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Transportation

Traffic Detection

Enhancing traffic management efficiency and infraction detection accuracy with AI technologies

Enhancing traffic management efficiency and infraction detection accuracy with AI technologies

For:
Urban citizens (drivers and pedestrians), government, car companies, traffic administrative bureaus, logistics companies, etc.
Goal:
Other
Problem addressed
To increase the accuracy and efficiency of infraction detection, traffic monitoring
and flow analysis, while minimizing the human effort and the overall solution
cost.
Scope of use case
Utilizing AI technologies in traffic monitoring and management
Description
With the population and the number of vehicles growing in
large cities, managing the heavy traffic in urban areas has
become a challenging yet essential task for the municipality.
Addressing this issue has become particularly urgent for big
cities in China, where millions of people live and commute
every day.
In this use case, big data-based AI technologies are applied to
monitoring and managing the heavy traffic in a metropolitan
area in south China. Previously, significant human resources
were involved in vehicle and road monitoring, and large
investment was made to the computing infrastructure
specific to certain functionalities. To increase the efficiency
of urban transportation and reduce traffic congestion and air
pollution, as well as minimize human labour, machine
learning techniques (e.g. deep learning) are applied to image
and video analysis, such as traffic flow analysis, infraction
detection and incident detection. Example applications
include but are not limited to: 1) detection of traffic rule
violations, e.g. speeding, driving in the wrong lane and
parking. AI-enabled detection produces much faster and
more accurate results, and helps in enforcing the traffic
regulations; and 2) traffic light optimization. Based on the
modelling and analysis of multi-sourced traffic information
(both real-time and historical data), traffic lights are
dynamically configured to divert the flow, increase the
76
passing speed of cars and reduce traffic congestion at major
junctions.
The use of AI has delivered remarkable results that the
infraction detection efficiency has showed a 10X increase,
and the detection accuracy is greater than 95 %. It has
greatly alleviated traffic congestion in urban areas, with
vehicles passing speed through major junctions increasing
by 9 % to 25 %.
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Machine Learning
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