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Nason

While it will be some time before fully autonomous vehicles are a common sight on public roads, the technology developed for these vehicles is already being used to make roads safer and in controlled environments. 

OEMs are installing LiDAR (light detection and ranging) systems in buses and delivery vehicles which have numerous blind spots due to their size and shape. With their limited visibility and manoeuvrability delivery vehicles as well as large road vehicles such as buses and semi-trailers are at high risk of causing road accidents or structural damage to buildings and infrastructure. Operators of large vehicles also often have to work in challenging weather and deal with various distractions that may temporarily affect their attention. 

Thanks to LiDAR technology, these daily challenges mean that safety for all commercial and delivery vehicles will be enhanced by features such as collision avoidance, turn assist, and blind spot monitoring. LiDAR also opens the way for the use of autonomous delivery vehicles and truck platooning in order to increase efficiency and reduce transport costs.  

LiDAR is also being used to guide autonomous shuttles in controlled environments such as warehouses, airports and campuses. In order to meet this growing demand, OEMs need reliable access to volumes of automotive grade solid state LiDARs (SSLs).  

Canadian-based LeddarTech address this need through its auto and mobility LiDAR platform which provides Tier 1 and automotive system integrators, the technology required to develop and produced tailored SSL solutions to specific OEMS requirements. LeddarTech’s technology has been already been proven in the field through its use in autonomous shuttles, delivery vehicles and robot taxis, where the solid-state LiDAR sensors improve spatial awareness and obstacle detection up to 360 degrees around the vehicle.  Further technology includes a 3D solid state cocoon flash LiDAR with 180-degree field of view which provides reliable detection of pedestrians, cyclists and other obstacles in the vehicle’s vicinity and it ideal for use in perception platforms that are meant to ensure the safety and protection of vulnerable road users. It provides complete blind spot coverage with no dead zones in the illuminated field of view.  

Will the advent of connected autonomous vehicles take longer than predicted? 

2019 was the year of “reality check” and based on reports, and press articles and the automotive industry, it has become obvious that putting fully autonomous cars on the road is proving to be a lot more challenging than initially expected and forecasted. This is especially true for vehicle operating outside of geofenced areas. 

Many key players in the automotive sectors have recently announced delays or pushbacks in their initiatives. The industry seems to now acknowledge that the leap from level 3 to level 4/5 is orders of magnitude in complexity and will take a few more years than anticipated. Hence, while we continue to see sustained R&D activities in passenger cars to improve and optimise the capabilities of autonomous vehicle platforms, the focus has been shifted to commercial implementation of ADAS in level 2-2+ and level 3 semi-autonomous capabilities, where we should see significantly more traction in the short term. The mobility market is where we should first see implementation of level 4-5 in controlled use cases. 

What advantages does LiDAR have over technology such as radar, video cameras and ultrasonic sensors for autonomous vehicles? 

All these detection technologies prove useful in specific applications but they also have well-known limitations. Sonar for example is low cost, but has limited range and low resolution. Radar has issues detecting certain materials, or surfaces and does not like static objects. Cameras don’t provide range information and are significantly impacted by weather or lightning. 

LiDARs are strong at accurately measuring distances over long ranges providing valuable information. LiDAR emits its own signal and functions independently of the ambient light. It can therefore achieve fantastic results day and night without any loss of performance. 

The vast amount of data generated by LiDAR results in accurate 3D construction of a scene. It creates a precise three-dimensional mapping of the environment. Hence this is why you find LiDAR in the vast majority of AV platforms under development today. 

How are LiDAR technologies changing to overcome challenges such as being unable to perform optimally in bad weather? 

Inclement weather conditions like snow, rain or fog change the refraction index of the transmission of medium and indeed reduce the effective range of a LiDAR sensor. Radar’s high immunity to weather conditions is one of the key reasons why they are also incorporated in the design of most automotive sensor suites. That being said, the impacts of weather conditions on LiDAR can be significantly mitigated through the use of advanced signal post-processing and noise filtering algorithms.  

What role does LiDAR play in the public transportation systems of the future? 

LiDARs are already being deployed in applications that contribute to making public transportation safer. For example, public transit companies integrate LiDARs on buses in order to reduce driver blind spots. Most autonomous shuttle manufacturers use LiDARS for geo-positioning as well as for the protection of vulnerable road users around the vehicle. By improving detection and ranging capabilities of these autonomous vehicles, LiDAR plays a key role in enabling and accelerating the deployment of commercially viable and safe automated public transit in our cities.