Driver characteristics in the lane change process

Tian, E.

doi:10.1109/rsete.2011.5964968

Cited by 5 publications

(3 citation statements)

References 5 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Emotional instability had little influence on drivers’ proneness to the behaviour. The calculated results are similar to those in some existing research [35, 36], which indicates that the results are reliable. Fig.…”

Section: Resultssupporting

confidence: 88%

Psychological and environmental factors affecting driver's frequent lane‐changing behaviour: a national sample of drivers in China

Yin

Jiang

et al. 2020

IET Intelligent Transport Systems

View full text Add to dashboard Cite

Section: Resultssupporting

confidence: 88%

Psychological and environmental factors affecting driver's frequent lane‐changing behaviour: a national sample of drivers in China

Yin

Jiang

et al. 2020

IET Intelligent Transport Systems

View full text Add to dashboard Cite

“…(1) Different types of stimulus under LM Depending on the driving characteristics, different drivers displayed different driving styles during lane change [27], [28], which can be classified into 3 types according to the headway between the LM vehicle and the following vehicle at the moment of the beginning of the LM [29]: free lane change, forced lane change and competitive/cooperative lane change. These 3 types of LM process can be regarded as a different stimulus under different gap condition for the following vehicle:…”

Section: B Modeling Methodsmentioning

confidence: 99%

A Car-Following Model Considering Preceding Vehicle’s Lane-Changing Process

et al. 2019

View full text Add to dashboard Cite

Car following and lane changing are two common driving behaviors in the traffic flow. Preceding vehicle's lane changing is affected by the surroundings and will have a greater influence on the followers' driving decision. The existing car-following theory does not fully take it into consideration that the followers' driving behavior may change during a lane-changing process. In order to reflect the driving decision in a complex traffic flow more precisely, the influence on the following vehicle during the preceding vehicle's lane-changing process is studied. First, the different types of stimulus during the preceding vehicle's lane-merging (LM) process and the space gain effect produced by the preceding vehicle's lane-passing (LP) behavior are analyzed. Then, the LM-FVDM and LP-FVDM are proposed based on the classical carfollowing model-FVD model. Finally, the linear stability theory, numerical simulation, and NGSIM data sets are used to analyze and validate the performance of the LM-FVDM and LP-FVDM. The numerical simulation results show that the model can reasonably reflect the driving decision of the following vehicle in various scenarios, and verification based on NGSIM shows that the R-squared of vehicles' speed and distance is significantly better than the FVD model, which can more effectively reflect the speed adjustment process of the following vehicle during the preceding vehicle's lane-changing process in the real traffic flow.INDEX TERMS Car-following model, lane-changing behavior, multi-lane traffic, lateral separations, NGSIM.

show abstract

“…When a nearby vehicle cuts into the lane, the lateral distance and lateral velocity of the vehicle change quite obviously [25]. Therefore, this paper studies the cut-in possibility of nearby vehicles in the lateral distance and with a relative lateral velocity.…”

Section: Quantification Of Cut-in Possibility Based On Lateral Distance and Lateral Relative Velocitymentioning

confidence: 99%

Adaptive Cruise Control for Cut-In Scenarios Based on Model Predictive Control Algorithm

Chen¹,

Guo²,

Guo³

et al. 2021

Applied Sciences

View full text Add to dashboard Cite

In a cut-in scenario, traditional adaptive cruise control usually cannot effectively identify the cut-in vehicle and respond to it in advance. This paper proposes an adaptive cruise control (ACC) strategy based on the MPC algorithm for cut-in scenarios. A finite state machine (FSM) is designed to manage vehicle control in different cut-in scenarios. For a cut-in scenario, a method to identify and quantify the possibility of cut-in of a vehicle is proposed. At the same time, a safety distance model of the cut-in vehicle is established as the basis for the state transition of the finite state machine. Taking the quantified cut-in possibility of a vehicle as a reference, the model predictive control (MPC) algorithm, which considers the constraints of driving safety and comfort, is used to realize coordinated control of the host vehicle and the cut-in vehicle. Simulink–Carsim simulation studies show that the ACC strategy for a cut-in scenario can effectively identify a cut-in vehicle and quantify the possibility of cut-in of the vehicle. Faced with a cut-in vehicle, the host vehicle using the ACC strategy can brake several seconds early and switch the following target to the cut-in vehicle. Meanwhile, the acceleration and jerk of the host vehicle changes within a reasonable range, which ensures driving safety and comfort.

show abstract

Driver characteristics in the lane change process

Cited by 5 publications

References 5 publications

Psychological and environmental factors affecting driver's frequent lane‐changing behaviour: a national sample of drivers in China

Psychological and environmental factors affecting driver's frequent lane‐changing behaviour: a national sample of drivers in China

A Car-Following Model Considering Preceding Vehicle’s Lane-Changing Process

Adaptive Cruise Control for Cut-In Scenarios Based on Model Predictive Control Algorithm

Contact Info

Product

Resources

About