Investigating the Potential Transportation Impacts of Connected and Autonomous Vehicles

Asadi, F. Elham; Anwar, Ammar K.; Miles, J C

doi:10.1109/iccve45908.2019.8964994

Cited by 6 publications

(20 citation statements)

References 5 publications

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“…Along similar lines, by adapting the psychophysical Wiedemann 74 and 99 car following models in VISSIM, various other studies were carried out for different test scenarios to understand the impacts of AVs. ese studies included congested networks [82], traffic signals [83], roadway capacity [84], traffic stream characteristics [85], free speeds [86], operational performance [87], emission impacts [88], safety performance [89], unsignalized intersections [90,91], and transitional impacts [92]. Other studies have adapted the inbuilt Krauss model in SUMO [93,94] to model AVs.…”

Section: Av Modeling By Inbuilt Modelsmentioning

confidence: 99%

Evolution of Traffic Microsimulation and Its Use for Modeling Connected and Automated Vehicles

Raju

Farah

2021

Journal of Advanced Transportation

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Traffic microsimulation has a functional role in understanding the traffic performance on the road network. This study originated with intent to understand traffic microsimulation and its use in modeling connected and automated vehicles (CAVs). Initially, the paper focuses on understanding the evolution of traffic microsimulation and on examining the various commercial and open-source simulation platforms available and their importance in traffic microsimulation studies. Following this, current autonomous vehicle (AV) microsimulation strategies are reviewed. From the review analysis, it is observed that AVs are modeled in traffic microsimulation with two sets of strategies. In the first set, the inbuilt models are used to replicate the driving behavior of AVs by adapting the models’ parameters. In the second strategy, AV behavior is programmed with the help of externalities (e.g., Application Programming Interface (API)). Studies simulating AVs with inbuilt models used mostly VISSIM compared to other microsimulation platforms. In addition, the studies are heavily focused on AVs’ penetration rate impact on traffic flow characteristics and traffic safety. On the other hand, studies which simulated AVs with externalities focused on the communication aspects for traffic management. Finally, the cosimulation strategies for simulating the CAVs are explored, and the ongoing research attempts are discussed. The present study identifies the limitations of present CAV microsimulation studies and proposes prospects and improvements in modeling AVs in traffic microsimulation.

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Section: Av Modeling By Inbuilt Modelsmentioning

confidence: 99%

Evolution of Traffic Microsimulation and Its Use for Modeling Connected and Automated Vehicles

Raju

Farah

2021

Journal of Advanced Transportation

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“…To model this feature in Vissim, CC8 and CC9 values must be modified in the Wiedemann99 model. (3) During free flow, AVs keep their speed constant without any oscillation [25]. As such, they have a smaller speed range [21].…”

Section: Autonomous Drivingmentioning

confidence: 99%

“…Many companies are involved in the project, the most important of which are Ford, Jaguar, and the University of Cambridge. Asadi et al [25] simulated this type of vehicle in the Vissim software and achieved the results presented in Table 3 for the parameters of driving behavior.…”

Section: Autonomous Drivingmentioning

confidence: 99%

“…Asadi et al [25] thoroughly address the approximate presence time of each AV generation, which is presented in Table 4. Although these predictions may be optimistic, it can be argued that the overall forecast trend is accurate and only the start year of the presence of AVs maybe 10 to 20 years later than the scenarios presented.…”

Section: Simulation Scenariosmentioning

confidence: 99%

“…e distribution of distraction time and the angle of deviation were entered into the Vissim software. e Coexist and UK Autodrive projects were used to model the behavior of AVs and the scenarios for the market penetration rate of AVs were determined using Asadi's predictions [25]. Analyzing the results revealed that the advent of autonomous vehicles will lead to significant improvements in terms of safety at both intersections.…”

Section: Conclusion and Suggestions For Future Workmentioning

confidence: 99%

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Studying the Simultaneous Effect of Autonomous Vehicles and Distracted Driving on Safety at Unsignalized Intersections

Khashayarfard

Nassiri

2021

Journal of Advanced Transportation

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Human error is one of the leading causes of accidents. Distraction, fatigue, poor visibility, speeding, and other such errors made by drivers can cause accidents. With the rapid advancements in automation technologies, transportation planners have strived to use Intelligent Transportation Systems (ITS) to minimize human error. In this study, the effect of Autonomous Vehicles (AVs) on the number of potential conflicts at two unsignalized intersections is investigated by using a microsimulation model in PTV Vissim software. For human-driven cars, the factor that is considered for calibration is driver distraction mainly caused by reading or writing text messages on a cellphone while driving. This factor can be estimated using driving simulators. In this paper, five different scenarios were defined for simulation, in addition to the primary state, according to the different market penetration rates of AVs in Vissim. Safety assessment was performed by the Surrogate Safety Assessment Model (SSAM) using Time to Collision (TTC) and Deceleration Rate to Avoid Crashes (DRAC) indicators to determine the number of accidents. It was concluded that the presence of 100% of AVs could reduce the potential for accidents by up to 93%.

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Exploring the effects of Connected and Autonomous Vehicles on traffic safety and operation at full-cloverleaf interchanges

Khadka,

Hassan

2024

Journal of Transportation Safety & Security

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Investigating the Potential Transportation Impacts of Connected and Autonomous Vehicles

Cited by 6 publications

References 5 publications

Evolution of Traffic Microsimulation and Its Use for Modeling Connected and Automated Vehicles

Evolution of Traffic Microsimulation and Its Use for Modeling Connected and Automated Vehicles

Studying the Simultaneous Effect of Autonomous Vehicles and Distracted Driving on Safety at Unsignalized Intersections

Exploring the effects of Connected and Autonomous Vehicles on traffic safety and operation at full-cloverleaf interchanges

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