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The phenomenon of high-speed-car-following on Chinese highways

The phenomenon of high-speed-car-following on Chinese highways. Mingmin Guo, Zheng Wu Department of Mechanics and Engineering Science Fudan University . Outline. Background and motivation Data Sets Results and analysis Conclusions. Background and motivation.

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The phenomenon of high-speed-car-following on Chinese highways

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  1. The phenomenon of high-speed-car-followingon Chinese highways MingminGuo, Zheng Wu Department of Mechanics and Engineering Science Fudan University

  2. Outline • Background and motivation • Data Sets • Results and analysis • Conclusions

  3. Background and motivation • Traffic flow is of complicated nonlinearity: stop-and-go phenomenon under high density. • We found the nonlinearity under low density on urban expressways: high-speed-car-following (HSCF).

  4. Background and motivation • Similar results in literatures U.S. highway 101, NGSIM data Chen et al., IEEE Trans. Intell. Transp. 2010: 11(4) : 773-785 German highway A1, loop detector data Neubert et al., PRE 1999, 60(6) : 6480-6490

  5. Background and motivation • Empirical observations play crucial roles. • Numerous important achievements • Next Generation Simulation (NGSIM) project • The traffic videos taken from the intercity highways are lacking. • So we studied the HSCF phenomenon on intercity highways based on traffic videos.

  6. Outline • Background and motivation • Data Sets • Results and analysis • Conclusions

  7. Data Sets • 100 hours of traffic video from fours locations

  8. Data Sets • Seven samples from 17.5 hours out of total videos • About 40,000 vehicles • 94392 speed data、28201 space headway data

  9. Data Sets • The vehicle class was collected. • The proportions of heavy vehicles of two frequently-used NGSIM data • I-80 (Berkeley Highway): 2.2% • US-101 (Hollywood Freeway): 3.8%

  10. Data Sets • Overview of the traffic situation

  11. Outline • Background and motivation • Data Sets • Results and analysis • Conclusions

  12. Results and analysis • Time headway (ht): the time difference between two successive vehicles passing the same location. • In this paper, it was calculated by where hsis space headway, v is speed.

  13. Results and analysis • The percentages of ht ≤ 2 s and ht ≤ 1 s are remarkable.

  14. Frequency distribution of the data with ht≤1 s in sample 3 for different speed ranges Results and analysis • The small ht are related to the driving behavior with high speed and small spacing, so-called “high-speed-car-following”.

  15. Proportion of the vehicles with ht≤1 s in sample 3 for each lane Results and analysis • The distributions of HSCF vehicles on each lane are different. Most of the HSCF vehicles are cars.

  16. Results and analysis • Dependence of the average speed at different lanes on the number of HSCF vehicles----in 1 min interval Sample 3, G2 Sample 5, G15w

  17. Results and analysis • Dependence of the flow at different lanes on the number of HSCF vehicles----in 1 min interval Sample 3, G2 Sample 5, G15w

  18. Results and analysis • Dependence of the density at different lanes on the number of HSCF vehicles----in 1 min interval Sample 3, G2 Sample 5, G15w

  19. Results and analysis • HSCF can roughly be classified into two types: Active HSCF Passive HSCF

  20. Results and analysis • HSCF often makes the rear vehicle’s driver take a lane-changing maneuver as well.

  21. Results and analysis • Dependence of the average frequency of lane-changing at different lanes on the number of HSCF vehicles----in 1 min interval

  22. Outline • Background and motivation • Data Sets • Results and analysis • Conclusions

  23. Conclusions • HSCF, such a dangerous driving behavior, has a relatively high frequency of occurrence on Chinese intercity highways. • Cars, fast lanes and locations near the urban area have higher proportion of HSCF than trucks, slow lanes and locations far from the urban area, respectively.

  24. Conclusions • In general, the flow and the density will increase as the frequency of HSCF increases. HSCF may affect the capacity and level of service. • As the frequency of HSCF increases, the average velocity of the left lane decreases, while the average velocity of the other lanes increases.

  25. Conclusions • HSCF can be classified into active type and passive type. The latter type is caused by lane-changing and overtaking. • HSCF may cause lane-changing as well, and the frequencies of them vary synchronously. • HSCF enhances the nonlinearity of traffic flowunder low density.

  26. Thank you!

  27. In sample 3 (09:37-11:24) • 258 cars with ht ≤ 1s were observed. • 13 trucks with ht ≤ 1s were observed. • Among the 258 HSCF cars, only 2 of them followed trucks. • Among the 13 HSCF trucks, more than a half, i.e. 7 of them, travelled after cars.

  28. The time series of the flow, the density and the velocity of sample 3

  29. The fundamental diagram of sample 3----in 1 min interval

  30. The fundamental diagram of sample 3---- based on the moving average of 15-min period

  31. The trends of the flow and the HSCF----based on the moving average of 15-min period

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