Accommodation of freeway merging in a mixed traffic environment including connected autonomous vehicles

Pakzadnia, Afshin; Roustom, Saad; Hassan, Yasser

doi:10.1139/cjce-2020-0815

Cited by 10 publications

(11 citation statements)

References 11 publications

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“…In the case if a merge vehicle merges onto the freeway right lane between lead and lag vehicles, the total gap was determined as the sum of the lead gap and lag gap plus the length of the subject vehicle divided by the vehicle speed. Because of lack of information on the exact length of test vehicles, a 4.641-m length was assumed for all vehicles based on a review of the dimensions of top-selling vehicles (Pakzadnia et al, 2021). In this chapter, driver behaviour at entrance and exit sites is qualitatively assessed based on the entire trip trajectory over the SCL and ramp along with the extracted data from NDS.…”

Section: Data Processingmentioning

confidence: 99%

Reliability Analysis of Freeway Speed Change Lanes Using Naturalistic Driving Study Data

Alyamani¹

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This research investigates and models drivers' behaviour on freeway entrance and exit ramp terminals using SHRP-2 Naturalistic Driving Study (NDS) data from 24 sites located in three different US states. The research included first a qualitative assessment of the driver speed behaviour as they navigate the ramp and acceleration/deceleration speed change lane (SCL). A trend of continuous vehicle acceleration was evident from the beginning of the ramp controlling curve that continued after merging onto the freeway right lane (FRL). A similar finding was noted at exit ramps but with deceleration behaviour from the beginning of taper-type SCL that continued after diverging onto the ramp controlling curve. It was also found that at entrance ramps, a portion of the drivers tends to merge onto the FRL on the taper after the SCL had ended on acceleration.At exit ramps, a portion of the observed drivers tends to diverge from the FRL on the taper before the beginning of the deceleration SCL, with this behaviour being dominant on the taper-type SCL.Statistical tests showed that the driver behaviour measures in general follow a normal distribution at each site. Tests of hypothesis examined the differences of different driver behaviour measures on the study sites, and it was shown that the speed and acceleration/deceleration behaviour of the drivers differs on the different sites indicating that it depends on the complete set of geometric characteristics at the site. Linear-mixed models were developed for driver behaviour parameters such as the speed, acceleration, and deceleration, to account for the repeated measures caused by repeated trips by the same drivers in the dataset. Also, the research involved conducting a reliability analysis to evaluate the performance of acceleration SCLs, taking into consideration essential factors such as driver speeds and behavior, SCL and ramp geometric design, and traffic conditions. 𝑉𝑉 𝐵𝐵𝐵𝐵𝐵𝐵𝑉𝑉 𝑀𝑀𝐵𝐵𝐵𝐵 𝑉𝑉 𝐸𝐸𝐵𝐵𝐵𝐵 𝑉𝑉 𝑀𝑀 𝐿𝐿 𝐴𝐴𝐷𝐷𝐴𝐴,𝑁𝑁 𝑎𝑎 All Data 0.000 a 0.000 a 0.000 a 0.000 a 0.000 a 0.000 a Off-Peak 0.000 a 0.000 a 0.000 a 0.008 0.000 a 0.000 a On-Peak 0.360 b 0.024 0.000 a 0.008 0.000 a 0.000 a 88.50 speed limit 0.000 a 0.000 a 0.000 a 0.000 a 0.000 a 0.000 a Taper-type SCL 0.015 0.108 b 0.001 a 0.784 b 0.000 a 0.000 a Parallel-type SCL 0.000 a 0.000 a 0.000 a 0.000 a 0.000 a 0.000 a Equality of MeanAll Data 0.000 a 0.000 a 0.000 a 0.000 a 0.000 a 0.000 a Off-Peak 0.000 a 0.000 a 0.000 a 0.000 a 0.000 a 0.000 a On-Peak 0.000 a 0.000 a 0.000 a 0.000 a 0.000 a 0.000 a 88.50 speed limit 0.000 a 0.000 a 0.000 a 0.000 a 0.000 a 0.000 a Taper-type SCL 0.011 0.000 a 0.000 a 0.967 b 0.000 a 0.000 a Parallel-type SCL 0.000 a 0.000 a 0.000 a 0.000 a 0.000 a 0.000 a

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Section: Data Processingmentioning

confidence: 99%

Reliability Analysis of Freeway Speed Change Lanes Using Naturalistic Driving Study Data

Alyamani¹

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“…As mentioned in chapter three, eight merging strategies are proposed as solutions to eliminate or reduce the conflicts expected at freeway merging due to CAV platooning in a mixed traffic environment. The eight strategies were assessed in comparison to each other and to a base condition called S0, which is a do-nothing strategy, at different CAV penetration rates based on different traffic performance measures using traffic micro-simulation (Pakzadnia et al 2021). The comparison accounted for different site conditions based on traffic volumes on the freeway and ramp and based on the entrance ramp geometric design as reflected in the ramp design speed.…”

Section: Merging Strategiesmentioning

confidence: 99%

“…• Segment 2 is selected 900 m long and divided into three (3×300 m) sub-segments to allow gradual change of vehicles' speeds or headways for S2 and S3 (Pakzadnia et al 2021).…”

Section: Study Corridor and Simulation Attributesmentioning

confidence: 99%

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Accommodation of Freeway Merging in Environment of Mixed Vehicle Technologies

Pakzadnia¹

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The connected autonomous vehicle (CAV) is the most significant breakthrough in the automobile industry since the wide adoption of automobiles as a mode of transportation. These vehicles can respond faster, drive more precisely within their lane, and keep gaps shorter than driver-operated vehicles (DVs). Therefore, they can improve traffic operations and reduce collisions resulting from human errors. However, shorter gaps on the freeway right lane (FRL) can create difficulty for on-ramp vehicles to merge onto the freeway. In addition, there is a transition period from all DVs to all CAVs. As a result, there would be a mixed traffic environment including DVs and CAVs, which might necessitate different merging management strategies.This study proposes eight possible solutions to address the merging problems by providing acceptable gaps or resolving the conflicts between merging and mainline vehicles in a mixed traffic environment. These strategies are then evaluated based on different measures to determine which merging solution is most effective for each traffic condition. Average travel times and the capacity drop are used as traffic performance measures, while safety measures include the percentage of vehicles with low merging speed (VLMS) and probability of non-compliance (PNC) of merging manoeuvre.The behaviour of CAVs and performance merging strategies are modelled using Vissim v2020, internal programing, and a MATLAB program. The simulation results indicate that when the CAV penetration rate is between 0% and 100%, most proposed strategies outperform the base condition of do-nothing. The traffic performance changes depending on the CAV penetration rate and the type of traffic management strategy.iiiThe results of the safety measure for most strategies based on the VLMS index indicate that at low traffic volumes, increasing CAV penetration rate reduces VLMS, thereby improving safety. At high traffic volume, some strategies such as dissolving platoons and ramp metering show better performance. For the PNC measure, most strategies have lower PNC and better expected safety performance than the base strategy.Furthermore, increasing the CAV penetration rate reduces PNC. Finally, a regression analysis between PNC and the existing collision database demonstrated a correlation between PNC and collision frequency.

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“…The approach followed to assess the impact of CAVs on GHG emissions and fuel consumption involves traffic microsimulation of four different routes within the City of Ottawa. First, base scenarios are simulated with the vehicle fleet made entirely of conventional DOVs calibrated to local driving behaviour found in the literature (19,20).…”

Section: Frameworkmentioning

confidence: 99%

Environmental Impacts of Connected and Automated Vehicles Considering Traffic Flow and Road Characteristics

Roustom¹

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Connected and automated vehicles (CAVs) have the potential to revolutionize the transportation system by improving traffic conditions, increasing road capacities and reducing congestion and crash risks. This study aims to investigate the implications of this technology on greenhouse gas (GHG) emissions levels through traffic micro-simulations and emissions modelling. Three different driving behaviours (cautious, normal and aggressive) of CAVs are simulated along with a base driving behaviour of driver-operated vehicle (DOV) with varying traffic demands and under different network configurations to evaluate CAVs' implications. Results of this study show that aggressive CAVs can reduce large percentages of emissions compared to DOVs but can also increase emissions at situations of increased traffic demand and high congestion due to their higher acceleration rates which can cause irregular driving cycles. Analysis of the findings suggests there are optimal traffic demand levels of aggressive CAVs that can maximize the reduction of emissions relative to DOVs.

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Accommodation of freeway merging in a mixed traffic environment including connected autonomous vehicles

Cited by 10 publications

References 11 publications

Reliability Analysis of Freeway Speed Change Lanes Using Naturalistic Driving Study Data

Reliability Analysis of Freeway Speed Change Lanes Using Naturalistic Driving Study Data

Accommodation of Freeway Merging in Environment of Mixed Vehicle Technologies

Environmental Impacts of Connected and Automated Vehicles Considering Traffic Flow and Road Characteristics

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