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Pilot project displays Potential of LiDAR data for a better traffic data basis
2022.03.11
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Published on January 14, 2022

LiDAR Perspective - Intersection Ludwigstrasse / Corner of Oskar-von-Miller Ring/Von der Tann- Strasse , Munich

For sustainable and safe Mobility concepts of tomorrow is the digitization of the traffic infrastructure as one extensive traffic data basis essential . Current existing Data acquisition systems , such as the induction loop and thermal imager , point partly still _ significant defects in terms of measurement accuracy , detection capacity at non-motorized road users , as well as in the real-time capability of the data . in the framework of the Munich Innovation Prize 2021 , the city of Munich is jointly investigating with this year's Award winner LiangDao the potential of the sensor technology LiDAR (Light Detection and Ranging) for a better Traffic data basis of the city.

LiDAR based sensor system to the collection of traffic data

LiangDao develops at the interface innovative system solutions for smart cities and future mobility , for real-time object recognition and optimization of traffic flow . That from company developed LiDAR- based sensor system with AI -supported software, is capable of road traffic and environmental data with one Range of up to 70 meters to capture . With the high-precision capture even at night and when it rains, the system can not only traffic volumes after different Road users (motor, bicycle , pedestrian ) and vehicle type information (truck, car, van) reliably generate and classify but _ even data protection compliant and based on AI, the traffic situation in real time map . The system can also the direction , the trajectory and the speed of the modes of transport register .

Innovative counting stations for the inner city area with Focus on walking and cycling searched

The focus of traffic data collection is in Munich currently still in the Outskirts of town on freeways and on heavily trafficked roads streets . There are the majority of the total over 2000 counting detectors installed which are able _ Cross- sectional - or node counts to be carried out according to the “8+1” vehicle categories [1] of the Federal Roads Office ( BASt ) . They offer the present Data basis for the documentation and analysis of the traffic development , as well as for the traffic and development planning .

More into focus target at future Traffic data collection and strategies for city planning development of pedestrian and bicycle traffic back . With that in the future more holistic picture of urban transport mapped and the information basis improved will the city of Munich plans to implement it news Sensor technology and the installation of innovative counting methods even in the inner city area .

In seven steps from the system build to the data acquisition

After first the use case with colleagues from the mobility department _ identified and the framework of the crossings analyzed were , took place on November 26 , 2021 first Test run in Munich City center at the intersection of “ Ludwigstrasse / corner of Oskar-von-Miller Ring / Von der Tann- Strasse ” .

After more successful Calibration of the LiDAR sensor at the desired position , the exact Coverage area (region of interest) ( Figure 2) defined and a one hour data acquisition performed . The exact Staking the ROI is for one efficient computing power important . in the Interval of about 2 minutes the LiDAR sensor automatically captures and directs the raw data these to the Computing Unit . These processed the raw data in real time and sent the result , the so-called Object List , via a standard data protocol UDP to the computer . While the traffic monitoring is carried out in real time , the data is evaluated in the Subsequent offline .

test run delivered valuable findings above Potential of LiDAR data to the traffic data acquisition

Those collected by a LiDAR sensor Data form real-time traffic flow and traffic volume into 10 different directions and include the 7-lane north-south axis , the 5-lane east-west axis , as well a pedestrian crossing and one Bicycle path on the east side of Ludwigstrasse in the perimeter a .

The data analysis of the one-hour admission shows that it is a heavily motor vehicle -loaded crossing acts ( Figure 3.4). in the Two Minute Interval is the number of road users per category and their relative composition recorded , including those of pedestrians and cyclists . The fact that _ However only a quarter of the bike area and a Third of the pedestrian crossings at the intersection covered by the sensor became , leaves guess that number _ _ this two Traffic object types in reality higher is .

From here result yourself valuable findings about the relationship between the non-motorized and the motorized traffic and its Effects on noise protection and emissions . In addition be able effects certain Events ( e.g. events , construction sites , holidays ) on the traffic flow or . on the traffic volume analyzed become . out of it permit yourself in turn Strategies and measures for urban planning development and for safe mobility concepts derive .

another _ important element of the evaluation of the LiDAR data represents the different Traffic volumes per direction and the schematic Representation of the relative traffic load at the intersection represent . Figure 5 and 6 show that most Road users crossing from north to south ( brown curve ) and cross from west to east (red curve ) .

In addition to the cars that are in this direction drive , play the heavily used Pedestrian and bicycle paths from the University district towards city center one important role. Into the opposite direction ( light green ) . clear fewer traffic registered what on less car traffic due to the one-way street regulation in the Brienner Street short in front of the Odeonsplatz attributed is .

Summary and Outlook

LiDAR sensor system developed by LiangDao puts one reliable and real-time capable data basis supplementary to classic Data sources (GPS, thermal imaging camera , induction loops etc.) for automatic Generation of traffic data and statistics represent . By mapping the regional _ traffic volume can strengthen the system as Reference data storage for urban planning and thus for implementation news Urban mobility concepts used become .

it is also the starting point for many Further digital Applications such as real-time traffic monitoring, V2X applications and pedestrian warning systems and can be used in combination with others sensors , like eg . environmental sensors , one valuable contribution to the Reduction of environmental pollutants afford .

LiangDaos core business is to make the traffic infrastructure of tomorrow smarter to make and sustainable Mobility concepts in German cities to advance . The company understands yourself as Drivers of the mobility turnaround and innovation partners of municipalities . in the framework of the Munich innovation competition LiangDao benefited enormously from the immediate exchange with colleagues from the mobility department . _ The company could thereby valuable new findings about the requirements municipal Traffic counts and sustainable Town planning win , as well as the further development of the sensor system and the business model advance .

LiangDao sees for this reason big potential in the future cooperation with the city of Munich to relevant use cases to examine and to test . For this reason is in the coming months one one day real-time data collection with a or . two sensor systems , possibly as Comparative count with colleagues from the mobility department _ planned to work together one safer and more sustainable mobility of tomorrow guarantee .

Author : Fabienne Frauendorfer , Project Manager Smart Cities, LiangDao GmbH Contact : fabienne.frauendorfer@liangdao.de [1] car , car with Trailer , Van , Lorry , Lorry with Trailers , articulated vehicles , buses, motorcycles , other

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