| Title |
Modeling Driver Behavior in Road Traffic Simulation |
| ID_Doc |
43037 |
| Authors |
Mecheva, T; Furnadzhiev, R; Kakanakov, N |
| Title |
Modeling Driver Behavior in Road Traffic Simulation |
| Year |
2022 |
| Published |
Sensors, 22, 24 |
| DOI |
10.3390/s22249801 |
| Abstract |
Driver behavior models are an important part of road traffic simulation modeling. They encompass characteristics such as mood, fatigue, and response to distracting conditions. The relationships between external factors and the way drivers perform tasks can also be represented in models. This article proposes a methodology for establishing parameters of driver behavior models. The methodology is based on road traffic data and determines the car-following model and routing algorithm and their parameters that best describe driving habits. Sequential and parallel implementation of the methodology through the urban mobility simulator SUMO and Python are proposed. Four car-following models and three routing algorithms and their parameters are investigated. The results of the performed simulations prove the applicability of the methodology. Based on more than 7000 simulations performed, it is concluded that in future experiments of the traffic in Plovdiv it is appropriate to use a Contraction Hierarchies routing algorithm with the default routing step and the Krauss car-following model with the default configuration parameters. |
| Author Keywords |
Intelligent Transportation Systems; Smart City; SUMO |
| Index Keywords |
Index Keywords |
| Document Type |
Other |
| Open Access |
Open Access |
| Source |
Science Citation Index Expanded (SCI-EXPANDED) |
| EID |
WOS:000904273200001 |
| WoS Category |
Chemistry, Analytical; Engineering, Electrical & Electronic; Instruments & Instrumentation |
| Research Area |
Chemistry; Engineering; Instruments & Instrumentation |
| PDF |
https://www.mdpi.com/1424-8220/22/24/9801/pdf?version=1670999088
|