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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.