Those in the know have long compared the effect to driving on snow. But could the humble leaf really be as slippery as the white stuff? A group of Ford engineers have come up with an answer – after conducting a unique experiment in order to find out.
Getting the data for the snow was the easy part. This was sourced from vehicle testing in snowy Scandinavian locations. But there was no research to show how slippery leaves were. To fix that, the team gathered bags of leaves and used them to cover the test track at the company’s proving ground in Belgium. They then called in the help of a friction-testing device that identifies how slippery surfaces are by rolling over them.
After testing they did indeed find that, in certain situations, the leaves were as slippery as snow.
“It was fun to conduct the experiment but there was a serious point,” said Eddy Kasteel, development engineer, Ford of Europe. “Most people know to slow down and drive more cautiously for snow. But far fewer of us give the same respect to roads covered in leaves – that can be just as slippery.”
Slipperiness is measured in units called µ. The more slippery the surface the lower the number. In testing, and at their most slippery, the leaves measured a µ level between 0.3 and 0.4. Typically, the same µ levels observed on snow surfaces
The same engineers helped to develop “Slippery Mode” for the all-new Ford Focus Active crossover that goes on sale next month. Designed to improve traction on surfaces including ice snow and wet leaves, the system makes rapid readjustments to stability systems, acceleration and braking to help prevent the car from skidding, swerving or deviating from its intended path.
Two-thirds of adults ready for cars that drive themselves
The latest Looking Further with Ford Trends Report reveals that behaviour is changing across key areas of our lives
Self-driving cars are a hot topic today, but if you had to choose, would you rather your children ride in an autonomous vehicle or drive with a stranger? You may be surprised to learn that 67 per cent of adults globally would opt for the self-driving car.
That insight is one of many revealed in the 2019 Looking Further with Ford Trend Report, released last week. The report takes a deep look into the drivers of behavioural change, specifically uncovering the dynamic relationships consumers have with the shifting landscape of technology.
Change is not always easy, particularly when it is driven by forces beyond our control. In a global survey of 14 countries, Ford’s research revealed that 87 per cent of adults believe technology is the biggest driver of change. And while 79 per cent of adults maintain that technology is a force for good, there are large segments of the population that have significant concerns. Some are afraid of artificial intelligence (AI). Others fear the impact of technology on our emotional wellbeing.
“Individually and collectively, these behavioural changes can take us from feeling helpless to feeling empowered, and unleash a world of wonder, hope and progress,” says Kuda Takura, smart mobility specialist at Ford Motor Company of Southern Africa. “At Ford we are deeply focused on human-centric design and are committed to finding mobility solutions that help improve the lives of consumers and their communities. In the context of change, we have to protect what we consider most valuable – having a trusted relationship with our customers. So, we are always deliberate and thoughtful about how we navigate change.”
Key insights from Ford’s 7th annual Trends Report:
Almost half of people around the world believe that fear drives change
Seven in 10 say that they are energised by change
87 per cent agree that technology is the biggest driver of today’s change
Eight in 10 citizens believe that technology is a force for good
45 per cent of adults globally report that they envy people who can disconnect from their devices
Seven out of 10 consumers agree that we should have a mandatory time-out from our devices
Click here to read more about the seven trends for 2019.
At last, cars talk to traffic lights to catch ‘green wave’
By ANDRE HAINZLMAIER, head of development of apps, connected services and smart city at Audi.
Stop-and-go traffic in cities is annoying. By contrast, we are pleased when we have a “green wave” – but we catch them far too seldom, unfortunately. With the Traffic Light Information function, drivers are more in control. They drive more efficiently and are more relaxed because they know 250 meters ahead of a traffic light whether they will catch it on green. In the future, anonymized data from our cars can help to switch traffic lights in cities to better phases and to optimise the traffic flow.
In the USA, Audi customers have been using the “Time-to-Green” function for two years: if the driver will reach the lights on red, a countdown in the Audi virtual cockpit or head-up display counts the seconds to the next green phase. This service is now available at more than 5,000 intersections in the USA, for example in cities like Denver, Houston, Las Vegas, Los Angeles, Portland and Washington D.C. In the US capital alone, about 1,000 intersections are linked to the Traffic Light Information function.
Since February, Audi has offered a further function in North America. The purpose of this is especially to enable driving on the “green wave”. “Green Light Optimized Speed Advisory” (GLOSA) shows to the driver in the ideal speed for reaching the next traffic light on green.
Both Time-to-Green and GLOSA will be activated for the start of operation in Ingolstadt in selected Audi models. These include all Audi e-tron models and the A4, A6, A7, A8, Q3, Q7 and Q8 to be produced from mid-July (“model year 2020”). The prerequisite is the “Audi connect Navigation & Infotainment” package and the optional “camera-based traffic sign recognition”.
Why is this function becoming available in Europe two years later than in the USA?
The challenges for the serial introduction of the service are much greater here than, for example, in the USA, where urban traffic light systems were planned over a large area and uniformly. In Europe, by contrast, the traffic infrastructure has developed more locally and decentrally – with a great variety of traffic technology. How quickly other cities are connected to this technology depends above all on whether data standards and interfaces get established and cities digitalise their traffic lights.
On this project, Audi is working with Traffic Technology Services (TTS). TTS prepares the raw data from city traffic management centres and transmits them to the Audi servers. From here, the information reaches the car via a fast Internet connection.
Audi is working to offer Traffic Light Information in further cities in Germany, Europe, Canada and the USA in the coming years. In the large east Chinese city of Wuxi, Audi and partners are testing networks between cars and traffic light systems in the context of a development project.
In future, Audi customers may be able to benefit from additional functions, for example when “green waves” are incorporated into the ideal route planning. It is also conceivable that Audi e-tron models, when cruising up to a red traffic light, will make increased used of braking energy in order to charge their batteries. Coupled with predictive adaptive cruise control (pACC), the cars could even brake automatically at red lights.
In the long term, urban traffic will benefit. When cars send anonymised data to the city, for example, traffic signals could operate more flexibly. Every driver knows the following situation: in the evening you wait at a red light – while no other car is to be seen far and wide. Networked traffic lights would then react according to demand. Drivers of other automotive brands will also profit from the development work that Audi is carrying out with Traffic Light Information – good news for cities, which are dependent on the anonymised data of large fleets to achieve the most efficient traffic management.
In future, V2I technologies like Traffic Light Information will facilitate automated driving.
A city is one of the most complex environments for an autonomous car. Nevertheless, the vehicle has to be able to handle the situation, even in rain and snow. Data exchange with the traffic infrastructure can be highly relevant here.