Open Access

Research on Traffic Flow Detection by Incorporating Improved Deep Learning Algorithms under Intelligent Transportation Construction

  
Mar 17, 2025

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Figure 1.

Yolov5 network architecture analysis
Yolov5 network architecture analysis

Figure 2.

Real-time test results of the system
Real-time test results of the system

Figure 3.

Modified loss variation image
Modified loss variation image

Figure 4.

Specific data
Specific data

Figure 5.

Effect assessment
Effect assessment

Test system accuracy test

Yolov5s test system accuracy test
Vehicle type Actual quantity ¥ vehicles System detection statistics ¥ vehicles Detection accuracy
Car 112 110 98.21%
Bus 8 5 62.50%
Van 25 20 80.00%
Other 5 4 80.00%
Total amount 150 139 92.67%
System accuracy test for rep_yolov5s_ours
Car 112 111 99.11%
Bus 8 8 100.00%
Van 25 24 96.00%
Other 5 5 100.00%
Total amount 150 148 98.67%

Experimental results of multi-lane traffic flow

Statistical plan Experimental environment Experimental results True result Accuracy rate
Yolov5s test system accuracy test Triplane 400 430 91.02%
Five lane 593 695 85.32%
System accuracy test for Yolov5s_ours Triplane 408 430 94.88%
Five lane 654 695 94.10%
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