<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>By designing road infrastructure, it is necessary to adapt the real situation to current development trends and respond accordingly to the intensity of traffic on the transport network. The development of the traffic situation is generally very dynamic, difficult to predict and influenced by a number of other factors. Modern technologies enable adaptive traffic flow management based on the sharing and evaluation of traffic information obtained in real time from traffic monitoring systems or even from vehicles as such (e.g. thanks to “Connected Vehicles” technology). The article first carries out a literature review of professional literature and scientific articles dealing with the issue of autonomous mobility and autonomous management of transport processes. That is followed by a description and creation of own algorithm for autonomous control of vehicles at the level crossing, including description of used data, methods and proposed solutions. Finally, the developed method (algorithm) is tested by the Anylogic simulation program in a real environment, as a case study of autonomous vehicle decision-making at the level crossing.</p>
</abstract>

By designing road infrastructure, it is necessary to adapt the real situation to current development trends and respond accordingly to the intensity of traffic on the transport network. The development of the traffic situation is generally very dynamic, difficult to predict and influenced by a number of other factors. Modern technologies enable adaptive traffic flow management based on the sharing and evaluation of traffic information obtained in real time from traffic monitoring systems or even from vehicles as such (e.g. thanks to “Connected Vehicles” technology). The article first carries out a literature review of professional literature and scientific articles dealing with the issue of autonomous mobility and autonomous management of transport processes. That is followed by a description and creation of own algorithm for autonomous control of vehicles at the level crossing, including description of used data, methods and proposed solutions. Finally, the developed method (algorithm) is tested by the Anylogic simulation program in a real environment, as a case study of autonomous vehicle decision-making at the level crossing.

Simulation of Autonomous Mobility of Connected Vehicles in the Context of Real Conditions – a Case Study

LOGI – Scientific Journal on Transport and Logistics

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

By designing road infrastructure, it is necessary to adapt the real situation to current development trends and respond accordingly to the intensity of traffic...

Simulation of Autonomous Mobility of Connected Vehicles in the Context of Real Conditions – a Case Study

Online veröffentlicht: 04. Dez. 2021

Seitenbereich: 226 - 237

Eingereicht: 10. Nov. 2021

Akzeptiert: 25. Nov. 2021

DOI: https://doi.org/10.2478/logi-2021-0021

Schlüsselwörter
Autonomous mobility, connected vehicles, simulation, traffic density, traffic flow

© 2021 Jiří Hanzl et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Simulation of Autonomous Mobility of Connected Vehicles in the Context of Real Conditions – a Case Study

Online veröffentlicht: 04. Dez. 2021

Seitenbereich: 226 - 237

Eingereicht: 10. Nov. 2021

Akzeptiert: 25. Nov. 2021

DOI: https://doi.org/10.2478/logi-2021-0021

SchlüsselwörterAutonomous mobility, connected vehicles, simulation, traffic density, traffic flow

© 2021 Jiří Hanzl et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Schlüsselwörter
Autonomous mobility, connected vehicles, simulation, traffic density, traffic flow