How to reduce congestion in cities

Smart traffic with the help of LiDAR technology

If you have ever driven along the Mittler Ring in Munich during rush hour, you will be aware of the enormous problem facing urban spaces throughout the world: traffic jams as far as the eye can see. On average, Germans were stuck in traffic for 120 hours – and, in Munich, for as long as 140 hours – in 2018. For individuals, these lost hours are annoying and impair their quality of life. For the state, though, these figures mean considerable economic effects. Traffic jams cost several billion euros per year because employees are stuck in traffic jams instead of being productive, and goods are on the road instead of on the shelf. In addition, there is a high level of environmental pollution due to increased fuel consumption and thus increased CO2 emissions.

Traffic is a problem, especially in cities. However, new technologies can and will make an important contribution to solving this problem.

 

Knowing more than the individual road user

How does congestion develop? Traffic jams are a distributed problem caused by the fact that all road users drive their vehicles in a way that is optimized for themselves. For example, they may catch up with the car in front or change lanes – whatever appears to them to be the best way to get to their destination faster. Since the individual road users cannot see how they influence the traffic around them, they cannot act accordingly. Drivers themselves are not aware that a traffic jam can be triggered three kilometers behind the vehicle that is stopping.

This is the point at which we have to start: the behavior of individuals must be counterbalanced in traffic planning and control so as to optimize the flow of traffic. The solution is to regulate traffic in a pre-emptive and distributed manner, i.e. with anticipation and going beyond the individual road user. This requires a complete overview of the traffic situation.

Gaining a complete overview with GPS, cameras and sensors

Various technologies can be used to achieve this complete overview. However, if you take a closer look at them, you will see that some of them are less suitable for equipping a smart infrastructure:

GPS:

GPS provides valuable data by tracking the movements of road users. This technology can therefore be used to report traffic jams quite reliably. The ability to take pedestrians and cyclists into account, however, exceeds the capabilities of GPS.

Instead of collecting information with the help of road users, as in the case with GPS, sensors and cameras can be integrated into the infrastructure to monitor the traffic situation. This requires that the devices be installed in traffic lights, street lamps or traffic signs so that they can collect information about their surroundings from there. Here, too, clear advantages and disadvantages of the possible technologies can be identified:

Cameras:

Cameras, for example, are able to record color images, but they cannot provide the same quality when used in darkness. Additionally, they only capture the data in 2D, whereas 3D data is needed to reliably detect objects and determine distances. They also quickly find themselves in a grey area with regard to data protection when recording and storing personal data.

Radar:

Radar is mainly used for speed monitoring, but could also be used for traffic monitoring. However, radar only provides a very crude picture: although the technology identifies objects, it is not able to classify them due to the lack of detail. Radar data, for example, cannot reliably distinguish between pedestrians and cyclists.

LiDAR captures road users precisely and anonymously

Laser-based LiDAR technology is a technology that can distinguish very precisely between all road users. The sensors provide detailed and reliable 3D information that makes it easy to distinguish between different road users. Although it is possible to recognize whether the 3D point cloud is a pedestrian or a cyclist, the identification of individuals is not possible, which protects the privacy of road users.

In addition, LiDAR sensors are able to reliably collect information even in difficult weather and lighting conditions. Darkness, dust or fog do not bother the technology. In addition to position and object information, the sensors also record speeds, which can be helpful in analyzing traffic flow or the causes of traffic jams.

Solid-state as a solution for today’s LiDAR problems

High-tech sensors are currently used primarily in the field of autonomous driving, but they face a major challenge: the LiDAR sensors that are available today are expensive and prone to faults. Solid-state technology solves these problems. In this type of LiDAR, the moving parts that deflect the laser to scan the environment are replaced by maintenance-free components. The sensors are therefore much more robust and also less expensive – and hence ideally suited to a wide range of applications in the infrastructure.

Traffic information enables practical measures

The LiDAR sensors installed in the infrastructure provide information about the current traffic situation in real time: Is the traffic flowing or stagnating? Is there an accident or a construction site? Are there many pedestrians at the traffic lights or at the crosswalk?

With this information, the following measures can be taken in real time and adapted to the traffic in order to optimize the traffic flow:

  • Adaptation of traffic light phases
  • Adaptation of speed limits
  • Displaying traffic jam warnings
  • Showing redirection recommendations
  • Identification and reconstruction of hazardous locations

In future we will even go one step further: autonomous vehicles will then use the information to dynamically adapt their schedules and routes to the traffic situation.

Cities that revolve around people again

In many cities, the influences of the paradigm of the “car-friendly city” can still be clearly seen today: urban planning is aligned to the goal of unhindered traffic flow by car. Even though this model has been subject to strong criticism for several decades now, many traffic concepts in cities are still oriented towards motorized individual transport.

In recent years, this approach has been increasingly replaced by a demand for car-free zones or even entire city centers. These demands clearly show that urban and traffic planning must once again be more about people. The needs of residents, commuters and all other road users must be centermost, which means making mobility as safe and uncomplicated as possible. Pedestrian crossings must be designed to be safer; turning accidents must be avoided; sufficient space must be created for cyclists – the list of measures is long. Intelligent traffic control with the help of a smart infrastructure makes this possible – and LiDAR technology is at the heart of it.

Blickfeld presents new long-range LiDAR

Cube Range detects obstacles at a distance of up to 250 meters

Munich – Blickfeld, a leading provider of solid-state LiDAR technology, is introducing the latest member of its product family. With the Cube Range, the Munich-based company is launching a MEMS-based LiDAR sensor for extended detection of objects at a distance of up to 250 meters. In combination with the well-established Blickfeld Cube, Blickfeld now offers a full LiDAR suite for autonomous vehicles.

The Cube Range sensor was designed as a robust and powerful 3D solid-state LiDAR for the mass market. It has a range of 150 meters with 10 percent reflection; a range of up to 250 meters is easily achievable with higher reflection. In addition, the Cube Range exhibits an impressive resolution of 0.18°.

The proven Blickfeld technology allows cost-effective and scalable production of the sensor. The core of this technology is a proprietary silicon MEMS mirror embedded in a coaxial structure that is based on commercial standard components.

Reliable and detailed collection of 3D data during a highway drive

With its high resolution and long range, the Cube Range addresses the need for moving objects to be detected with high accuracy. By precisely generating a dense 3D point cloud and then evaluating it in real time using Blickfeld’s software stack, the company makes an important contribution to enabling autonomous driving. The Blickfeld technology ensures precise environmental detection even in darkness, fog or strong sunlight.

“With the Cube Range, we have developed an extraordinary LiDAR which, thanks to its outstanding properties, is particularly suitable for driving at highway speed because it provides reliable environmental images even under these conditions,” says Dr. Mathias Müller, co-founder and CEO of Blickfeld. “Autonomous vehicles are just one application example for our LiDAR sensors. We also see a great demand in other areas, such as security, agriculture and smart city environments. Therefore, we are all the more pleased that the Cube Range has already proven itself successfully in various projects and will be available for purchase in 2019.”

 

 

IAA review: An industry on the road to change

There was much talk, writing and discussion about this year’s IAA. There were lively and excited debates about a necessary change of the trade fair format as well as the entire industry. Blickfeld was on site with two booths. We would like to share our firsthand experience: here’s our impression.

One major novelty at this year’s IAA, was the New Mobility World (NMW) Conference, a three-day conference within the framework of the trade fair in which speakers from a wide variety of companies and organizations discussed current mobility topics. Both, the speakers and the dominant topics of the conference show that the mobility industry is changing. Ola Källenius, the new chairman of Daimler, joined Ginni Rometty, CEO of IBM, on stage, and names such as Qualcomm and Facebook were among the sponsors of the conference – this clearly shows that the IAA no longer only belongs to car manufacturers and suppliers. Topics such as connectivity, mobility-as-a-service and autonomous vehicles are gaining importance with more and more IT companies, start-ups and providers of new mobility presenting at booths and podiums.

The industry is looking at new and alternative mobility concepts. While the OEMs focused on electromobility at their booths, Tier 1 suppliers often designed their IAA presence around autonomous applications. One of these suppliers was Webasto, who unveiled their new “Roof Sensor Module”. The module is designed to smoothly integrate sensors in autonomous vehicles without bulky constructions on the roof of the cars. The module is capable to include the Blickfeld Cube, which is why Blickfeld sensors could not only to be found at the company’s own booths, but also at the Webasto booth.

The shift in the industry is important and necessary, as demonstrated by the protesters on the doorstep of the IAA. The industry will have to reorient to some extent. In the long term, autonomous driving will contribute to reducing vehicle emissions worldwide – the importance of this development was accentuated by Waymo CEO John Krafcik opening the show together with Angela Merkel. The Google sister Waymo drives many thousands of testing miles autonomously in California every month and is regarded a pioneer among the manufacturers of autonomous vehicles.

In the NMW exhibition area, Blickfeld was in good company: Start-ups in the fields of HD mapping, ultrasonic sensor technology, connected car, shared mobility, smart charging and many more were exhibiting. Here, too, there was a clear focus on autonomous driving.

The future of autonomous driving was further discussed by Blickfeld founder, Dr. Florian Petit, with his lecture on when self-driving will be the new normal on the NMW Conference stage. Florian took a critical look at the status quo in the areas of technology as well as legislation and customer acceptance of autonomous applications and gave an outlook on the developments of the upcoming years.