BY IMPROVING DETECTION CAPABILITIES , THIS SYSTEM COULD PROPEL AUTONOMOUS VEHICLES INTO THE MAINSTREAM .
INDUSTRY WATCH technique , which is the most active state-of-the-art technique available for 2D visual detection .
The researchers first used this new model for 2D object detection and then modified the YOLOv3 technique to detect 3D objects .
Using both point cloud data and RGB images as input , the system generates bounding boxes with confidence scores and labels for visible obstacles as output .
To assess the system ’ s performance , the team conducted experiments using the Lyft dataset , which
BY IMPROVING DETECTION CAPABILITIES , THIS SYSTEM COULD PROPEL AUTONOMOUS VEHICLES INTO THE MAINSTREAM .
Future for smart transportation
A new report released by ResearchAndMarkets . com estimates the global smart transportation market will grow from US $ 120.4 billion in 2023 to reach US $ 310.65 billion by 2030 – a CAGR of 14.50 % during the forecast period from 2023 to 2030 .
The trend toward autonomous vehicles is referenced in the report as having the potential to transform the concept of transportation .
In the report , IoT is recognised as establishing networked ecosystems enabling real-time data sharing and decision-making by integrating sensors , communication devices and data analysis tools into cars , infrastructure and urban environments .
Vehicles outfitted with IoT devices can connect , traffic control systems and even people , providing a complete picture of the transportation landscape .
This real-time connectivity is recognised in the report as improving traffic management , optimizing routes and reducing congestion .
Furthermore , the report says , IoT technology is enabling predictive maintenance , allowing for the early diagnosis of vehicle issues and the prevention of failures , contributing to smoother operations and reduced downtime .
The report identifies the combination of IoT with Mobility as a Service ( MaaS ) as having the potential to provide to provide consumers with ‘ seamless access ’ to several modes of transportation – including public transport , ridesharing , bikesharing , and even autonomous taxis , all through a single app .
Furthermore , the report says , automation technology can improve traffic flow by allowing vehicles to communicate and coordinate with one another , reducing abrupt lane changes and braking , both of which contribute to congestion .
The report concludes that smart transportation is now poised to change the very concept of urban mobility in paving the way for a future characterized by ‘ intelligent , connected and autonomous ’ transportation systems as governments , industry , and researchers work together to overcome issues and harness the potential of emerging technologies . consisted of road information captured from 20 autonomous vehicles traveling a predetermined route in Palo Alto , California , over a four-month period .
The results demonstrated that YOLOv3 exhibits high accuracy , surpassing other state-of-the-art architectures .
Notably , the overall accuracy for 2D and 3D object detection were an impressive 96 % and 97 %, respectively .
Prof . Jeon said : “ By improving detection capabilities , this system could propel autonomous vehicles into the mainstream . The introduction of autonomous vehicles has the potential to transform the transportation and logistics industry , offering economic benefits through reduced dependence on human drivers and the introduction of more efficient transportation methods .”
The present work is expected to drive research and development in various technological fields such as sensors , robotics and AI .
Going ahead , the team aims to explore additional Deep Learning algorithms for 3D object detection , recognizing the current focus on 2D image development . p
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