How PTV Vissim Has Been Calibrated for the Simulation of Automated Vehicles in Literature?
Recently, in the literature, microscopic simulation is one of the most attractive methods in impact assessment of automated vehicles (AVs) on traffic flow. AVs can be divided into different categories, each having different driving characteristics. Hence, calibrating microscopic simulators for diffe...
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| Format: | Article |
| Language: | English |
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Wiley
2022-01-01
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| Series: | Advances in Civil Engineering |
| Online Access: | http://dx.doi.org/10.1155/2022/2548175 |
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| author | Abebe Dress Beza Mohammad Maghrour Zefreh Adam Torok Anteneh Afework Mekonnen |
| author_facet | Abebe Dress Beza Mohammad Maghrour Zefreh Adam Torok Anteneh Afework Mekonnen |
| author_sort | Abebe Dress Beza |
| collection | DOAJ |
| description | Recently, in the literature, microscopic simulation is one of the most attractive methods in impact assessment of automated vehicles (AVs) on traffic flow. AVs can be divided into different categories, each having different driving characteristics. Hence, calibrating microscopic simulators for different AV categories could be challenging in AVs’ impact assessment. The PTV Vissim microscopic traffic simulation software has been calibrated for simulating diverse types of AVs in a large body of literature. There are two main streams of studies in literature adapting AVs' driving behaviors in Vissim following either internal (i.e., adjusting the parameters of the Vissim's default driving behavior models) or external (i.e., adapting AVs' behavior through external VISSIM interfaces) modeling approaches. The current paper investigates how the PTV Vissim has been internally calibrated for the simulation of different types of AVs and compares the calibrated values in the literature with default values introduced in the recent version of PTV Vissim. In the present paper, the reviewed studies are partitioned into two main categories according to the characteristics of the studied AVs, the studies focused on autonomous automated vehicles (AAVs) and the ones focused on cooperative automated vehicles (CAVs). Our findings indicate that the literature expects a lower value for parameters including standstill distance (CC0), headway time (CC1), following variation (CC2), the threshold for entering “following” (CC3), negative/positive following thresholds (CC4/CC5), speed dependency of oscillation (CC6), oscillation acceleration (CC7), safety distance reduction factor (SDRF), and minimum headway front/rear (MinHW) for AVs than conventional vehicles (CVs). Besides, the literature expects higher values for parameters including standstill acceleration (CC8), acceleration at 80 km/h (CC9), looking distances, and maximum deceleration for cooperative braking (MaxDCB) for AVs. When cautious AVs are introduced, deterring effects are expected in the literature (e.g., higher CC0). Moreover, CAVs can have higher looking distance values compared with AAVs. |
| format | Article |
| id | doaj-art-92b3f89a3d9c4c5f91b7d3a26d0928d0 |
| institution | DOAJ |
| issn | 1687-8094 |
| language | English |
| publishDate | 2022-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Advances in Civil Engineering |
| spelling | doaj-art-92b3f89a3d9c4c5f91b7d3a26d0928d02025-08-20T03:20:37ZengWileyAdvances in Civil Engineering1687-80942022-01-01202210.1155/2022/2548175How PTV Vissim Has Been Calibrated for the Simulation of Automated Vehicles in Literature?Abebe Dress Beza0Mohammad Maghrour Zefreh1Adam Torok2Anteneh Afework Mekonnen3Faculty of Civil and Water Resources EngineeringKTH Royal Institute of TechnologyBME-Budapest University of Technology and EconomicsBME-Budapest University of Technology and EconomicsRecently, in the literature, microscopic simulation is one of the most attractive methods in impact assessment of automated vehicles (AVs) on traffic flow. AVs can be divided into different categories, each having different driving characteristics. Hence, calibrating microscopic simulators for different AV categories could be challenging in AVs’ impact assessment. The PTV Vissim microscopic traffic simulation software has been calibrated for simulating diverse types of AVs in a large body of literature. There are two main streams of studies in literature adapting AVs' driving behaviors in Vissim following either internal (i.e., adjusting the parameters of the Vissim's default driving behavior models) or external (i.e., adapting AVs' behavior through external VISSIM interfaces) modeling approaches. The current paper investigates how the PTV Vissim has been internally calibrated for the simulation of different types of AVs and compares the calibrated values in the literature with default values introduced in the recent version of PTV Vissim. In the present paper, the reviewed studies are partitioned into two main categories according to the characteristics of the studied AVs, the studies focused on autonomous automated vehicles (AAVs) and the ones focused on cooperative automated vehicles (CAVs). Our findings indicate that the literature expects a lower value for parameters including standstill distance (CC0), headway time (CC1), following variation (CC2), the threshold for entering “following” (CC3), negative/positive following thresholds (CC4/CC5), speed dependency of oscillation (CC6), oscillation acceleration (CC7), safety distance reduction factor (SDRF), and minimum headway front/rear (MinHW) for AVs than conventional vehicles (CVs). Besides, the literature expects higher values for parameters including standstill acceleration (CC8), acceleration at 80 km/h (CC9), looking distances, and maximum deceleration for cooperative braking (MaxDCB) for AVs. When cautious AVs are introduced, deterring effects are expected in the literature (e.g., higher CC0). Moreover, CAVs can have higher looking distance values compared with AAVs.http://dx.doi.org/10.1155/2022/2548175 |
| spellingShingle | Abebe Dress Beza Mohammad Maghrour Zefreh Adam Torok Anteneh Afework Mekonnen How PTV Vissim Has Been Calibrated for the Simulation of Automated Vehicles in Literature? Advances in Civil Engineering |
| title | How PTV Vissim Has Been Calibrated for the Simulation of Automated Vehicles in Literature? |
| title_full | How PTV Vissim Has Been Calibrated for the Simulation of Automated Vehicles in Literature? |
| title_fullStr | How PTV Vissim Has Been Calibrated for the Simulation of Automated Vehicles in Literature? |
| title_full_unstemmed | How PTV Vissim Has Been Calibrated for the Simulation of Automated Vehicles in Literature? |
| title_short | How PTV Vissim Has Been Calibrated for the Simulation of Automated Vehicles in Literature? |
| title_sort | how ptv vissim has been calibrated for the simulation of automated vehicles in literature |
| url | http://dx.doi.org/10.1155/2022/2548175 |
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