Fundamental Diagram and Passenger Comfort of Mixed Traffic Flow Consisting of Adaptive Cruise Control Vehicles and Manual Vehicles

CICTP 2017 ◽  
2018 ◽  
Author(s):  
Yanyan Qin ◽  
Hao Wang ◽  
Wei Wang ◽  
Qian Wan
Keyword(s):  
Traffic Flow ◽  
Adaptive Cruise Control ◽  
Mixed Traffic ◽  
Cruise Control ◽  
Fundamental Diagram ◽  
Passenger Comfort ◽  
Mixed Traffic Flow

scholarly journals Effect of Adaptive Cruise Control on Mixed Traffic Flow: A Comparison of Constant Time Gap Policy with Variable Time Gap Policy

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Jiakuan Dong ◽  
Jiangfeng Wang ◽  
Lei Chen ◽  
Zhijun Gao ◽  
Dongyu Luo
Keyword(s):  
Traffic Flow ◽  
Adaptive Cruise Control ◽  
Constant Time ◽  
Mixed Traffic ◽  
Cruise Control ◽  
Mixed Traffic Flow ◽  
Variable Time ◽  
Low Level ◽  
Time Gap ◽  
Simulation Results

With the emerging application of low-level driving automation technology, heterogeneous traffic flow mixed with human-driven vehicles and low-level autonomous vehicles is dawning. In this context, it is imperative to investigate its effect on mixed traffic flow. As a key component for adaptive cruise control (ACC) which is a practical low-level application of driving automation, the time gap policy determines the dynamic of ACC-equipped vehicles and plays a crucial role in traffic flow stability and efficiency. There are two main time gap policies used for ACC at present, namely, constant time gap (CTG) policy and variable time gap (VTG) policy. In this study, we carried out a detailed comparison between these time gap policies to investigate their potential effect on mixed traffic flow, where the analytical- and simulation-based approaches are both considered. Analytical results show that VTG policy is superior to CTG policy in stabilizing the mixed traffic flow. In addition, numerical simulations are also conducted and simulation results further support the analytical results. As for throughput, there is no difference between CTG policy and VTG policy in analytical progress when the same time gap is set at the equilibrium. However, simulation results based on an on-ramp scenario show that the throughput of mixed traffic flow with VTG policy is slightly higher than that of CTG policy. Meanwhile, the scatter of mixed traffic flow with VTG policy in the flow-density diagram gradually clusters in the middle range of density (i.e., 20–40 veh/km) with the increase of the penetration rates of ACC vehicles, where the traffic flow operates more efficiently. These results indicate that VTG policy is better than CTG policy when designing controllers for ACC in the context of traffic flow operation and control.

scholarly journals Leading Cruise Control in Mixed Traffic Flow

2020 ◽  
Author(s):  
Jiawei Wang ◽  
Yang Zheng ◽  
Chaoyi Chen ◽  
Qing Xu ◽  
Keqiang Li
Keyword(s):  
Traffic Flow ◽  
Mixed Traffic ◽  
Cruise Control ◽  
Mixed Traffic Flow

scholarly journals How Does Heterogeneity Affect Freeway Safety? A Simulation-Based Exploration Considering Sustainable Intelligent Connected Vehicles

2020 ◽  
Vol 12 (21) ◽  
pp. 8941
Author(s):  
Yuntao Shi ◽  
Ye Li ◽  
Qing Cai ◽  
Hao Zhang ◽  
Dan Wu
Keyword(s):  
Traffic Flow ◽  
Dynamic Models ◽  
Sustainable Transportation ◽  
Individual Heterogeneity ◽  
Model Parameters ◽  
Connected Vehicles ◽  
Mixed Traffic ◽  
Cruise Control ◽  
Negative Effects ◽  
Mixed Traffic Flow

Intelligent connected vehicles (ICVs) are recognized as a new sustainable transportation mode, which could be promising for reducing crashes. However, the mixed traffic consisting of manually driven vehicles and ICVs may negatively affect road safety due to individual heterogeneity. This study investigated heterogeneity effects on freeway safety-based simulation experiments. Two types of vehicle dynamic models were employed to depict dynamic behaviors of manually driven vehicles and adaptive cruise control (ACC) vehicles (a simplified version of ICVs), respectively. Real vehicle trajectories were utilized to calibrate model parameters based on genetic algorithms. Surrogate safety measures were applied to establish the relationship between vehicle behaviors and longitudinal collision risks. Simulation results indicate that the heterogeneity has negative effects on longitudinal safety. With the higher degree of heterogeneity, longitudinal collision risks are increased. Compared to traffic flow consisting of human drivers only, mixed traffic flow may be more dangerous when the market penetration rate of ACC is low, since the ACC system can be recognized as a new source of individual heterogeneity. Findings of this study show that necessary countermeasures should be developed to improve safety for mixed traffic flow from the perspective of transportation safety planning in the near future.

Smart Driving System for Improving Traffic Flow

2017 ◽  
Vol 7 (7) ◽  
pp. 236
Author(s):  
Rajesh Kumar Gupta ◽  
L. N. Padhy ◽  
Sanjay Kumar Padhi
Keyword(s):  
Traffic Flow ◽  
Traffic Congestion ◽  
Urban Areas ◽  
Adaptive Cruise Control ◽  
Human Perception ◽  
Cruise Control ◽  
Driving System ◽  
V2v Communication ◽  
Traffic Conditions ◽  
Cooperative Adaptive Cruise Control

Traffic congestion on road networks is one of the most significant problems that is faced in almost all urban areas. Driving under traffic congestion compels frequent idling, acceleration, and braking, which increase energy consumption and wear and tear on vehicles. By efficiently maneuvering vehicles, traffic flow can be improved. An Adaptive Cruise Control (ACC) system in a car automatically detects its leading vehicle and adjusts the headway by using both the throttle and the brake. Conventional ACC systems are not suitable in congested traffic conditions due to their response delay.  For this purpose, development of smart technologies that contribute to improved traffic flow, throughput and safety is needed. In today’s traffic, to achieve the safe inter-vehicle distance, improve safety, avoid congestion and the limited human perception of traffic conditions and human reaction characteristics constrains should be analyzed. In addition, erroneous human driving conditions may generate shockwaves in addition which causes traffic flow instabilities. In this paper to achieve inter-vehicle distance and improved throughput, we consider Cooperative Adaptive Cruise Control (CACC) system. CACC is then implemented in Smart Driving System. For better Performance, wireless communication is used to exchange Information of individual vehicle. By introducing vehicle to vehicle (V2V) communication and vehicle to roadside infrastructure (V2R) communications, the vehicle gets information not only from its previous and following vehicle but also from the vehicles in front of the previous Vehicle and following vehicle. This enables a vehicle to follow its predecessor at a closer distance under tighter control.

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