Two-lane traffic flow model based on regular hexagonal cells with realistic lane changing behavior

Proceedings of the Institution of Mechanical Engineers, Part D:

Gao

et al. 2023

Lane-changing behaviour is one of the most important and basic driving behaviours. Intelligent and connected vehicles must face lane-changing scenarios to achieve autonomous driving. To improve the rationality of lane-changing trajectory planning for intelligent vehicles, by analysing numerous real vehicle lane-changing trajectories in the German HighD natural driving dataset, a dimensionless lateral quantification balance index is proposed to realise a comprehensive and objective evaluation of the degree of human-likeness of lane change trajectory planning. Focused on the lateral kinematic characteristics of lane changing, a lane-changing trajectory extraction method based on the peak-to-peak value of lateral acceleration is proposed. Lateral displacement, lateral velocity, lateral acceleration and lane-changing duration are extracted from natural driving data, and the correlations between the parameters are revealed to deduce the lateral quantification balance index. With several common parametric lane-changing trajectory models of intelligent vehicles, such as sine, quintic polynomial, Gaussian and hyperbolic tangent and fifth-order Bessel models, as examples, the index values of each lane-changing trajectory model are calculated and obtained. Results show that the proposed index can balance the different requirements in lane-changing efficiency and comfort of the trajectory parameters during the lane-changing process, thus achieving a comprehensive quantitative evaluation of lateral stability, efficiency and comfort. This research establishes an intuitive and concise objective function for human-like trajectory planning and provides a basis for trajectory tracking control and real-time dynamic correction of intelligent vehicles.

“…Similarly, a y max and d . t 2 f satisfy the linear law, which can be described by the linear function shown in formula (5). In formulas (4) and ( 5), k 1 and k 2 are constants.…”

Section: Correlation Analysis Of Kinematic Parametersmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Objective evaluation index for the comprehensive performance of intelligent vehicle lane-changing trajectory

Proceedings of the Institution of Mechanical Engineers, Part D:

Gao

et al. 2023

“…Particularly, cellular automata (CA) (microscopic) models are widely adopted to simulate trafc fow systems, because of the models' simple rules and easy implementation. From the classic single-lane NaSch trafc fow model [3] to the improved models [19][20][21][22], and to the two-lane [23,24] or even multilane [25,26] models, CA methods have demonstrated their value in well-depicting the characteristics of both microdriving behavior and macrosystem evolution. Based on the models, Campari and Levi [27], Zeng et al [10], Jiang et al [28], and Diedrich et al [29] simulated on-ramp systems and investigated their evolution characteristics.…”

Section: Introductionmentioning

confidence: 99%

The Impact of Three Specific Collaborative Merging Strategies on Traffic Flow

Shang

Journal of Advanced Transportation

et al. 2023

Self Cite

On-ramps are considered to be one of the common traffic bottlenecks. In order to improve the operation efficiency of on-ramps, scholars worldwide have proposed various vehicle merging strategies. In this study, we designed different rules to express three collaborative strategies and studied their impact on on-ramp systems. Cellular automata models were used to simulate the systems under different situations, and the average speed and traffic flow rate of both the main roads and ramps were analyzed. The results show that (1) all the three merging strategies give excessive “priority” to the merging vehicle, leading to a severe reduction in the traffic performance of the main road; (2) nevertheless, these strategies have different effects on the entire system with a one-lane or two-lane main road. Due to the lane-changing behavior, the system with a two-lane main road has more advantages than that featured with a one-lane road, making the former system performing better than the latter under the same strategies; (3) the vehicles on the ramp and main road affect each other, and as the vehicle entering probabilities become large, the traffic flow rate on the main road decreases whereas that on the ramp increases. However, the effect is not unlimited, the flow rate on both roads finally reaches a stable level (forming a “platform”); and (4) large values of the merging safety distance parameter decrease the flow rate of the entire system. All the previous results provide a deep understanding of the impact of the three merging strategies on traffic flow, contributing to the design of on-ramp systems that have better operation efficiency and low levels of congestion.

“…Microscopic traffic simulation, which is one of the important simulation approaches in heterogeneous traffic flow research, can not only mine the interaction factors and mechanisms among individual vehicles in traffic, but also accurately reflect the differences of driving characteristics of individual vehicles in heterogeneous traffic flow [1][2][3][4]. However, the effect of microscopic traffic simulation mainly depends on its accuracy [5][6][7][8][9]. As trucks and cars have obvious differences in vehicle performance and behaviour characteristics in heterogeneous traffic flow when compared with homogeneous traffic flow, higher accuracy of microscopic model is required in heterogeneous traffic flow.…”

Section: Introductionmentioning

confidence: 99%

Cellular Automata Model for Traffic Flow with Optimised Stochastic Noise Parameter

Kong

SUN

2022

PROMTT

Based on the existing safe distance cellular automata model, an improved cellular automata model based on realistic human reactions is proposed in this paper, which aims to reproduce the characteristics of congested traffic flow. In the proposed model, the stochastic noise param-eter is optimised by considering driving behavioural dif-ference. The relative speed, gap and acceleration of the front vehicle are introduced into the optimised stochastic noise parameter oriented to describing the asymmetric acceleration behaviour of drivers in congestion. The sim-ulation results show that an uneven distribution of accel-eration trajectories of vehicles experiencing congestion exhibited on the spatial-temporal diagram of the pro-posed model is reproduced. Based on the analysis of the NGSIM, compared with the model with traditional sto-chastic noise parameter, the vehicles that move accord-ing to the proposed model can follow more easily and more realistically. Then the actual gap of vehicles can be better reflected by the proposed model and the change of vehicle speed is more stable. Additionally, the traffic efficiency from two aspects of flow and speed shows that the proposed model can significantly improve the traffic efficiency in the medium high density region.