Enhanced intelligent driver model to access the impact of driving strategies on traffic capacity

By Arne Kesting, Martin Treiber, Dirk Helbing. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 2009

925 citations recorded by the source corpus.

With an increasing number of vehicles equipped with adaptive cruise control (ACC), the impact of such vehicles on the collective dynamics of traffic flow becomes relevant. By means of simulation, we investigate the influence of variable percentages of ACC vehicles on traffic flow characteristics. For simulating the ACC vehicles, we propose a new car-following model that also serves as the basis of an ACC implementation in real cars. The model is based on the intelligent driver model (IDM) and inherits its intuitive behavioural parameters: desired velocity, acceleration, comfortable deceleration and desired minimum time headway. It eliminates, however, the sometimes unrealistic behaviour of the IDM in cut-in situations with ensuing small gaps that regularly are caused by lane changes of other vehicles in dense or congested traffic. We simulate the influence of different ACC strategies on the maximum capacity before breakdown and the (dynamic) bottleneck capacity after breakdown. With a suitable strategy, we find sensitivities of the order of 0.3, i.e. 1 per cent more ACC vehicles will lead to an increase in the capacities by about 0.3 per cent. This sensitivity multiplies when considering travel times at actual breakdowns.

Subfields: Control and Systems Engineering, Ocean Engineering, Transportation

View Paper: https://www.semanticscholar.org/paper/5c590b51396905f12b10bc5bc20146caf380cfe8

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Citations in the corpus

A Survey on Platoon-Based Vehicular Cyber-Physical Systems (2016, background): “It is verified that IDM can also accurately model the dynamics of a platoon that consists of ACC-equipped vehicles [60].”
Traffic jams: dynamics and control (2010, background): “Recent results show that even small percentages of ACC-driven vehicles may be beneficial for avoiding congestion (Zhang & Ioannou 2006; Kesting et al. 2010).”
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 ).”
Microscopic Calibration and Validation of Car-Following Models – A Systematic Approach (2013, methodology): “Some models such as the ACC model [25] also include the leading acceleration ˙ v l .”