The Impact of Cooperative Adaptive Cruise Control on Traffic-Flow Characteristics

By B. van Arem, Cornelie J. G. van Driel, R. Visser. IEEE transactions on intelligent transportation systems (Print), 2006

1,476 citations recorded by the source corpus.

Subfields: Building and Construction, Control and Systems Engineering, Transportation

View Paper: https://www.semanticscholar.org/paper/b5b3a9761d092aac2a43ef5ac69ab6f6aff2e205

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In Building and Construction

In Control and Systems Engineering

In Transportation

Citations in the corpus

A Survey on Platoon-Based Vehicular Cyber-Physical Systems (2016, background): “Although the investment on road construction can alleviate traffic congestion to some extent, it is not sustainable because of the huge construction cost and limited availability of land.”
Enhanced intelligent driver model to access the impact of driving strategies on traffic capacity (2009, background): “In the literature, positive as well as negative effects of ACC systems have been reported [van Arem et al., 2006; Kesting et al., 2008; Davis, 2004; VanderWerf et al., 2002; Marsden et al., 2001].”
Control barrier function based quadratic programs with application to adaptive cruise control (2014, background): “Adaptive cruise control (ACC) [11] is being developed and deployed on passenger vehicles due to its promise to enhance driver convenience, safety, traffic flow, and fuel economy [14], [15], [25].”
Flow: Architecture and Benchmarking for Reinforcement Learning in Traffic Control (2017, background): “[19], [20], [21], [22], which also have great potential to improve energy efficiency and safety in traffic.”
String-Stable CACC Design and Experimental Validation: A Frequency-Domain Approach (2010, background): “Moreover, specifically focusing on heavyduty vehicles, a significant reduction in the aerodynamic drag force is possible, thus decreasing fuel consumption [4], [5].”
A Review of Communication, Driver Characteristics, and Controls Aspects of Cooperative Adaptive Cruise Control (CACC) (2016, background): “In paper [12], the author investigates the number of shockwaves as the stability criterion during the simulation.”
Energy saving potentials of connected and automated vehicles (2018, background): “CACC not only increases road utilization due to smaller gaps [150], [139], [183], but is shown to attenuate velocity variations as shown in road experiments in [140], [141].”
A mixed traffic capacity analysis and lane management model for connected automated vehicles: A Markov chain method (2017, background): “A number of studies conducted capacity analyses for mixed traﬃc, most of them relying on computer simulation (e.g., Van Arem et al., 1997; Shladover et al., 2001; Vander Werf et al., 2002; Van Arem et al., 2006; Kesting et al., 2008; 2010; Shladover et al., 2012; Krause et al., 2017 ).”
Development and transport implications of automated vehicles in the Netherlands: scenarios for 2030 and 2050 (2017, methodology): “The transport impacts of automated vehicles have been explored based on multiple approaches ranging from traffic simulation (see van Arem et al., 2006), field experiments and analytical methods (see Rajamani and Shladover, 2001) to system dynamics (see Gruel and Stanford, 2015), agent-based…”
Flow: A Modular Learning Framework for Mixed Autonomy Traffic (2017, background): “Similarly, cooperative ACC (CACC) uses control theory to simultaneously optimize the performance of several adjacent vehicles, such as for minimizing the fuel consumption of a vehicle platoon [48], [49], [50], [51], [36].”
The social dilemma of autonomous vehicles (2015, background): “AVs promise worldchanging benefits, by increasing traffic efficiency [4], reducing pollution [5], and This is the author’s version of the work.”