scholarly journals Stability Analysis of Mixed Traffic Flow using Car-Following Models on Trajectory Data

2021 ◽  
Author(s):  
H R Surya ◽  
Narayana Raju ◽  
Shriniwas S Arkatkar
Keyword(s):  
Stability Analysis ◽  
Traffic Flow ◽  
Mixed Traffic ◽  
Trajectory Data ◽  
Car Following ◽  
Mixed Traffic Flow

scholarly journals Risk Modeling and Quantification of a Platoon in Mixed Traffic Based on the Mass-Spring-Damper Model

2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
Luo Jiang ◽  
Jie Ji ◽  
Yue Ren ◽  
Hong Wang ◽  
Yanjun Huang
Keyword(s):  
Total Energy ◽  
Traffic Flow ◽  
Dominant Factor ◽  
Mixed Traffic ◽  
Quantitative Index ◽  
Car Following ◽  
Mixed Traffic Flow ◽  
Emergency Braking ◽  
Car Following Model ◽  
Mass Spring

Connected and automated vehicle (CAV) technologies have great potential to improve road safety. However, an emerging type of mixed traffic flow with human-driven vehicles (HDVs) and CAVs has also arisen in recent years. To improve the overall safety of this mixed traffic flow, a novel car-following model is proposed to control the driving behaviors of the above two types of vehicles in a platoon from the perspective of a mechanical system, mass-spring-damper (MSD) system. Furthermore, a quantitative index is proposed by incorporating the psychological field theory into the MSD model. The errors of spacing and speed in the car-following processes can be expressed as the accumulation of the virtual total energy, and the magnitude of the energy is used to reflect the danger level of vehicles in the mixed platoon. At the same time, the optimization model of minimum total energy is solved under the constraints of vehicle dynamics and the mechanical characteristics of the MSD system, and the optimal solutions are used as the parameters of the MSD car-following model. Finally, a mixed platoon composed of 3 CAVs and 2 HDVs without performing lane changing is tested using the driver-in-the-loop test platform. The test results show that, in the mixed platoon, CAVs can optimally adjust the intervehicle spacing by making full use of the braking distance, which also provides sufficient reaction time for the driver of HDV to avoid rear-end collisions. Furthermore, in the early stage of the emergency braking, the spacing error is the dominant factor influencing the car-following behaviors, but in the later stage of emergency braking, the speed error becomes the decisive factor of the car-following behaviors. These results indicate that the proposed car-following model and quantitative index are of great significance for improving the overall safety of the mixed traffic flow with CAVs and HDVs.

Analytical studies on an extended car following model for mixed traffic flow with slow and fast vehicles

2016 ◽  
Vol 27 (01) ◽  
pp. 1650004 ◽  
Author(s):  
Zhipeng Li ◽  
Xun Xu ◽  
Shangzhi Xu ◽  
Yeqing Qian ◽  
Juan Xu
Keyword(s):  
Standard Deviation ◽  
Traffic Flow ◽  
Maximum Velocity ◽  
Traffic Density ◽  
Extended Model ◽  
Mixed Traffic ◽  
Car Following ◽  
Mixed Traffic Flow ◽  
Average Maximum ◽  
Car Following Model

The car-following model is extended to take into account the characteristics of mixed traffic flow containing fast and slow vehicles. We conduct the linear stability analysis to the extended model with finding that the traffic flow can be stabilized with the increase of the percentage of the slow vehicle. It also can be concluded that the stabilization of the traffic flow closely depends on not only the average value of two maximum velocities characterizing two vehicle types, but also the standard deviation of the maximum velocities among all vehicles, when the percentage of the slow vehicles is the same as that of the fast ones. With increase of the average maximum velocity, the traffic flow becomes more and more unstable, while the increase of the standard deviation takes negative effect in stabilizing the traffic system. The direct numerical results are in good agreement with those of theoretical analysis. Moreover, the relation between the flux and the traffic density is investigated to simulate the effects of the percentage of slow vehicles on traffic flux in the whole density regions.

scholarly journals Stability and Environmental Analysis of Mixed Traffic Flow – Using the Markov Probabilistic Theory

2020 ◽  
Vol 32 (6) ◽  
pp. 849-861
Author(s):  
Linheng Li ◽  
Jing Gan ◽  
Xu Qu ◽  
Jian Zhang ◽  
Bin Ran
Keyword(s):  
Spatial Distribution ◽  
Stability Analysis ◽  
Fuel Consumption ◽  
Traffic Flow ◽  
Open Boundary ◽  
Market Penetration ◽  
Mixed Traffic ◽  
Open Boundary Conditions ◽  
Mixed Traffic Flow ◽  
Stability Performance

The rapid growth of CAV (Connected and Automated Vehicle) market penetration highlights the need to gain insight into the overall stability of mixed traffic flows in order to better deploy CAVs. Several studies have examined the modelling process and stability analysis of traffic flow in a mixed traffic environment without considering its inner spatial distribution. In this paper, an innovative Markov chain-based model is established for integrating the spatial distribution of mixed traffic flow in the model process of car-following behaviour. Then the linear stability analysis of the mixed traffic flow is conducted for different CAV market penetration rates, different CAV platoon strength and different cooperation efficiency between two continuous vehicles. Moreover, several simulations under open boundary conditions in multiple scenarios are performed to explicate how CAV market penetration rate, platoon strength and cooperation efficiency jointly influence the stability performance of the mixed traffic flow. The results reveal that the performance of this mixed traffic flow stability could be strengthened in these three factors. In addition to stability, an investigation of the fuel consumption and emission reduction under different market penetration rates and the platoon strength of CAVs are explored, suggesting that substantial potential fuel consumption and emission could be reduced under certain scenarios.

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