Multianticipative Adaptive Cruise Control Compared With Connectivity-Enhanced Solutions: Simulation-Based Investigation in Mixed Traffic Platoons

The paper explores via simulation analysis how multianticipative adaptive cruise control (M-ACC) can address traffic oscillations with respect to cooperative adaptive cruise control (CACC) approaches. The work is grounded on our previous findings where we suggested a functioning logic and a performance characterization of M-ACC. That activity followed a manufacturer's claim that vehicles capable of reacting to more than one leader ahead are already populating public roads. In this light, M-ACC represents an intermediate solution between the traditional ACC, which typically is capable of reacting to only one vehicle ahead, and connectivity-enhanced approaches, which in principle could track multiple leaders. Given that M-ACC is effective from small penetration rates-as it does not require the presence of other M-ACC-equipped vehicles to reach its full potential-performance comparison with CACC is not straightforward. In particular, for a fair comparison it is necessary to quantify the performance gap as a function of the penetration rate, which is exactly the objective of this paper. Three CACC topologies are investigated and both stochastic simulations and Pareto analyses are performed. The results demonstrate that, for small market penetration figures, M-ACC can still guarantee better performances than any CACC heterogenous platoons for all the metrics considered given that it does not require infrastructure or other adjacent vehicles featuring the same technology. Considering that the market adoption of connectivity-based solutions is facing challenging practical issues, M-ACC could represent a suitable as well as realistic option to harvest the benefits of automation to traffic flow in the near future.

Automated summary

This paper investigates how multianticipative adaptive cruise control (M-ACC) can address traffic oscillations compared to cooperative adaptive cruise control (CACC) approaches through simulation analysis. The results show that for small market penetration rates, M-ACC outperforms any CACC heterogenous platoons in terms of performance metrics as it does not require infrastructure or other adjacent vehicles featuring the same technology. Given the challenges in market adoption of connectivity-based solutions, M-ACC could be a suitable and realistic option to harness the benefits of automation to traffic flow in the near future.