Welcome to Francis Academic Press

Academic Journal of Engineering and Technology Science, 2021, 4(5); doi: 10.25236/AJETS.2021.040502.

Calculation of Vehicle Following/Unfollowing Relationship and Its Application in The Automatic Train Operation Control

Author(s)

Yongbing Wan1, Meng Mei2, Deng Pan2

Corresponding Author:
Yongbing Wan
Affiliation(s)

1 Shanghai Rail Transit Technology Research Center, Shanghai, China

2 School of Electronics and Information Engineering, Tongji University, Shanghai, China

Abstract

Whether the following vehicle’s behavior is bounded in safety, efficiency, and comfort by the position, velocity and control strategy of the preceding vehicle depends on whether vehicle following relationship exists between the two successive trains or not. The mathematical models is established to calculate the critical values of judging vehicle following/unfollowing relationship under absolute and relative braking modes. Based on the real-time calculation of vehicle following/unfollowing relationship and dynamic safe following distance, the states of automatic train following system, such as unfollowing state (i.e. free driving state), safe following state, and unsafe following state under the absolute and relative braking modes, are given and can be recognized by automatic detection systems to create conditions for the following vehicle to travel in safety, efficiency, and comfort.

Keywords

Vehicle following/unfollowing relationship; critical value; safe following distance; vehicle following state; automatic train control

Cite This Paper

Yongbing Wan, Meng Mei, Deng Pan. Calculation of Vehicle Following/Unfollowing Relationship and Its Application in The Automatic Train Operation Control. Academic Journal of Engineering and Technology Science (2021) Vol. 4, Issue 5: 6-14. https://doi.org/10.25236/AJETS.2021.040502.

References

[1] M. Bando, K. Hasebe, and A. Nakayama, A. Shibata, and Y. Sugiyama, “Dynamic model of traffic congestion and numerical simulation,” Physical Review E, vol. 51, no. 2, pp. 1035–1042, Feb. 1995.

[2] D. Helbing and B. Tilch, “Generalized force model of traffic dynamics,” Physics Review E, vol. 58, no.1, pp. 133–138, Jul. 1998.

[3] R. Jiang, Q. S. Wu, and Z. J. Zhu, “Full velocity difference model for a car-following theory,” Physics Review E, vol. 64, no.1, Jun. 2001. Art. ID 017101.

[4] X. Zhao and Z. Gao, “A new car-following model: full velocity and acceleration difference model,” European Physical Journal B, vol. 47, no.1, pp. 145- 150, Sep. 2005.

[5] A. Okumura and S. Tadaki, “Asymmetric optimal velocity model,” Journal of the Physical Society of Japan, vol. 72, no. 11, pp. 2754-2758, Nov. 2003.

[6] H. X. Gong, H. C. Liu, and B. H. Wang, “An asymmetric full velocity difference car-following model,” Physica A, vol. 387, no. 11, pp. 2595-2602, Apr. 2008.

[7] G. H. Peng, X. H. Cai, and C. Q. Liu, “Optimal velocity difference model for a car-following theory,” Physics Letter A, vol. 375, no.45, pp. 3973- 3977, Oct. 2011.

[8] F. H. Somda and H. Cormerais, “Auto-adaptive and string stable strategy for intelligent cruise control,” IET Intelligent Transport Systems, vol. 5, no. 3, pp. 168-174, Sep. 2011. 

[9] A. Kesting, M. Treiber, M. Schoenhof, and D. Helbing, “Adaptive cruise control design for active congestion avoidance,” Transportation Research Part C, vol. 16, no. 6, pp. 668–683, Dec. 2008.

[10] M. Treiber, A. Hennecke, and D. Helbing, “Congested traffic states in empirical observations and microscopic simulations,” Physical Review E, vol . 62, no. 2, pp. 1805–1824, Aug. 2000.

[11] T. Lin, S. Hwang, and P. A. Green, “Effects of time-gap settings of adaptive cruise control (ACC) on driving performance and subjective acceptance in a bus driving simulator,” Safety Science, vol. 47, no. 5, pp. 620-625, May 2009.

[12] X. Y. Lu and S. Madanat, “Truck adaptive following distance based on threat assessment under variable conditions,” IET Intelligent Transport Systems, vol. 3, no. 2, pp. 138-147, Jun. 2009.

[13] R. Takagi, “Synchronisation control of trains on the railway track controlled by the moving block signalling system,” IET Electrical Systems in Transportation, vol. 2, no. 3, pp. 130–138, Sep. 2012.

[14] L. D. Baskar, B. De Schutter, and H. Hellendoorn, “Traffic Management for Automated Highway Systems Using Model-Based Predictive Control,” IEEE Transaction on Intelligent Transportation Systems, vol. 13, no. 2, pp. 838-847, Jun. 2012.

[15] J. J. Martinez and C. Canudas-de-Wit, “Model reference control approach for safe longitudinal control,” in Proceedings of the American Control Conference, 2004, pp. 2757-2762.