Response Time and Time Headway of an Adaptive Cruise Control. An Empirical Characterization and Potential Impacts on Road Capacity

Makridis, Michail; Mattas, Konstantinos; Ciuffo, Biagio · 2020 · Crossref

DOI: 10.1109/tits.2019.2948646

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Summary

This study investigates the empirical response time and time headway of Adaptive Cruise Control (ACC) systems to assess their actual impact on road capacity. While literature often assumes ACC systems have negligible response times (0.1–0.5 seconds) and thus significantly increase traffic capacity, this research challenges those assumptions by measuring the performance of a commercially available ACC system under real-world conditions. The authors aim to determine if the operational parameters of current ACC technology align with theoretical models or human driver behavior, thereby influencing traffic flow dynamics. The experimental design involved a field test campaign on a 2.3 km closed track at the Joint Research Centre in Ispra, Italy. Two vehicles were equipped with high-frequency GNSS receivers to record trajectory data. The leading vehicle was manually driven, while the following vehicle utilized its ACC system. The study conducted 18 lap tests with ACC enabled across various speed settings (40–70 km/h) and headway levels, alongside five manually driven laps for comparison. To estimate response time, the authors developed a methodology using cross-correlation between the speed difference of the two vehicles and the acceleration of the ACC-equipped follower. Additionally, instantaneous perturbation events were analyzed to distinguish response times during acceleration versus braking. The collected data was used to calibrate the Intelligent Driver Model (IDM) for traffic simulation. The results indicate that the ACC controller’s response time ranged from 0.8 to 1.2 seconds, which is comparable to human driver reaction times rather than the near-instantaneous responses assumed in many theoretical studies. The desired time gaps were found to be between 1.2 and 2.2 seconds. The study also found that the controller exhibited similar response times for both braking and acceleration under safe driving conditions. When these empirically derived parameters were applied to a ring road simulation, the results showed that the network’s capacity decreased sharply in the majority of cases, contradicting the common belief that ACC inherently improves traffic efficiency. The significance of this work lies in its correction of optimistic assumptions regarding automated vehicle performance. By demonstrating that current ACC systems operate with delays and headways similar to human drivers, the study suggests that mass deployment of such technology may not yield the expected increases in road capacity. Instead, it may negatively impact traffic flow if time gaps are not optimized below specific thresholds. These findings emphasize the need for realistic parameterization in traffic simulations and highlight that current ACC technology is primarily designed for comfort rather than traffic efficiency, necessitating further development to realize the potential benefits of automation on road networks.

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• Empirical Findings: behavioral performance data