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Ford, MIT, research pedestrians

Ford Motor Company and the Massachusetts Institute of Technology are collaborating on a new research project that measures how pedestrians move in urban areas to improve certain public transportation services, such as ride-hailing and point-to-point shuttles services.

The project will introduce a fleet of on-demand electric vehicle shuttles that operate on both city roads and campus walkways on the university’s Cambridge, Massachusetts, campus. The vehicles use LiDAR sensors and cameras to measure pedestrian flow, which ultimately helps predict demand for the shuttles. This, in turn, helps researchers and drivers route shuttles toward areas with the highest demand to better accommodate riders.

“The onboard sensors and cameras gather pedestrian data to estimate the flow of foot traffic,” said Ken Washington, vice president of Research and Advanced Engineering at Ford. “This helps us develop efficient algorithms that bring together relevant data. It improves mobility-on-demand services, and aids ongoing pedestrian detection and mapping efforts for autonomous vehicle research.”

Using a high-tech lab

The MIT research is being conducted by the Aeronautics and Astronautics Department’s Aerospace Controls Lab. ACL researches topics related to autonomous systems and control design for aircraft, spacecraft, and ground vehicles. Theoretical and experimental research is pursued in such areas as estimation and navigation, planning and learning under uncertainty, and vehicle autonomy.

“Through the mobility-on-demand system being developed for MIT’s campus, ACL can investigate new planning and prediction algorithms in a complex, but controlled, environment, while simultaneously providing a testbed framework for researchers and a service to the MIT community,” said ACL director Professor Jonathan How.

Hailing a ride

Ford and MIT researchers plan to introduce the service to a group of students and faculty beginning in September. This group will use a mobile application to hail one of three electric urban vehicles to their location and request to be dropped off at another destination on campus.

The electric vehicles are small enough to be able to navigate the campus’s sidewalks, while still leaving plenty of room for traditional pedestrian traffic. Each is outfitted with weatherproof enclosures that shield out inclement weather – a feature particularly useful for New England’s punishing winters.

After requesting the shuttles via a smartphone app, MIT students and faculty won’t be waiting long for their ride to arrive.

During the past five months, Ford and MIT have used LiDAR sensors and cameras mounted to the vehicles to document pedestrian flow between different points on campus. LiDAR is the most efficient way to detect and localise objects from the environment surrounding the shuttles. The technology is much more accurate than GPS, emitting short pulses of laser light to precisely pinpoint the vehicles’ location on a map and detect the movement of nearby pedestrians and objects.

Using this data, researchers study the overall pattern of how pedestrian traffic moves across campus, which helps the researchers anticipate where the most demand for the shuttles will be at any given moment. This allows the shuttles to be carefully pre-positioned and routed to serve the MIT population as efficiently as possible.

Researchers also take into account other factors that affect pedestrian movement on MIT’s campus, such as varying weather conditions, class schedules, and the dynamic habits of students and professors across different semesters.

Applying learnings to mobility services and beyond

This collaboration further enhances Ford’s Dynamic Shuttle project, which provides point-to-point shuttle rides to employees requesting rides using a mobile application on its Dearborn, Michigan, campus. The collaboration advances the ride-hailing concept to new heights by examining the movement of pedestrians to predict demand and reduce wait times for shuttles.

What’s more, the algorithms and methods learned when navigating densely crowded pedestrian areas using LiDAR will also strengthen Ford’s autonomous and driver assist technologies as the company continues develop autonomous vehicles.

The project is one of more than 30 mobility solutions university research projects between Ford and universities in the U.S., Germany and China aimed at helping the company and academic world better understand how to improve mobility for millions of people globally.

University research partnerships are an important part of Ford’s broader effort to change the way the world moves. Ford Smart Mobility is the company’s plan to be a leader in connectivity, mobility, autonomous vehicles, the customer experience, and data and analytics.

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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.

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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. 

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