Abstract
The introduction of automated vehicles is expected to affect traffic performance. Microscopic traffic simulation offers good possibilities to investigate the potential effects of the introduction of automated vehicles. However, current microscopic traffic simulation models are designed for modelling human-driven vehicles. Thus, modelling the behaviour of automated vehicles requires further development. There are several possible ways to extend the models, but independent of approach a large problem is that the information available on how automated vehicles will behave is limited to today’s partly automated vehicles. How future generations of automated vehicles will behave will be unknown for some time. There are also large uncertainties related to what automation functions are technically feasible, allowed, and actually activated by the users, for different road environments and at different stages of the transition from 0 to 100% of automated vehicles. This article presents an approach for handling several of these uncertainties by introducing conceptual descriptions of four different types of driving behaviour of automated vehicles (Rail-safe, Cautious, Normal, and All-knowing) and presents how these driving logics can be implemented in a commonly used traffic simulation program. The driving logics are also linked to assumptions on which logic that could operate in which environment at which part of the transition period. Simulation results for four different types of road facilities are also presented to illustrate potential effects on traffic performance of the driving logics. The simulation results show large variations in throughput, from large decreases to large increases, depending on driving logic and penetration rate.
Highlights
Academic Editor: Chengxiang Zhuge e introduction of automated vehicles is expected to affect traffic performance
How future generations of automated vehicles will behave will be unknown for some time. ere are large uncertainties related to what automation functions are technically feasible, allowed, and activated by the users, for different road environments and at different stages of the transition from 0 to 100% of automated vehicles. is article presents an approach for handling several of these uncertainties by introducing conceptual descriptions of four different types of driving behaviour of automated vehicles (Rail-safe, Cautious, Normal, and All-knowing) and presents how these driving logics can be implemented in a commonly used traffic simulation program. e driving logics are linked to assumptions on which logic that could operate in which environment at which part of the transition period
Within the CoEXist project, a test-track field test using CAV prototypes developed by TNO was conducted. ree vehicles were used in the field test, one with adaptive cruise control (ACC), one with Cooperative ACC (CACC), and one with Degraded cooperative adaptive cruise control (CACC)
Summary
Johan Olstam ,1,2 Fredrik Johansson, Adriano Alessandrini, Peter Sukennik, Jochen Lohmiller, and Markus Friedrich. Is article presents an approach for handling several of these uncertainties by introducing conceptual descriptions of four different types of driving behaviour of automated vehicles (Rail-safe, Cautious, Normal, and All-knowing) and presents how these driving logics can be implemented in a commonly used traffic simulation program. When applying the suggested approach for analysing a specific case, relevant uncertainty factors, such as penetration rates and AV mixes, need to be quantified for each stage based on assumptions on the evolution and deployment of AVs for the area of study with respect to the road environment and driving context. For automation to lead to more efficient, in addition to safer, traffic, a vehicle with the All-knowing driving logic predicts the behaviour of all road users detected by all connected detectors, on both vehicles and the infrastructure.
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