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Autonomous driving in SA faces pedestrian, road sign challenges, finds Merc

Self-driving mode on the Mercedes-Benz Inteliigent Drive S-Class with Jochen Haab. (See second self-parking video as well)

Self-parking mode on the Mercedes-Benz Inteliigent Drive S-Class with Jochen Haab (See second self-parking video as well)

15th January 2018

By: Irma Venter

Creamer Media Senior Deputy Editor

     

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It may surprise the taxi haters, but South Africa is not the most challenging country to sit behind the wheel of a vehicle in self-driving mode. The winner is China, with its sometimes erratic cyclists, lack of lane markings and confusing traffic signals.

Mercedes-Benz at the end of last year visited Cape Town as the fourth stop in its five-continent Intelligent World Drive tour, aimed at gathering insight into real-life traffic conditions and road user practices in different countries.

The goal is to validate and advance the German car maker’s driver assistance systems, as part of the greater effort to develop a fully self-driving vehicle.

The test vehicle, based on the S-Class, is equipped with a number of automated driving technologies – which means it can do a fair amount of self-driving.

The vehicle has been tested in Europe, Australia, China, the US and South Africa.

A number of self-driving, or autonomous vehicles from various manufacturers are already being tested worldwide, with the commercial rollout of the technology expected in the next five to ten years.

Daimler autonomous driving and intelligent drive spokesperson Bernard Weidemann believes the world will see the first use of fully autonomous vehicles within the next five years, with mobility solution companies such as Uber, for example.

Mercedes-Benz is a Daimler group company.

Learning Curve
The S-Class tasked with travelling the five continents has thee radar sensors, one stereo camera, 12 ultrasound sensors and four optical cameras.

Equipping a highly automated vehicle to operate in any country is about ‘teaching’ that vehicle about general road behaviour and obstacles, as well as country-specific road behaviour and obstacles, explains Jochen Haab, Mercedes-Benz manager of concept and field validation of driver assistance systems.

Mercedes-Benz engineers could programme the vehicle to obey the rules of the road, but that would be insufficient to deal with the reality of everyday driving.

In Australia the Intelligent World-Drive encountered the vehicle’s need to read road signs warning of animals in the area, and to identify these animals should they appear near the vehicle. This is no one-size-fits-all lesson, as animals come in different shapes and sizes, such as wombats, kangeroos, hippos or kudus.

In South Africa the team was confronted with a turtle crossing the road. While the vehicle could ‘see’ the animal as an object, it could not grasp its identity. Does it need to stop, swerve, or measure if it could ride over it safely?

Human behaviour also differs in each country. In China the team experienced some aggressive tailgating, while South Africans are prone to some harsh cut-in behaviour.

While automated vehicle systems should, technically, regard traffic laws as sacrosanct, overtaking another vehicle safely sometimes requires breaking the speed limit. Also, road works sometimes demand of the driver to cross a solid line.

The reality of these situations means that automated vehicles still have a lot to learn.

“We have to teach the car tolerance and intuition,” says Haab. “The autonomous car must not be one that drives rudely.”

SA Realities
South Africa’s traffic and road conditions presented its own particular challenges to the Mercedes-Benz team, most notably different road surfaces, wildlife on rural roads and pedestrian behaviour.

Pedestrians presented a great challenge, especially along highways. In Europe, a pedestrian on a highway would make the evening news, while it is a common occurrence in South Africa, says Weidemann.

There are high volumes of pedestrians on the road, whether in the country or in the city. Sometimes they walk on the street and often they cross lanes “completely unexpectedly”.

In 2016 some 5 410 pedestrians died in road traffic accidents in South Africa. That figure represents 38% of all road traffic deaths in the country.

This pedestrian behaviour calls for an additional, increased level of awareness, thus, also poses particular challenges for the sensor systems of automated and autonomous vehicles.

Cameras and radar systems have to detect passers-by and interpret their movement correctly so that the vehicle can react within milliseconds.

Other region-specific challenges include traffic signs which are only found in the 15 member States of the Southern African Development Community, such as South Africa, Namibia, Botswana or the Seychelles.

For example, the no stopping sign shows a crossed-out letter 'S' in a red circle, while the sign for no entry is made up of two black horizontal bars in a red circle.

In addition, the road traffic signs in South Africa are often incomplete. Intersections where you have to stop are not always indicated by a stop sign – in some cases they only have wide, white lines across the road surface.

Also, speed bumps are often not preceded by warning signs, or they are positioned so close to the obstacle that the vehicle has insufficient time to react.

The lack of signs presents a major challenge for the performance of the camera and radar systems, as well as the quality of digital maps, which enable some automated driving functions.

Red lines on the perimeter of the road, or yellow zig-zag lines, are also uncommon elsewhere in the world.

Red lines create difficulty for the vehicle’s cameras, as their contrast with the tar surface of the road is not as sharp as that of white or yellow lines.

Biggest Challenges
While Mercedes-Benz can ‘teach’ driver assistance systems or fully autonomous vehicles as much as possible of the real world, a number of challenges remain.

The one is that the world is highly unpredictable, as human drivers learn every day.

“It is difficult to put human behaviour in code,” says Haab.

Another challenge is not that people don’t trust automated driving systems, but rather that they trust them too much, he adds.

“They don’t know the limits of the system.”

Weidemann also emphasises the need for the vehicle to collect the right information, and to alert the driver only to those dangers essential to his or her well-being.

“It’s like the lion that roared too much. We can’t warn the driver about every pedestrian otherwise he’ll get annoyed. Think of Google. You type in a search and Google gives you the most relevant information, not everything on the subject. We need to be clever in what information we give to the car and the driver.”

 

Edited by Creamer Media Reporter

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