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Institutional Repository [SANDBOX]
Technical University of Crete
Technical University of Crete
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| URI: | http://purl.tuc.gr/dl/dias/346FD646-FC99-4B15-868D-11207B03B4B5 | ||
| Year | 2022 | ||
| Type of Item | Conference Full Paper | ||
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| Bibliographic Citation | M. Malekzadeh, D. Manolis, I. Papamichail and M. Papageorgiou, "Empirical investigation of properties of lane-free automated vehicle traffic," in Proceedings of the 2022 IEEE 25th International Conference on Intelligent Transportation Systems (ITSC 2022), Macau, China, 2022, pp. 2393-2400, doi: 10.1109/ITSC55140.2022.9921864. https://doi.org/10.1109/ITSC55140.2022.9921864 | ||
| Appears in Collections |
A new traffic paradigm has been recently proposed for automated vehicles, characterized by two combined principles: lane-free roads and vehicle nudging; the latter implying that vehicles may be influenced (nudged) by other vehicles around and even behind them. This paper presents and employs an ad-hoc vehicle movement strategy for Connected and Automated Vehicles (CAVs) driving in a lane-free environment, to investigate empirically (via simulation) some properties of the new traffic paradigm, such as the emerging fundamental diagram, traffic flow capacity, the impact of vehicle nudging, the impact of road width and more. The vehicle movement strategy is inspired by an adaptive cruise control scheme, albeit with significant modifications to account for lane-free driving, nudging, and respect of road boundaries. The movement strategy relies on real-time information to decide on longitudinal and lateral accelerations. Specifically, an “aura” is defined around each vehicle that depends on the vehicle dimensions, position, and relative speeds with surrounding vehicles. Virtual forces from surrounding vehicles are activated if these vehicles intersect with the corresponding aura. The proposed vehicle movement strategy is employed for traffic simulation on a ring-road, using a recently developed microscopic simulator called TrafficFluid-Sim, which builds on the SUMO simulation infrastructure. The achieved results demonstrate: safe (crash-free) driving at all densities; high traffic flows and capacity; increase of traffic flows and capacity via vehicle nudging; as well as via small road widening.
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