Safety, Energy, and Emissions Impacts of Adaptive Cruise Control and Cooperative Adaptive Cruise Control

2020 ◽  
Vol 2674 (6) ◽  
pp. 253-267 ◽  
Author(s):  
Iman Mahdinia ◽  
Ramin Arvin ◽  
Asad J. Khattak ◽  
Amir Ghiasi
Keyword(s):  
Fuel Consumption ◽  
Adaptive Cruise Control ◽  
Field Tests ◽  
System Level ◽  
Level Energy ◽  
Cruise Control ◽  
Driver Assistance Systems ◽  
Cooperative Adaptive Cruise Control ◽  
Vehicle Platoon ◽  
Fuel Consumption And Emissions

Connected and automated vehicle technologies have the potential to significantly improve transportation system performance. In particular, advanced driver-assistance systems, such as adaptive cruise control (ACC) and cooperative adaptive cruise control (CACC), may lead to substantial improvements in performance by decreasing driver inputs and taking over control of the vehicle. However, the impacts of these technologies on the vehicle- and system-level energy consumption, emissions, and safety have not been quantified in field tests. The goal of this paper is to study the impacts of automated and cooperative systems in mixed traffic containing conventional, ACC, and CACC vehicles. To reach this goal, experimental data based on real-world conditions are collected (in tests conducted by the Federal Highway Administration and the U.S. Department of Transportation) with presence of ACC, CACC, and conventional vehicles in a vehicle platoon scenario and a cooperative merging scenario. Specifically, a platoon of five vehicles with different vehicle type combinations is analyzed to generate new knowledge about potential safety, energy efficiency, and emission improvement from vehicle automation and cooperation. Results show that adopting the CACC system in a five-vehicle platoon substantially reduces the driving volatility and reduces the risk of rear-end collision which consequently improves safety. Furthermore, it decreases fuel consumption and emissions compared with the ACC system and manually-driven vehicles. Results of the merging scenario show that while the cooperative merging system slightly reduces the driving volatility, the fuel consumption and emissions can increase because of sharper accelerations of CACC vehicles compared with manually-driven vehicles.

Multiobjective Optimization Framework for Cooperative Adaptive Cruise Control Vehicles in the Automated Vehicle Platooning Environment

2017 ◽  
Vol 2625 (1) ◽  
pp. 32-42 ◽  
Author(s):  
Zijia Zhong ◽  
Joyoung Lee ◽  
Liuhui Zhao
Keyword(s):  
Multiobjective Optimization ◽  
Fuel Consumption ◽  
Adaptive Cruise Control ◽  
Control Method ◽  
Cruise Control ◽  
Longitudinal Control ◽  
Target Time ◽  
Cooperative Adaptive Cruise Control ◽  
Vehicle Platoon ◽  
Unsafe Condition

Automated longitudinal control technology has been tested through cooperative adaptive cruise control (CACC), which is envisioned to improve highway mobility drastically by forming a vehicle platoon with short headway while maintaining stable traffic flow under disturbances. Compared with previous research efforts with the pseudomultiobjective optimization process, this paper proposes an automated longitudinal control framework based on multiobjective optimization (MOOP) for CACC by taking into consideration four optimization objectives: mobility, safety, driver comfort, and fuel consumption. Of the target time headways that have been tested, the proposed CACC platoon control method achieved the best performance with 0.9- and 0.6-s target time headways. Compared with a non-optimization-based CACC, the MOOP CACC achieved 98%, 93%, 42%, and 33% objective value reductions of time headway deviation, unsafe condition, jitter, and instantaneous fuel consumption, respectively. In comparison with a single-objective-optimization-based approach, which optimized only one of the four proposed objectives, it was shown that the MOOP-based CACC maintained a good balance between all of the objective functions and achieved Pareto optimality for the entire platoon.

Effects of adaptive and cooperative adaptive cruise control on the fuel consumption and emissions at the signalized intersection

2018 ◽  
Vol 32 (32) ◽  
pp. 1850396 ◽  
Author(s):  
Hongjun Cui ◽  
Jiangke Xing ◽  
Xia Li ◽  
Minqing Zhu
Keyword(s):  
Fuel Consumption ◽  
Red Light ◽  
Signalized Intersection ◽  
Environmental Benefit ◽  
Cruise Control ◽  
Car Following ◽  
Vehicle Type ◽  
Cooperative Adaptive Cruise Control ◽  
Car Following Model ◽  
Fuel Consumption And Emissions

In this paper, the HDM car-following model, the IIDM car-following model and the IDM car-following model with a constant-acceleration heuristic is utilized to explore the effects of ACC/CACC on the fuel consumption and emissionsat the signalized intersection. Two simulation experiments are studied: (i) one with free road ahead and (ii) the second with a red light 300 m downstream at the second intersection. The numerical results show that CACC vehicle is the best vehicle type among the three vehicle types from the perspective of vehicle’s cumulative fuel consumptions and cumulative exhaust emissions. The results of this paper also suggest a very high environmental benefit of ACC/CACC at little or no cost in infrastructure.

Multi-Vehicle Trajectory Design During Cooperative Adaptive Cruise Control Platoon Formation

2020 ◽  
Vol 2674 (4) ◽  
pp. 30-41 ◽  
Author(s):  
Qinzheng Wang ◽  
Xianfeng (Terry) Yang ◽  
Zhitong Huang ◽  
Yun Yuan
Keyword(s):  
Fuel Consumption ◽  
Adaptive Cruise Control ◽  
Second Phase ◽  
Trajectory Design ◽  
Cruise Control ◽  
Basic Scenario ◽  
Vehicle Trajectories ◽  
Cooperative Adaptive Cruise Control ◽  
Proposed Model ◽  
Study Results

Cooperative adaptive cruise control (CACC) organizes connected and automated vehicles (CAVs) in platoons to improve traffic flow and reduce fuel consumption. Platoon formation involves a very complex process, however, because lateral and longitudinal misbehavior of CAVs results in greater fuel consumption and risk of collision. This study aims to design optimal vehicle trajectories of CAVs during CACC platoon formation. First, a basic scenario and a destination-based protocol are described to determine vehicle sequence in the platoon. A space-time lattice based model is then formulated to construct vehicle trajectories considering boundary conditions of kinematic limits, vehicle-following safety, and lane-changing rules. The objective is to optimize the vehicle sequence and fuel consumption simultaneously. A two-phase algorithm is proposed to solve this model, where the first phase is a heuristic algorithm that determines vehicle sequence and in the second phase dynamic programming is adapted to optimize fuel consumption based on the determined sequence. To evaluate the effectiveness of the proposed model in designing CAV trajectories, extensive experimental tests have been conducted in this study. Results show that the proposed model and algorithm can effectively optimize CAV sequence in the platoon based on their destinations. After optimization, CAV fuel consumption was reduced by 42%, 46%, and 43%, respectively, in three different tested scenarios.

scholarly journals Time-delay feedback cooperative adaptive cruise control of connected vehicles by heterogeneous channel transmission

2019 ◽  
Vol 52 (5-6) ◽  
pp. 369-378 ◽  
Author(s):  
Xiulan Song ◽  
Xiaoxin Lou ◽  
Limin Meng
Keyword(s):  
Time Delay ◽  
Autonomous Vehicles ◽  
Adaptive Cruise Control ◽  
Sufficient Conditions ◽  
Wireless Channel ◽  
Linear Matrix ◽  
Connected Vehicle ◽  
Cruise Control ◽  
Cooperative Adaptive Cruise Control ◽  
Vehicle Platoon

In this paper, we consider the cooperative adaptive cruise control problem of connected autonomous vehicles networked by heterogeneous wireless channel transmission. The cooperative adaptive cruise control model with variable input delays is established to describe the varying time-delays induced from vehicular actuators and heterogeneous channel transmission. Then a set of decentralized time-delay feedback cooperative adaptive cruise control controllers is computed in such way that each vehicle evaluates its own adaptive cruise control strategy using only neighborhood information. In order to establish string stability of the connected vehicle platoon with the decentralized controllers, the sufficient conditions are obtained in the form of linear matrix inequalities. The scenarios, consisting of four different cars with three heterogeneous wireless channels, are used to demonstrate the effectiveness of the presented method.

Analytical studies on an optimized adaptive cruise control model of traffic flow based on self-stabilizing strategy

2020 ◽  
Vol 31 (04) ◽  
pp. 2050054
Author(s):  
Zhipeng Li ◽  
Yingying Liu ◽  
Shangzhi Xu ◽  
Yeqing Qian
Keyword(s):  
Adaptive Cruise Control ◽  
High Reliability ◽  
Cruise Control ◽  
Stabilizing Control ◽  
Traffic Capacity ◽  
Cooperative Adaptive Cruise Control ◽  
Strict Requirement ◽  
Real Time Information ◽  
Fuel Consumption And Emissions ◽  
The Impact

Cooperative adaptive cruise control (CACC) system possesses more remarkable ability to suppress disturbance and enhance the traffic capacity than adaptive cruise control (ACC). However, CACC asks for strict requirement on wireless communication and precise equipment, which remains a big difficulty to implement. This paper extends a new ACC model by introducing the self-stabilizing control with historical data, aimed at achieving the close performance of CACC and make it practicable. Substituting real-time information with pre-stored data substantially reduces the technical demand and offers high reliability to withstand the network delay. Linear stability analysis for this model points out enhancing the value of the gain or time delay of self-stabilizing control benefits to stabilize the traffic. The theories are corroborated via the simulation and further numerical simulations explicate the impact on fuel consumption and emissions and traffic capacity.

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