Cellular automata-based modeling and simulation of the mixed traffic flow of vehicle platoon and normal vehicles

Zhu, Lei; Tang, Yandong; Yang, Da

doi:10.1016/j.physa.2021.126368

Cited by 28 publications

(10 citation statements)

References 26 publications

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“…where i g denotes the transmission gear ratio, i 0 denotes the fnal reduction drive ratio, and ξ represents the mechanical efciency of the transmission system. By combining equations ( 2), (7), and (8), the output power of the engine can be expressed in the following form:…”

Section: Optimal Velocity Sequence Planningmentioning

confidence: 99%

“…Te proportion of CAVs in a platoon could also signifcantly afect the fuel consumption and the average speed of the platoon [5,6]. As for the trafc fow, the appropriate penetration and size of platoons could increase the capacity of the trafc and reduce the risk of potential trafc accidents due to the unreasonable lanechanging behaviors of other environmental vehicles [7]. However, the stability, safety, and economy of the whole trafc fow will also be reduced as the size of platoons increases [8].…”

Section: Introductionmentioning

confidence: 99%

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A Two-Stage Cooperative Adaptive Cruise Control for Connected Automated Vehicles in Multislope Roads considering Communication Delay and Actuator Delay

Kuang,

Tan,

Guo

et al. 2024

Journal of Advanced Transportation

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Connected and automated vehicle platoons (CAVPs) are considered an effective way to alleviate traffic congestion, reduce the incidence of traffic accidents, and improve vehicle economy in the intelligent transportation system (ITS). Vehicles in the CAVPs can communicate with each other through V2X technology, which could optimize the economy of the platoon. Cooperative adaptive cruise control (CACC) can make effective use of the characteristics of CAVPs and contribute to resource conservation, ecological driving, and traffic system development. In this paper, a two-stage CACC method is proposed for CAVPs to reduce fuel consumption in the multislope road section. In the first stage, the optimal velocity profiles for the leader based on dynamic programming (DP) are planned according to the road information and the fuel consumption model. In the second stage, a vehicle longitudinal third-order differential dynamics model is utilized to build the platoon time-delay system considering communication delay and actuator delay. A feedback controller is developed for each vehicle considering the internal stability and the string stability of the CAVPs. Results show that the proposed method can save 5.33% of fuel consumption compared to the constant speed cooperative adaptive cruise control (CS-CACC) method and has a better tracking performance compared to the model predictive control (MPC) method. The CACC method proposed in this paper can provide a theoretical basis and data support for building an ecological CACC strategy for CAVPs.

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Section: Optimal Velocity Sequence Planningmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A Two-Stage Cooperative Adaptive Cruise Control for Connected Automated Vehicles in Multislope Roads considering Communication Delay and Actuator Delay

Kuang,

Tan,

Guo

et al. 2024

Journal of Advanced Transportation

View full text Add to dashboard Cite

show abstract

“…Therefore, the AVP could plan the optimal driving strategy, and could maintain smaller spacing than the normal safe spacing [1,2]. These advantages could not only help the AVP save energy consumption, but also reduce the probability of traffic congestion occurring [3]. Studies have shown that platoons could be able to reduce fuel consumption by an average of 2.7% to 5.3% by rationally reducing spacing [4].…”

Section: Introductionmentioning

confidence: 99%

Research of obstacle vehicles avoidance for automated heavy vehicle platoon by switching the formation

Kuang,

Tan,

Guo

et al. 2024

IET Intelligent Trans Sys

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With the development of automated vehicles, researches related to automated vehicle platoon (AVP) have received more and more attention. AVP is considered one of the effective means to alleviate traffic congestion and reduce vehicle energy consumption. This paper studies a three‐layer method of avoiding obstacle vehicles in traffic by switching the formation for the automated heavy vehicle platoon. In the decision‐making layer, a decision‐making system based on the finite‐state machine is established for formation switching. In the second layer, the lane‐changing trajectory is optimized based on the quantic polynomial curve fitting for vehicles that need to change lanes. In terms of vehicle control layer, each vehicle has a longitudinal controller based on sliding mode control and a lateral controller based on model predictive control to track the planned trajectory to complete the target formation. Finally, the proposed method is simulated in MATLAB/TruckSim. The simulation results show that the proposed method could effectively avoid the obstacle vehicles by switching the formation and has a small average value of errors in speed tracking and trajectory tracking.

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“…Lu et al conducted the simulation based on the SUMO software to study the efect of the diferent MPRs of AVs and AV levels on the Macroscopic Fundamental Diagram (MFD) [22]. Cellular automata-based models simulate mixed trafc fow, which is constructed by AVs platoon and normal vehicle [23]. Road capacity will increase as the size of platoon increases, but it will reach a maximum value and will not continue to increase.…”

Section: Introductionmentioning

confidence: 99%

Modeling Autonomous Vehicles’ Altruistic Behavior to Human-Driven Vehicles in the Car following Events and Impact Analysis

Tang

2023

Journal of Advanced Transportation

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To explore the impact of autonomous vehicles (AVs) on human-driven vehicles (HDVs), a solution for AV to coexist harmoniously with HDV during the car following period when AVs are in low market penetration rate (MPR) was provided. An extension car following framework with two possible soft optimization targets was proposed in this article to improve the experience of HDV followers with different following strategies by deep deterministic policy gradient (DDPG) algorithm. The pretreated Next Generation Simulation (NGSIM) dataset was used for the experiments. 1027 car following events with being redefined were extracted from it, in which 600 of the events were used for training and 427 of the events were used for testing. The different driving strategies obtained from the classical car following models were embedded into virtual environment built by OpenAI gym. The reward function combined safety, efficiency, jerk, and stability was used to encourage the agent with DDPG algorithm to maximize it. The final result reveals that disturbance of HDV followers decreases by 2.362% (strategy a), 8.184% (strategy b), and 13.904% (strategy c), respectively. The disturbance of HDV follower decreases by 14.961% (strategy a), 12.020% (strategy b), and 13.425% (strategy c), respectively. HDV followers with different strategies get less jerk in both soft optimizations. AV passengers get a loss on jerk and efficiency, but safety is enhanced. Also, AV car following performs better than HDV car following in both soft and brutal optimizations. Moreover, two possible solutions for harmonious coexistence of HDVs and AVs when AVs are in low MPR are proposed.

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Cellular automata-based modeling and simulation of the mixed traffic flow of vehicle platoon and normal vehicles

Cited by 28 publications

References 26 publications

A Two-Stage Cooperative Adaptive Cruise Control for Connected Automated Vehicles in Multislope Roads considering Communication Delay and Actuator Delay

A Two-Stage Cooperative Adaptive Cruise Control for Connected Automated Vehicles in Multislope Roads considering Communication Delay and Actuator Delay

Research of obstacle vehicles avoidance for automated heavy vehicle platoon by switching the formation

Modeling Autonomous Vehicles’ Altruistic Behavior to Human-Driven Vehicles in the Car following Events and Impact Analysis

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