drive.
Even advanced nations are at least 5 years from deploying autonomous vehicles commercially in some shape or form though there are many trials happening. In India the focus on autonomous cars will be less towards replacing labour but more towards assisting the driver in order to make roads safer.
In our view, we can expect autonomous vehicles can appear in India by 2025 that too at level 2 which corresponds to partial automation – the driving mode-specific execution by one or more driver assistance systems of both steering and acceleration/ deceleration using information about the driving environment and with the expectation that the human driver perform all remaining aspects of the dynamic driving task
Security is a major concern when it comes to autonomous vehicles. The surface of attack of autonomous vehicles has increased as the electronics components in the vehicle have increased. A Multilevel security measures along with consumer education is required to address the security issues.
According to the June 2015 early estimate of motor vehicles fatalities from U.S. National Highway Traffic Safety Administration (NHTSA), an estimated 32,675 people died in car crashes in 2014. The Eno Center for Transportation, a think tank, notes that “driver error is believed to be the main reason behind over 90 percent of all crashes” with drunk driving, distracted drivers, failure to remain in one lane and falling to yield the right of way the main causes. Because the majority of these accidents are caused by human error, self-driving cars could potentially reduce the rate of automobile-related deaths—and save the U.S. over $400 billion (2 percent of the U.S. GDP) in total annual costs of accidents.
So, Autonomous vehicle (vehicles with various degrees of autonomy) are relatively safer than manual driving. However, users need to get used to being driven by a computer and that change in mindset will take time.
How can India speed up towards Autonomous driving?
Government’s incentive for safer vehicles should be introduced so that it will focus on the autonomous driving. Possibly a certification mechanism in lines of BS for emission for safety would incentivise vehicle manufactures to incorporate some of these technologies.
Setting up of dedicated lanes/tracks where the vehicle can be tested – the smart city initiative of the Govt. of India would be a good precursor to this and the ‘smart cities’ would be good candidates for implementing infrastructure for autonomous vehicle testing. Business models such as ‘Can India be test bed for Asian/African market?’ would incentivize more private-public partnerships in this area.