The Impact of Spatial Distribution of Heterogeneous Vehicles on Performance of Mixed Platoon: A Cyber-Physical Perspective

다국어 초록 (Multilingual Abstract)

This paper explores a method to improve the performance of mixed platoon when the penetration rate of automated vehicles (AVs) is low. The mixed traffic, composing of conventional vehicles and AVs, on the one hand, there is heterogeneity between conventional vehicles and AVs, on the other hand, conventional vehicles also show heterogeneity because of different drivers. Therefore, the cyber-physical relationship between vehicles is more complicated. To this end, we firstly analyze the car-following process of vehicles from the cyber-physical perspective and give the model of mixed traffic system. Then we present the descriptive method of driver heterogeneity of conventional vehicles and give the relevant evaluation indices for evaluating the performance of mixed platoon. Finally, we explore the impact of the spatial distribmution of vehicles on performance of mixed platoon in three cases, and the driver heterogeneity of conventional vehicles is also considered. What’s more, in each case, we give three spatial distribution modes and analyze the differences of mixed platoon between the three modes from multiple perspectives. The results show that when the penetration rate of AV is low in the mixed traffic, even considering driver heterogeneity, the performance of the mixed platoon can be improved by arranging regularly the spatial distribution between AVs and conventional vehicles.

참고문헌 (Reference)

1 Calvert S, "Will AVs negatively impact traffic flow?" 2 : 1-17, 2017

2 Liu B, "V2X-based decentralized cooperative adaptive cruise control in the vicinity of intersections" 17 (17): 644-658, 2016

3 Xiao L, "Unravelling effects of cooperative adaptive cruise control deactivation on traffic flow characteristics at merging bottlenecks" 96 : 380-397, 2018

4 Sun J, "Stability analysis methods and their applicability to car-following models in conventional and connected environments" 109 (109): 212-237, 2018

5 Delis A, "Simulation of the penetration rate effects of ACC and CACC on macroscopic traffic dynamics" 336-341, 2016

6 Zhao L, "Simulation framework for vehicle platooning and car-following behaviors under connected-vehicle environment" 96 : 914-924, 2013

7 Wang M, "Rolling horizon control framework for driver assistance systems. Part II: Cooperative sensing and cooperative control" 40 : 290-311, 2014

8 Jia DY, "Platoon based cooperative driving model with consideration of realistic inter-vehicle communication" 68 : 245-264, 2016

9 Deb S, "Pedestrians’receptivity toward fully AVs : Research review and roadmap for future research" 48 (48): 279-290, 2018

10 Bradley JM, "Optimization and control of cyberPhysical vehicle systems" 15 (15): 23020-23049, 2015

11 Wan NF, "Optimal speed advisory for connected vehicles in arterial roads and the impact on mixed traffic" 69 : 548-563, 2016

12 Milanés V, "Modeling cooperative and autonomous adaptive cruise control dynamic responses using experimental data" 48 : 285-300, 2014

13 Jin S, "Modeling and stability analysis of mixed traffic with conventional and connected automated vehicles from cyber physical perspective" 551 : 124217-, 2020

14 Kesting A, "Jamavoiding adaptive cruise control (ACC) and its impact on traffic dynamics" Springer 633-643, 2007

15 Qu FZ, "Intelligent transportation spaces : Vehicles, traffic, communications and beyond" 48 (48): 136-142, 2010

16 Talebpour A, "Influence of connected and autonomous vehicles on traffic flow stability and throughput" 71 : 143-163, 2016

17 Xie DF, "Heterogeneous traffic mixing regular and connected vehicles : Modeling and stabilization" 20 (20): 2060-2071, 2019

18 Zhang YM, "Force-driven traffic simulation for a future connected autonomous vehicle-enabled smart transportation system" 19 (19): 2221-2233, 2018

19 Ioannou PA, "Evaluation of ACC vehicles in mixed traffic : Lane change effects and sensitivity analysis" 6 (6): 79-89, 2005

20 Werf JV, "Effects of adaptive cruise control systems on highway traffic flow capacity" 1800 : 78-84, 2002

21 Davis LC, "Effect of adaptive cruise control systems on mixed traffic flow near an on-ramp" 379 (379): 274-290, 2007

22 Kamal MAS, "Ecological vehicle control on roads with up-down slopes" 12 (12): 83-794, 2011

23 Treiber M, "Delays, inaccuracies and anticipation in microscopic traffic models" 360 (360): 71-88, 2006

24 Xiong G, "Cyber-physical-social system in intelligent transportation" 2 (2): 320-333, 2015

25 Hu J, "Coordinated transit signal priority supporting transit progression under connected vehicle technology" 55 : 393-408, 2015

26 Sun DH, "Consensus phenomenon and characteristics of vehicle cooperative driving" 146 (146): 04020054-, 2020

27 Nobe T, "Connected vehicle accelerates green driving" 3 (3): 68-75, 2010

28 Treiber M, "Congested traffic states in empirical observations and microscopic simulations" 62 (62): 1805-1824, 2000

29 James R, "Characterizing the impact of production adaptive cruise control on traffic flow : An investigation" 7 (7): 1-21, 2018

30 Delhi N, "Automotive revolution & perspective towards 2030" 5 (5): 20-25, 2016

31 Ngoduy D, "Application of gas-kinetic theory to modeling mixed traffic of manual and ACC vehicles" 8 (8): 43-60, 2012

32 Jin PJ, "Analyzing the impact of false-accident cyber attacks on traffic flow stability in connected vehicle environment" 2013 : 616-621, 2013

33 Ngoduy D, "Analytical studies on the instabilities of heterogeneous intelligent traffic flow" 18 (18): 2699-2706, 2013

34 Wang Q, "Analysis on road capacity for mixed manual/automated traffic" 351-358, 2014

35 Bose A, "Analysis of traffic flow with mixed manual and semiautomated vehicles" 4 (4): 173-188, 2003

36 Liu H, "Analysis of traffic flow based on carfollowing theory : A cyber-physical perspective" 84 (84): 81-93, 2015

37 Zhu WX, "Analysis of mixed traffic flow with human-driving and autonomous cars based on car-following model" 496 : 274-285, 2018

38 Kesting A, "Adaptive cruise control design for active congestion avoidance" 16 (16): 668-683, 2008

39 Jia DY, "A survey on platoonbased vehicular cyber-physical systems" 18 (18): 263-284, 2016

40 Jia DY, "A multiclass microscopic model for heterogeneous platoon with vehicle-to-vehicle communication" 7 (7): 448-472, 2019

41 Liu H, "A model prediction control based framework for optimization of signaled intersection : A cyber-physical perspective" 127 (127): 68-75, 2016