Characterizing the impact of production adaptive cruise control on traffic flow: an investigation

2018 ◽  
Vol 7 (1) ◽  
pp. 992-1012 ◽  
Author(s):  
Rachel M. James ◽  
Christopher Melson ◽  
Jia Hu ◽  
Joe Bared
Keyword(s):  
Traffic Flow ◽  
Adaptive Cruise Control ◽  
Cruise Control ◽  
The Impact

scholarly journals Resuming Manual Control or Not?: Modeling Choices of Control Transitions in Full-Range Adaptive Cruise Control

2017 ◽  
Vol 2622 (1) ◽  
pp. 38-47 ◽  
Author(s):  
Silvia F. Varotto ◽  
Haneen Farah ◽  
Tomer Toledo ◽  
Bart van Arem ◽  
Serge P. Hoogendoorn
Keyword(s):  
Traffic Flow ◽  
Traffic Congestion ◽  
Adaptive Cruise Control ◽  
Driver Behavior ◽  
Full Range ◽  
Mixed Logit ◽  
Manual Control ◽  
Cruise Control ◽  
Data Set ◽  
The Impact

Automated vehicles and driving assistance systems such as adaptive cruise control (ACC) are expected to reduce traffic congestion, accidents, and levels of emissions. Field operational tests have found that drivers may prefer to deactivate ACC in dense traffic flow conditions and before changing lanes. Despite the potential effects of these control transitions on traffic flow efficiency and safety, most mathematical models evaluating the impact of ACC do not adequately represent that process. This research aimed to identify the main factors influencing drivers’ choice to resume manual control. A mixed logit model that predicted the choice to deactivate the system or overrule it by pressing the gas pedal was estimated. The data set was collected in an on-road experiment in which 23 participants drove a research vehicle equipped with full-range ACC on a 35.5-km freeway in Munich, Germany, during peak hours. The results reveal that drivers were more likely to deactivate the ACC and resume manual control when approaching a slower leader, when expecting vehicles cutting in, when driving above the ACC target speed, and before exiting the freeway. Drivers were more likely to overrule the ACC system by pressing the gas pedal a few seconds after the system had been activated and when the vehicle decelerated. Everything else being equal, some drivers had higher probabilities to resume manual control. This study concludes that a novel conceptual framework linking ACC system settings, driver behavior characteristics, driver characteristics, and environmental factors is needed to model driver behavior in control transitions between ACC and manual driving.

LWR Model for Traffic Flow Mixed with CACC Vehicles

2021 ◽  
Author(s):  
Yanyan Qin ◽  
Hao Wang ◽  
Daiheng Ni
Keyword(s):  
Shock Waves ◽  
Traffic Flow ◽  
Adaptive Cruise Control ◽  
Cruise Control ◽  
Small Perturbations ◽  
Car Following ◽  
Lwr Model ◽  
And Shock Waves ◽  
Generalized Framework ◽  
The Impact

In the future, road traffic will incorporate a random mix of manual vehicles and cooperative adaptive cruise control (CACC) vehicles, where a CACC vehicle will degrade to an adaptive cruise control (ACC) vehicle when vehicle-to-vehicle communications are not available. This paper proposes a generalized framework of the Lighthill-Whitham-Richards (LWR) model for such mixed vehicular flow under different CACC penetration rates. In this approach, the kinematic wave speed propagating through the mixed platoon was theoretically proven to be the slope of mixed fundamental diagram. In addition, the random degradation from CACC to ACC was captured in mathematical expectation for traffic scenarios where the CACC only monitors one vehicle ahead. Three concrete car-following models, the intelligent driver model (IDM) and CACC/ACC models validated by Partners for Advanced Transit and Highways (PATH) program, were selected as examples to investigate the propagation of small perturbations and shock waves. Numerical simulations were also performed based on the selected car-following models. Moreover, the derived mixed LWR model was applied to solve some traffic flow problems. It indicates that the proposed LWR model is able to describe the propagation properties of both small perturbations and shock waves. The mixed LWR model can also be used to solve some practical problems, such as the queue caused by a traffic accident and the impact of a moving bottleneck. More importantly, the proposed generalized framework admits other CACC/ACC/regular car-following models, including those developed from further experiments.

Stability Analysis of a Macroscopic Traffic Flow Model for Adaptive Cruise Control Systems

2015 ◽  
Author(s):  
K. N. Porfyri ◽  
I. K. Nikolos ◽  
A. I. Delis ◽  
M. Papageorgiou
Keyword(s):  
Traffic Flow ◽  
Traffic Engineering ◽  
Communication Systems ◽  
Flow Model ◽  
Adaptive Cruise Control ◽  
Cruise Control ◽  
Small Perturbations ◽  
Traffic Flow Model ◽  
Traffic Jams ◽  
The Impact

Since the early days of traffic engineering, traffic flow stability has attracted a lot of attention, as the frequent occurrence of traffic jams, caused by small perturbations in traffic flow such as a sudden deceleration of a vehicle, deteriorate the performance of traffic flow and the utilization of the available infrastructure. Such traffic jams are usually related to instabilities in traffic flow, resulting in the formation of stop-and-go waves, propagating upstream the traffic flow. Emerging technologies in the field of Vehicle Automation and Communication Systems (VACS), such as Adaptive Cruise Control (ACC) systems, appear to be a remedy to reduce the amplitude or to eliminate the formation of such traffic instabilities. To this end, this work aims to derive a stability threshold of a novel macroscopic model, developed to simulate the flow of ACC-equipped vehicles, and study the impact of such vehicles on the stabilization of the traffic flow, with respect to small perturbations. The adopted macroscopic approach reflecting ACC traffic dynamics is based on the gas-kinetic (GKT) traffic flow model. The analytic results show that ACC vehicles enhance the stabilization of the traffic flow; the instability region is very narrow and by reducing the ACC time-gap setting it moves to higher values of density.

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.

Modeling of cooperative adaptive cruise control vehicle and its effect on traffic flow

2021 ◽  
pp. 2250022
Author(s):  
Jianzhong Chen ◽  
Yang Zhou ◽  
Jing Li ◽  
Huan Liang ◽  
Zekai Lv ◽  
...  
Keyword(s):  
Traffic Flow ◽  
Cooperative Control ◽  
Adaptive Cruise Control ◽  
Cruise Control ◽  
Lane Changing ◽  
Vehicle Communication ◽  
Traffic Efficiency ◽  
Vehicle To Vehicle ◽  
Road Capacity ◽  
Cooperative Adaptive Cruise Control

In this paper, an improved multianticipative cooperative adaptive cruise control (CACC) model is proposed based on fully utilizing multivehicle information obtained by vehicle-to-vehicle communication. More flexible, effective and practical spacing strategy is embedded into the model. We design a new lane-changing rule for CACC vehicles on the freeway. The rule considers that CACC vehicles are more inclined to form a platoon for coordinated control. Furthermore, we investigate the effect of CACC vehicles on two-lane traffic flow. The results demonstrate that introducing CACC vehicles into mixed traffic and forming CACC platoon to cooperative control can improve traffic efficiency and enhance road capacity to a certain extent.

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