Multi-lane Changing Model with Coupling Driving Intention and Inclination

Chang, Gerard J.; Zhu, Zhouyuan; Yan, Xuedong

doi:10.7307/ptt.v29i2.2085

Cited by 10 publications

(3 citation statements)

References 19 publications

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“…In other words, when speed distribution was high, the examined vehicles tended to change lanes frequently due to the difference in speeds between vehicles. Some previous studies have found speed variations to be positively related to crashes [44,45,47,68].…”

Section: Effect Of Desired Speed Distribution On Lane Change Frequencymentioning

confidence: 92%

Simulation-Based Analysis of the Effect of Significant Traffic Parameters on Lane Changing for Driving Logic “Cautious” on a Freeway

Farooq

Juhász

2019

Sustainability

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Lane changing of traffic flow is a complicated and significsant behavior for traffic safety on the road. Frequent lane changing can cause serious traffic safety issues, particularly on a two-lane road section of a freeway. This study aimed to analyze the effect of significant traffic parameters for traffic safety on lane change frequency using the studied calibrated values for driving logic “conscious” in VISSIM. Video-recorded traffic data were utilized to calibrate the model under specified traffic conditions, and the relationship between observed variables were estimated using simulation plots. The results revealed that changes in average desired speed and traffic volume had a positive relationship with lane change frequency. In addition, lane change frequency was observed to be higher when the speed distribution was set large. 3D surface plots were also developed to show the integrated effect of specified traffic parameters on lane change frequency. Results showed that high average desired speed and large desired speed distribution coupled with high traffic volume increased the lane change frequency tremendously. The study also attempted to develop a regression model to quantify the effect of the observed parameters on lane change frequency. The regression model results showed that desired speed distribution had the highest effect on lane change frequency compared to other traffic parameters. The findings of the current study highlight the most significant traffic parameters that influence the lane change frequency.

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Section: Effect Of Desired Speed Distribution On Lane Change Frequencymentioning

confidence: 92%

Simulation-Based Analysis of the Effect of Significant Traffic Parameters on Lane Changing for Driving Logic “Cautious” on a Freeway

Farooq

Juhász

2019

Sustainability

View full text Add to dashboard Cite

show abstract

“…The simulation results showed that the model can better capture the important features of lane-changing actions, and it also reflected the impact of lane-changing on road congestion. Wang [33] considered the influence of the driver's psychology and behavior, introduced two quantitative indicators of intention intensity and risk factor, and proposed a multi-lane lane changing model that couples the driver's intention and driving tendency. Deng et al [34] introduced a one-dimensional cellular automata model for improved comfortable driving and formed a multi-lane cellular automata model based on the decision-making mechanism of lane changing.…”

Section: Research Review Of Lane-changing Modelmentioning

confidence: 99%

Theory and Experiment of Cooperative Control at Multi-Intersections in Intelligent Connected Vehicle Environment: Review and Perspectives

2022

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A heterogeneous traffic flow consists of regular vehicles, and intelligent connected vehicles having interactive functions is updating the composition of the current urban-road network traffic flow. It has been a growing trend and will continue to be so. Because of the urgent demand, the research focused on three main parts of cooperative control methods under intelligent connected vehicles environment, typical traffic control application scenarios and experimental validation in intelligent connected vehicles conditions, and intersection-oriented hybrid traffic control mechanism for urban road. For heterogeneous interrupted traffic flow of intelligent connected vehicles, to analyze the characteristics and information extraction method of heterogeneous traffic flow of intelligent connected vehicles under different conditions, the research examined driving modes of regular vehicles and intelligent connected vehicles, including car following and lane changing. This study summarized control modes of traffic-signal control, active control of intelligent connected vehicles, and indirect control of regular vehicles through intelligent vehicles to study the active control mechanism and multi-intersection coordinated control strategy for intelligent connected vehicle heterogeneous traffic flow. With the combination of coordinated control theory, this work overviewed integrated experiment of information interaction and coordinated control under intelligent-connected-vehicle heterogeneous traffic-flow environments.

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“…Chen H. et al [22] developed a dissatisfaction accumulation model based on the driver's anticipated speed in order to evaluate lane-changing decisions. Wang J. et al [23] introduced two quantitative indicators of lane-changing intensity and risk factors to devise and identify safe lane-changing conditions. Using the relative motion state of the ego vehicle and the surrounding vehicles, Ji X et al [24] established a data-driven LSTM model for recognizing the driver's lane-changing intention.…”

Section: Introductionmentioning

confidence: 99%

Research on the SSIDM Modeling Mechanism for Equivalent Driver’s Behavior

Fang

2023

WEVJ

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To solve the problem of smooth switching between the car-following model and lane-changing model, the Intelligent Driver Model (IDM) for a single lane was used to study the driver’s behavior switching mechanism of normally following, generating intentions to change lanes, creating space and speed gains, and performing lane change. In the case of sufficient lane-changing space and speed gains, the ego vehicle’s intention to change lanes was considered to solve the switching boundary between car-following behavior and lane-changing behavior, which is also the IDM failure point. In the event that there are no lane-changing gains, the IDM was optimized by incorporating the constraint components of the target lane vehicles in conjunction with the actual motion state of the ego vehicle, and the Stepless Switching Intelligent Driver Model (SSIDM) was constructed. Drivers’ natural driving information was collected, and scenario mining was performed on structured roads. On the basis of the collected data, an elliptic equation was used to fit the behavior switching boundary, and the two component balance coefficients of the front and rear vehicles on the target lane were identified. According to the test set verification results, the Mean Square Error (MSE) of the SSIDM is 2.172, which is 57.98% less than that of the conventional single-lane IDM. The SSIDM can accomplish stepless switching comparable to the driver’s behavior between the car-following behavior and the lane-changing behavior, with greater precision than IDM. This research can provide theoretical support for the construction of the point-to-point driving model and the development of L2+ autonomous driving functions. It can provide assistance for the landing and application of full-behavior and full-scene autonomous driving.

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Multi-lane Changing Model with Coupling Driving Intention and Inclination

Abstract: Considering the impact of drivers' psychology and behaviour, a multi-lane changing model coupling driving intention and inclination is proposed by introducing two quantitative indices of intention

Cited by 10 publications

References 19 publications

Simulation-Based Analysis of the Effect of Significant Traffic Parameters on Lane Changing for Driving Logic “Cautious” on a Freeway

Simulation-Based Analysis of the Effect of Significant Traffic Parameters on Lane Changing for Driving Logic “Cautious” on a Freeway

Theory and Experiment of Cooperative Control at Multi-Intersections in Intelligent Connected Vehicle Environment: Review and Perspectives

Research on the SSIDM Modeling Mechanism for Equivalent Driver’s Behavior

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