Influences of Single-Lane Automatic Driving Systems on Traffic Efficiency and CO2 Emissions on China’s Motorways

Song, Haokun; Zhao, Fuquan; Liu, Zongwei

doi:10.3390/app112211032

Cited by 4 publications

(19 citation statements)

References 17 publications

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“…It is worth mentioning that AVs can have cautious or aggressive driving behaviours depending on their level of automation and their driving logic. us, Song et al [46] calibrated the CC0 value to 2.17 and 0.5 for caution CAVs and aggressive CAVs, respectively, for different roadway networks consisting of expressways and secondary motorways. Furthermore, Boualam [47] assumed 1.5 and 1.0 for simulating AAVs with cautious and aggressive driving behaviour on roundabout, respectively.…”

Section: Cc0: Standstill Distance (M)mentioning

confidence: 99%

“…In 2020, Liu and Fan [53], using a method of genetic algorithm, found a calibrated value of 1.2 for CAVs in four-lane basic freeway segments. In 2021, Song et al calibrated the CC1 value to 1.70 and 0.5 for caution CAVs and aggressive CAVs for roadway networks consisting of arterial highways and secondary motorways in China [46]. Above and beyond, Rao et al adjusted CC1 to 1.20 for simulating AAVs in freeway networks with different geometric characteristics [39].…”

Section: Cc1: Headway Time (S)mentioning

confidence: 99%

“…Song et al considered a CC2 value of 1.00 for both caution CAVs and aggressive CAVs in different road networks comprised of arterial highways and secondary motorways [46]. Besides, the value was set to 2.0 for assessing the safety impacts of AAVs on multilane freeway segments [43].…”

Section: Advances In Civil Engineeringmentioning

confidence: 99%

“…Recently, in 2022, Postigo et al [48] assumed a narrower range, which is from −10.0 to −6.0 for simulating AAVs impacts on motorway traffic. Similarly, Song et al considered a CC3 value to −3.33 caution CAVs and −1.00 for aggressive CAVs in different road networks comprised of arterial highways and secondary motorways [46]. Quite different from the abovementioned studies, Lee et al set the CC3 value to 0.0 for CAVs in a four-lane freeway [44,51].…”

Section: Cc3: Reshold Formentioning

confidence: 99%

“…In 2018, Budan et al [54] assumed a value −0.05/0.05 m for the simulation of CAVs on urban road intersections. In the studies [51] for CAVs in a four-lane freeway and the studies [29,44,46] that simulated CAVs in a roadway with diverse geometric configuration and traffic conditions, CC4/CC5 was adjusted to 0.0/0.0.…”

Section: Cc4/cc5: Negative/positive Following Reshold (M/s)mentioning

confidence: 99%

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How PTV Vissim Has Been Calibrated for the Simulation of Automated Vehicles in Literature?

Beza

Zefreh

Török

et al. 2022

Advances in Civil Engineering

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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.

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Section: Cc0: Standstill Distance (M)mentioning

confidence: 99%

Section: Cc1: Headway Time (S)mentioning

confidence: 99%

Section: Advances In Civil Engineeringmentioning

confidence: 99%

Section: Cc3: Reshold Formentioning

confidence: 99%

Section: Cc4/cc5: Negative/positive Following Reshold (M/s)mentioning

confidence: 99%

See 3 more Smart Citations

How PTV Vissim Has Been Calibrated for the Simulation of Automated Vehicles in Literature?

Beza

Zefreh

Török

et al. 2022

Advances in Civil Engineering

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Impacts of Connected and Autonomous Vehicles with Level 2 Automation on Traffic Efficiency and Energy Consumption

Song

Zhao

Zhu

et al. 2023

Journal of Advanced Transportation

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Evaluating the economic benefits of traffic optimization from connected and autonomous vehicles (CAVs) and relevant traffic organization methods is significant, which will help to put forward suggestions for policymakers to promote the application of CAVs. The impacts and related benefits from CAVs with level 2 automation (L2 CAVs) on traffic efficiency and energy consumption of expressways are analyzed in this paper. Average travel time and actual road capacity are on behalf of traffic efficiency while average electric energy consumption is used to compute traffic energy consumption. The corresponding traffic economic benefits consist of travel-time-saving benefits, road construction benefits, and energy-saving benefits. A benefit evaluation framework is newly proposed and microscopic traffic simulation software is applied as the experiment platform. Different market penetration rates of L2 CAVs and various traffic flow statuses are considered. Besides, dedicated lanes for CAVs are also involved in this research, which are regarded as a traffic organization method expected to promote the realization of CAV’s traffic benefits. It is found that L2 CAVs can save the average travel time and reduce average energy consumption for a single vehicle in most scenes. However, negative impacts on energy consumption are observed in several scenes due to the increase of actual road capacity. Positive economic benefits are obtained as soon as the traffic flow rate is out of saturation, which become increasingly higher as CAV’s market penetration rate turns larger. Additionally, amplification in traffic economic benefits appears only if CAV lanes are provided under proper conditions.

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The Impact of Automated Vehicles on Road and Intersection Capacity

Zhang

et al. 2023

Applied Sciences

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With the rapid development of autonomous driving technology, future road traffic must be composed of autonomous vehicles and artificial vehicles. Although autonomous vehicles have greatly improved road capacity, few studies have involved capacity at signal-controlled intersections, and most of the studies are based on experimental simulation. As such, there is a need to more scientifically analyze the impact of autonomous vehicles on road and intersection capacity. Based on three theories of flow-density relationships, traffic flow equilibrium analysis, and the following model, this paper firstly deduces the flow-density relationship of different vehicle types in a single environment. Secondly, flow-density relationships under different proportions of self-driving vehicles are derived. Through the derivation of these two models, the basic road saturation flow rates under different permeabilities of self-driving vehicles, can be obtained. Based on these results, a revised calculation model for the capacity of signalized intersections with different proportions of autonomous vehicles is proposed, which is essentially to revise the basic saturation flow rate under different permeabilities of autonomous vehicles. By using SUMO 1.15.0 traffic simulation software, the theoretical models are individually tested. The results show that the error rate between the theoretical calculation results and the SUMO simulation results, is less than 16%. This study can provide a basis for the calculation of basic capacity of roads and intersections in a future man-machine hybrid driving environment, and provide theoretical guidance for traffic management and control.

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Influences of Single-Lane Automatic Driving Systems on Traffic Efficiency and CO2 Emissions on China’s Motorways

Cited by 4 publications

References 17 publications

How PTV Vissim Has Been Calibrated for the Simulation of Automated Vehicles in Literature?

How PTV Vissim Has Been Calibrated for the Simulation of Automated Vehicles in Literature?

Impacts of Connected and Autonomous Vehicles with Level 2 Automation on Traffic Efficiency and Energy Consumption

The Impact of Automated Vehicles on Road and Intersection Capacity

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