Empirical Study on the Properties of Adaptive Cruise Control Systems and Their Impact on Traffic Flow and String Stability

Adaptive cruise control (ACC) systems are standard equipment in many commercially available vehicles. They are considered the first step of automation, and their market penetration rate is expected to rise, along with the interest of researchers worldwide to assess their impact in relation to traffic flow and stability. These properties are currently discussed mainly through microsimulation studies and empirical observations, with the first being the most common. Experimental observations can draw safer conclusions about the behavior of such systems, but the literature is limited. In this work, an experimental campaign with five vehicles equipped with ACC was conducted at the proving ground of AstaZero in Sweden to improve understanding on the properties of ACC systems and their functionality under real driving conditions. The main parameters under investigation are the response time of controllers, the available time headway settings, and the stability of the car-platoon. The results show that the response time range for the controllers is between 1.7 and 2.5 s, significantly longer than the values reported in the literature. The range of the time headway settings was found to be quite broad. Finally, a dataset of perturbations on a variety of equilibrium speeds of the car-platoon and of variable magnitudes was created. Results clearly highlight the instability of the car-platoon. Instability is also displayed even for slight perturbations derived by variability in the road gradient. Numerical differentiation on the altitude shows a negative correlation with the speed trajectory of the leading vehicle.

[1]  Steven E Shladover,et al.  Cooperative Adaptive Cruise Control: Driver Acceptance of Following Gap Settings Less than One Second , 2010 .

[2]  Peter Wagner,et al.  Impacts of gradual automated vehicle penetration on motorway operation: a comprehensive evaluation , 2019 .

[3]  Martijn van Noort,et al.  Cooperative driving in mixed traffic networks — Optimizing for performance , 2012, 2012 IEEE Intelligent Vehicles Symposium.

[4]  Biagio Ciuffo,et al.  Simulating deployment of connectivity and automation on the Antwerp ring road , 2018, IET Intelligent Transport Systems.

[5]  Victor L. Knoop,et al.  Platoon of SAE Level-2 Automated Vehicles on Public Roads: Setup, Traffic Interactions, and Stability , 2019, Transportation Research Record: Journal of the Transportation Research Board.

[6]  Ken Tough Optimizing the Performance , 1999 .

[7]  Xiao-Yun Lu,et al.  COOPERATIVE ADAPTIVE CRUISE CONTROL (CACC) DEFINITIONS AND OPERATING CONCEPTS , 2015 .

[8]  Yunpeng Wang,et al.  Influence of Driving Behaviors on the Stability in Car Following , 2019, IEEE Transactions on Intelligent Transportation Systems.

[9]  Stephen D. Boyles,et al.  Effects of Autonomous Vehicle Behavior on Arterial and Freeway Networks , 2016 .

[10]  Steven E Shladover,et al.  Impacts of Cooperative Adaptive Cruise Control on Freeway Traffic Flow , 2012 .

[11]  Ye Li,et al.  Longitudinal safety impacts of cooperative adaptive cruise control vehicle's degradation. , 2019, Journal of safety research.

[12]  Steven E Shladover,et al.  Modeling cooperative and autonomous adaptive cruise control dynamic responses using experimental data , 2014 .

[13]  Antonio Sciarretta,et al.  Safe- and Eco-Driving Control for Connected and Automated Electric Vehicles Using Analytical State-Constrained Optimal Solution , 2018, IEEE Transactions on Intelligent Vehicles.

[14]  L. Davis Effect of adaptive cruise control systems on traffic flow. , 2004, Physical review. E, Statistical, nonlinear, and soft matter physics.

[15]  Vicente Milanés Montero,et al.  Cooperative Adaptive Cruise Control in Real Traffic Situations , 2014, IEEE Transactions on Intelligent Transportation Systems.

[16]  Dirk Helbing,et al.  Microsimulations of Freeway Traffic Including Control Measures , 2002, cond-mat/0210096.

[17]  Feng Gao,et al.  A comprehensive review of the development of adaptive cruise control systems , 2010 .

[18]  Marc Green,et al.  "How Long Does It Take to Stop?" Methodological Analysis of Driver Perception-Brake Times , 2000 .

[19]  Biagio Ciuffo,et al.  Adaptive Cruise Control Strategies Implemented on Experimental Vehicles: A Review , 2019, IFAC-PapersOnLine.

[20]  L C Davis,et al.  Multilane simulations of traffic phases. , 2004, Physical review. E, Statistical, nonlinear, and soft matter physics.

[21]  Dirk Helbing,et al.  Adaptive cruise control design for active congestion avoidance , 2008 .

[22]  Jian Sun,et al.  Stability analysis methods and their applicability to car-following models in conventional and connected environments , 2018 .

[23]  Meng Wang,et al.  Potential impacts of ecological adaptive cruise control systems on traffic and environment , 2014 .

[24]  Meixin Zhu,et al.  Impact on car following behavior of a forward collision warning system with headway monitoring , 2020 .

[25]  Maria Laura Delle Monache,et al.  Are Commercially Implemented Adaptive Cruise Control Systems String Stable? , 2019, IEEE Transactions on Intelligent Transportation Systems.

[26]  Markos Papageorgiou,et al.  On Microscopic Modelling of Adaptive Cruise Control Systems , 2015 .

[27]  Biagio Ciuffo,et al.  Response Time and Time Headway of an Adaptive Cruise Control. An Empirical Characterization and Potential Impacts on Road Capacity , 2020, IEEE Transactions on Intelligent Transportation Systems.

[28]  Bruno Augusto Angélico,et al.  Predictive Adaptive Cruise Control Using a Customized ECU , 2019, IEEE Access.

[29]  Lei Zhu,et al.  An Automated Vehicle Fuel Economy Benefits Evaluation Framework Using Real-World Travel and Traffic Data , 2019, IEEE Intelligent Transportation Systems Magazine.

[30]  Daniele Borio,et al.  Estimating empirically the response time of commercially available ACC controllers under urban and freeway conditions , 2019, 2019 6th International Conference on Models and Technologies for Intelligent Transportation Systems (MT-ITS).

[31]  R. E. Wilson,et al.  Mechanisms for spatio-temporal pattern formation in highway traffic models , 2008, Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences.

[32]  Petros A. Ioannou,et al.  Evaluation of ACC vehicles in mixed traffic: lane change effects and sensitivity analysis , 2005, IEEE Transactions on Intelligent Transportation Systems.

[33]  Steven E. Shladover,et al.  Connected and automated vehicle systems: Introduction and overview , 2018, J. Intell. Transp. Syst..

[34]  R. E. Wilson,et al.  Car-following models: fifty years of linear stability analysis – a mathematical perspective , 2011 .

[35]  Christopher Nowakowski,et al.  Cooperative Adaptive Cruise Control , 2015 .

[36]  Dirk Helbing,et al.  Jam-Avoiding Adaptive Cruise Control (ACC) and its Impact on Traffic Dynamics , 2005 .