Safety evaluation of connected and automated vehicles in mixed traffic with conventional vehicles at intersections

Arvin, Ramin; Khattak, Asad J.; Kamrani, Mohsen; Rios-Torres, Jackeline

doi:10.1080/15472450.2020.1834392

Cited by 97 publications

(40 citation statements)

References 55 publications

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“…It has been shown that CAVs can significantly improve safety [19]- [21], traffic efficiency [22]- [24], traffic flow stability [11], and air quality [17], [25]. A recent comprehensive study has shown that it is important to take an adaptive approach to autonomous vehicles concerning the environmental impact.…”

Section: B Impacts Of Cavs On Network Efficiencymentioning

confidence: 99%

“…Nevertheless, incorporating shared driverless cars can significantly reduce the total travel demand [33], [36] and annual vehicle distances traveled [37], [38]. With the introduction of CAVs, an improvement in traffic can be expected through more efficient driving, congestion relief, better accident prevention with a reduction estimated to be around 90%, as well as a reduction in fuel consumption, energy, and pollution up to 40% [20], [21]. Previous research has shown that a reduction of 12−17% in fuel use can be achieved when a CAV is trailing a lead vehicle with the specific objective of minimizing accelerations and decelerations [39].…”

Section: B Impacts Of Cavs On Network Efficiencymentioning

confidence: 99%

See 1 more Smart Citation

Potential Pollutant Emission Effects of Connected and Automated Vehicles in a Mixed Traffic Flow Context for Different Road Types

Bandeira¹,

Macedo

Fernandes

et al. 2021

IEEE Open J. Intell. Transp. Syst.

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The environmental impact of connected and autonomous vehicles (CAVs) is still uncertain. Little is known about how CAVs operational behavior influences the environmental performance of network traffic, including conventional vehicles (CVs). In this paper, a microscopic traffic and emission modeling platform was applied to simulate CAVs operation in Motorway, Rural, and Urban road sections of a medium-sized European city, assuming different configurations of the car-following model parameters associated with a pre-determined or cooperative adaptative behavior of the CAVs. The main contribution is to evaluate the impact of the CAVs operation on the distribution of accelerations, Vehicle Specific Power (VSP) modal distribution, carbon dioxide (CO2) and nitrogen oxides (NOx) emissions for different road types and Market Penetration Rates (MPR). Results suggest CAVs operational behavior can affect CVs environmental performance either positively or negatively, depending on the driving settings and road type. It was found network-wide CO2 varies between savings of 18% and an increase of 4%, depending on the road type and MPR. CAVs adjusted driving settings allowed minimization of system NOx up to 13-23% for MPR ranging between 10 and 90%. These findings may support policymakers and traffic planners in developing strategies to better accommodate CAVs in a sustainable way.

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Section: B Impacts Of Cavs On Network Efficiencymentioning

confidence: 99%

Section: B Impacts Of Cavs On Network Efficiencymentioning

confidence: 99%

Potential Pollutant Emission Effects of Connected and Automated Vehicles in a Mixed Traffic Flow Context for Different Road Types

Bandeira¹,

Macedo

Fernandes

et al. 2021

IEEE Open J. Intell. Transp. Syst.

View full text Add to dashboard Cite

show abstract

“…Ye et al [7] analysed the dynamic evolution law of traffic flow under heterogeneous flow scenarios with different penetration rates of autonomous. Kerschbaumer et al [8], Yao et al [9], and Arvin et al [10] described driving behaviours of vehicles with different categories and levels through different models, and based on Vissim, analysed the interaction process of vehicles with different permeability under various road sections and special conditions.…”

Section: Introductionmentioning

confidence: 99%

Mechanism of Road Capacity under Different Penetration Scenarios of Autonomous Vehicles

Zhang¹,

Duan²,

Zhang³

et al. 2022

Int. j. simul. model.

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This paper takes L0 (ordinary vehicles), L2 and L4 (autonomous vehicles) as the research objects, adopts different car-following rules and improves them respectively based on driver's personality factors and variable time headway (VTH) strategy, introduces a benefit parameters to distinguish lane changing ability of them, and evaluates road capacity under mixed traffic flow with a basic diagram model and average travel time. Use SUMO to build a simulation platform and conduct a real-time systematic research based on Python. The results prove that: (1) After the penetration rate of autonomous exceeds 60 %, road capacity can be effectively improved, and the maximum increase of 32.52 % occurs in 100 % penetration scenario. (2) When traffic density is less than 27 vehicles/km, the average speed continues to be the maximum in 100 % scenario, and when it is greater than 27 vehicles/km, the critical penetration scenario is 80 %. (3) The average travel time begins to decrease after the penetration rate exceeds 20 %, and can be reduced by 23.38 % in 100 % scenario. It shows that traffic efficiency is closely associated with penetration rates of autonomous vehicles.

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“…However, the safety benefits of CAVs are not proportional to CAV penetration (Sinha et al , 2021). At low levels of CAV penetration rate, the safety improvements were found to be marginal (Arvin et al , 2021). Full-scale benefits of CAVs can only be achieved at 100% CAV penetration.…”

Section: Introductionmentioning

confidence: 99%

Traffic signal coordination control for arterials with dedicated CAV lanes

Xu¹,

Jin

2022

JICV

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Purpose This study aims to make full use of the advantages of connected and autonomous vehicles (CAVs) and dedicated CAV lanes to ensure all CAVs can pass intersections without stopping. Design/methodology/approach The authors developed a signal coordination model for arteries with dedicated CAV lanes by using mixed integer linear programming. CAV non-stop constraints are proposed to adapt to the characteristics of CAVs. As it is a continuous problem, various situations that CAVs arrive at intersections are analyzed. The rules are discovered to simplify the problem by discretization method. Findings A case study is conducted via SUMO traffic simulation program. The results show that the efficiency of CAVs can be improved significantly both in high-volume scenario and medium-volume scenario with the plan optimized by the model proposed in this paper. At the same time, the progression efficiency of regular vehicles is not affected significantly. It is indicated that full-scale benefits of dedicated CAV lanes can only be achieved with signal coordination plans considering CAV characteristics. Originality/value To the best of the authors’ knowledge, this is the first research that develops a signal coordination model for arteries with dedicated CAV lanes.

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Safety evaluation of connected and automated vehicles in mixed traffic with conventional vehicles at intersections

Cited by 97 publications

References 55 publications

Potential Pollutant Emission Effects of Connected and Automated Vehicles in a Mixed Traffic Flow Context for Different Road Types

Potential Pollutant Emission Effects of Connected and Automated Vehicles in a Mixed Traffic Flow Context for Different Road Types

Mechanism of Road Capacity under Different Penetration Scenarios of Autonomous Vehicles

Traffic signal coordination control for arterials with dedicated CAV lanes

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