Fuel Consumption Analysis of Automated Driving Traffic Flow Based on Vehicle Specific Power

Abstract

Abstract:

Fuel consumption has a direct relationship with energy conservation and vehicle exhaust emissions. This paper explores the impacts of automated vehicles on the fuel consumption. The manual driving platoon and automated driving platoon were considered as the objective in numerical simulations, which were performed in the environment of traffic oscillations. Additionally, parameter sensitivity analyses of vehicle number, initial speeds, and vehicle-to-vehicle communication delay of automated vehicles were also conducted in simulations. Then, the vehicle-specific power-based evaluation model of fuel consumption was used to calculate the reduction of average fuel consumption rate by automated driving compared with manual driving. Meanwhile, from the perspective of traffic flow stability, the intrinsic relevance between fuel consumption reduction and stability state transition was evaluated. The results show that reduction magnitudes of fuel consumption by automated vehicles have relation with initial speeds of vehicular platoon. Moreover, there is qualitative influence relationship between fuel consumption reduction and traffic flow stability. This means the stable vehicular flow has benefits in significantly improving the reduction magnitude of fuel consumption, which can be used for providing theoretical reference for fuel control strategy, under the background of large-scale automated vehicles.

Key words: traffic engineering, traffic flow fuel consumption, numerical simulation, automated driving platoon, stability

摘要：

鉴于油耗与节约能源和车辆尾气排放直接相关，探究自动驾驶车辆对油耗的影响. 以手动驾驶车队与自动驾驶车队为数值仿真对象，在交通震荡环境下设计数值仿真实验. 对车队的车辆数量，车队初始速度，以及自动驾驶车辆的车间通信延时做参数敏感性分析. 基于机动车比功率的油耗评价模型，对仿真结果进行统计；相比于手动驾驶车队，计算自动驾驶车队平均油耗率的降低. 从交通流稳定性角度考察油耗降低与稳定性状态转变之间的内在关联性. 研究结果表明，自动驾驶车辆对油耗的降低幅度与车队初始速度有关，与交通流稳定性之间存在定性的影响关系，交通流的平稳性有利于显著改善车辆油耗降低的幅度. 研究结果可为大规模自动驾驶背景下的油耗控制策略提供理论参考.

关键词: 交通工程, 交通流油耗, 数值仿真, 自动驾驶车队, 稳定性

CLC Number:

U491

QIN Yan-yan,WANG Hao, HE Zhao-yi, RAN Bin. Fuel Consumption Analysis of Automated Driving Traffic Flow Based on Vehicle Specific Power[J]. Journal of Transportation Systems Engineering and Information Technology, 2020, 20(1): 91-96.

秦严严，王昊，何兆益，冉斌. 基于比功率的自动驾驶交通流油耗分析[J]. 交通运输系统工程与信息, 2020, 20(1): 91-96.

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URL: http://www.tseit.org.cn/EN/abstract/abstract19980.shtml

http://www.tseit.org.cn/EN/Y2020/V20/I1/91

References

[1] TAN W, LI Z C, TAN Z. Modeling the effects of speed limit, acceleration, and deceleration on overall delay and traffic emission at a signalized intersection[J]. Journal of Transportation Engineering, Part A: Systems, 2017, 143(12): 04017063.

[2] 秦严严, 王昊, 王炜, 等. 自适应巡航控制车辆跟驰模型综述[J]. 交通运输工程学报, 2017, 17(3): 121-130. [QIN Y Y, WANG H, WANG W, et al. Review of carfollowing models of adaptive cruise control[J]. Journal of Traffic and Transportation Engineering, 2017, 17(3): 121-130.]

[3] KAMALANATHSHARMA R K, RAKHA H A. Leveraging connected vehicle technology and telematics to enhance vehicle fuel efficiency in the vicinity of signalized intersections[J]. Journal of Intelligent Transportation Systems, 2016, 20(1): 33-44.

[4] 秦严严，王昊，冉斌. CACC车辆跟驰建模及混合交通流分析[J]. 交通运输系统工程与信息, 2018, 18(2):60-65. [QIN Y Y, WANG H, RAN B. Car-following modeling for CACC vehicles and mixed traffic flow analysis[J]. Journal of Transportation Systems Engineering and Information Technology, 2018, 18(2): 60-65.]

[5] PUEBOOBPAPHAN R, VAN AREM B. Driver and vehicle characteristics and platoon and traffic flow stability: Understanding the relationship for design and assessment of cooperative adaptive cruise control[J]. Transportation Research Record: Journal of the Transportation Research Board, 2010 (2189): 89-97.

[6] 秦严严, 王昊, 王炜, 等. 混有CACC车辆和ACC车辆的混合交通流驾驶舒适性[J]. 哈尔滨工业大学学报, 2017, 49(9): 103-108, 173. [QIN Y Y, WANG H, WANG W, et al. Driving comfort of traffic flow mixed with cooperative adaptive cruise control vehicles and adaptive cruise control vehicles[J]. Journal of Harbin Institute of Technology, 2017, 49(9): 103-108, 173.]

[7] 高云峰, 胡华. 基于比功率法的信号控制交叉口排队车辆尾气排放估计[J]. 中国公路学报, 2015, 28(4): 101-108. [GAO Y F, HU H. Estimation of queued vehicle emissions at signalized intersections based on vehicle specific power approach[J]. China Journal of Highway and Transport, 2015, 28(4): 101-108.]

[8] QIN Y Y, WANG H, RAN B. Stability analysis of connected and automated vehicles to reduce fuel consumption and emissions[J]. Journal of Transportation Engineering, Part A: Systems, 2018, 144(11): 04018068.

[9] SONG G, YU L. Estimation of fuel efficiency of road traffic by characterization of vehicle-specific power and speed based on floating car data[J]. Transportation Research Record: Journal of the Transportation Research Board, 2009 (2139): 11-20.

[10] BANDO M, HASEBE K, NAKAYAMA A, et al. Dynamical model of traffic congestion and numerical simulation[J]. Physical Review E, 1995, 51(2): 1035- 1042.

[11] 秦严严，王昊，冉斌. 考虑多前车反馈的智能网联车辆跟驰模型[J]. 交通运输系统工程与信息, 2018, 18(3): 48- 54. [QIN Y Y, WANG H, RAN B. Car- following model of connected and autonomous vehicles considering multiple feedbacks[J]. Journal of Transportation Systems Engineering and Information Technology, 2018,18(3): 48-54.]

[12] LI Y, ZHANG L, PEETA S, et al. A car-following model considering the effect of electronic throttle opening angle under connected environment[J]. Nonlinear Dynamics, 2016, 85(4): 2115-2125.

[13] KESTING A, TREIBER M. Influence of reaction times and anticipation on the stability of vehicular traffic flow [J]. IFAC Proceedings Volumes, 2006, 39(10): 205-210.

[14] SHLADOVER S E, NOWAKOWSKI C, LU X Y, et al. Cooperative adaptive cruise control: definitions and operating concepts[J]. Transportation Research Record: Journal of the Transportation Research Board, 2015 (2489): 145-152.

[15] WANG H, WANG W, CHEN J, et al. Estimating equilibrium speed-spacing relationship from dynamic trajectory data[C]. Proceedings of the 91rd Annual Meeting of the Transportation Research Board, Washington DC: TRB, 2012: 1-18.

[16] MLIANES V, SHLADOVER S E. Modeling cooperative and autonomous adaptive cruise control dynamic responses using experimental data[J]. Transportation Research Part C: Emerging Technologies, 2014(48): 285-300.

[17] 秦严严, 王昊, 王炜, 等. 混有CACC车辆和ACC车辆的异质交通流基本图模型[J]. 中国公路学报, 2017, 30 (10): 127-136. [QIN Y Y, WANG H, WANG W, et al. Fundamental diagram model of heterogeneous traffic flow mixed with cooperative adaptive cruise control vehicles and adaptive cruise control vehicles[J]. China Journal of Highway and Transport, 2017, 30(10): 127- 136.]

[18] LI X, CUI J, AN S, et al. Stop-and-go traffic analysis: Theoretical properties, environmental impacts and oscillation mitigation[J]. Transportation Research Part B: Methodological, 2014(70): 319-339.

[19] GONG S, SHEN J, DU L. Constrained optimization and distributed computation based car following control of a connected and autonomous vehicle platoon[J]. Transportation Research Part B: Methodological, 2016 (94): 314-334.