Women — Left Turn! | ScienceGate

Through movement capacity is an essential factor used to reflect intersection performance, especially for signalized intersections, where a large proportion of vehicle demand is making through movements. Generally, left-turn spillback is considered a key contributor to affect through movement capacity, and blockage to the left-turn bay is known to decrease left-turn capacity. Previous studies have focused primarily on estimating the through movement capacity under a lagging protected only left-turn (lagging POLT) signal setting, as a left-turn spillback is more likely to happen under such a condition. However, previous studies contained assumptions (e.g., omit spillback), or were dedicated to one specific signal setting. Therefore, in this study, through movement capacity models based on probabilistic modeling of spillback and blockage scenarios are established under four different signal settings (i.e., leading protected only left-turn [leading POLT], lagging left-turn, protected plus permitted left-turn, and permitted plus protected left-turn). Through microscopic simulations, the proposed models are validated, and compared with existing capacity models and the one in the Highway Capacity Manual (HCM). The results of the comparisons demonstrate that the proposed models achieved significant advantages over all the other models and obtained high accuracies in all signal settings. Each proposed model for a given signal setting maintains consistent accuracy across various left-turn bay lengths. The proposed models of this study have the potential to serve as useful tools, for practicing transportation engineers, when determining the appropriate length of a left-turn bay with the consideration of spillback and blockage, and the adequate cycle length with a given bay length.

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Experimental Validation on Intersection Turning Trajectory Prediction Method for Advanced Driver Assistance System Based on Triclothoidal Curve

Applied Sciences ◽

10.3390/app11135900 ◽

2021 ◽

Vol 11 (13) ◽

pp. 5900

Author(s):

Yohei Fujinami ◽

Pongsathorn Raksincharoensak ◽

Shunsaku Arita ◽

Rei Kato

Keyword(s):

Traffic Accidents ◽

Computational Cost ◽

Prediction Method ◽

Smooth Curve ◽

Assistance System ◽

Driver Assistance ◽

Driver Assistance Systems ◽

Trajectory Prediction ◽

Left Turn ◽

Left Hand

Advanced driver assistance systems (ADAS) for crash avoidance, when making a right-turn in left-hand traffic or left-turn in right-hand traffic, are expected to further reduce the number of traffic accidents caused by automobiles. Accurate future trajectory prediction of an ego vehicle for risk prediction is important to activate the assistance system correctly. Our objectives are to propose a trajectory prediction method for ADAS for safe intersection turnings and to evaluate the effectiveness of the proposed prediction method. Our proposed curve generation method is capable of generating a smooth curve without discontinuities in the curvature. By incorporating the curve generation method into the vehicle trajectory prediction, the proposed method could simulate the actual driving path of human drivers at a low computational cost. The curve would be required to define positions, angles, and curvatures at its initial and terminal points. Driving experiments conducted at real city traffic intersections proved that the proposed method could predict the trajectory with a high degree of accuracy for various shapes and sizes of the intersections. This paper also describes a method to determine the terminal conditions of the curve generation method from intersection features. We set a hypothesis where the conditions can be defined individually from intersection geometry. From the hypothesis, a formula to determine the parameter was derived empirically from the driving experiments. Public road driving experiments indicated that the parameters for the trajectory prediction could be appropriately estimated by the obtained empirical formula.

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Evaluation and Analysis of CFI Schemes with Different Length of Displaced Left-Turn Lanes with Entropy Method

Sustainability ◽

10.3390/su13126917 ◽

2021 ◽

Vol 13 (12) ◽

pp. 6917

Author(s):

Binghong Pan ◽

Shasha Luo ◽

Jinfeng Ying ◽

Yang Shao ◽

Shangru Liu ◽

...

Keyword(s):

Fuel Consumption ◽

Heavy Traffic ◽

Efficiency Index ◽

Entropy Method ◽

Sustainable Transportation ◽

Assessment Model ◽

Left Turn ◽

Traffic Demand ◽

Traffic Efficiency ◽

Multi Attribute Decision Making

As an unconventional design to alleviate the conflict between left-turn and through vehicles, Continuous Flow Intersection (CFI) has obvious advantages in improving the sustainability of roadway. So far, the design manuals and guidelines for CFI are not enough sufficient, especially for the displaced left-turn lane length of CFI. And the results of existing research studies are not operational, making it difficult to put CFI into application. To address this issue, this paper presents a methodological procedure for determination and evaluation of displaced left-turn lane length based on the entropy method considering multiple performance measures for sustainable transportation, including traffic efficiency index, environment effect index and fuel consumption. VISSIM and the surrogate safety assessment model (SSAM) were used to simulate the operational and safety performance of CFI. The multi-attribute decision-making method (MADM) based on an entropy method was adopted to determine the suitability of the CFI schemes under different traffic demand patterns. Finally, the procedure was applied to a typical congested intersection of the arterial road with heavy traffic volume and high left-turn ratio in Xi’an, China, the results showed the methodological procedure is reasonable and practical. According to the results, for the studied intersection, when the Volume-to-Capacity ratio (V/C) in the westbound and eastbound lanes is less than 0.5, the length of the displaced left-turn lanes can be selected in the range of 80 to 170 m. Otherwise, other solutions should be considered to improve the traffic efficiency. The simulation results of the case showed CFI can significantly improve the traffic efficiency. In the best case, compared with the conventional intersection, the number of vehicles increases by 13%, delay, travel time, number of stops, CO emission, and fuel consumption decrease by 41%, 29%, 25%, 17%, and 17%, respectively.

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Impact of Turning Lane Storage Length and Turning Proportions on Throughput at Oversaturated Signalized Intersections

Transportation Research Record Journal of the Transportation Research Board ◽

10.1177/03611981211017139 ◽

2021 ◽

pp. 036119812110171

Author(s):

A. M. Tahsin Emtenan ◽

Christopher M. Day

Keyword(s):

Flow Rate ◽

Cycle Length ◽

Signal Timing ◽

Real World Data ◽

Left Turn ◽

Common Response ◽

Cycle Lengths ◽

Saturation Flow Rate ◽

Saturation Flow ◽

Timing Strategies

During oversaturated conditions, common objectives of signal timing are to maximize vehicle throughput and manage queues. A common response to increases in vehicle volumes is to increase the cycle length. Because the clearance intervals are displayed less frequently with longer cycle lengths and fewer cycles, more of the total time is used for green indications, which implies that the signal timing is more efficient. However, previous studies have shown that throughput reaches a peak at a moderate cycle length and extending the cycle length beyond this actually decreases the total throughput. Part of the reason for this is that spillback caused by the turning traffic may cause starvation of the through lanes resulting in a reduction of the saturation flow rate within each lane. Gaps created by the turning traffic after a lane change may also reduce the saturation flow rate. There is a relationship between the proportions of turning traffic, the storage length of turning lanes, and the total throughput that can be achieved on an approach for a given cycle length and green time. This study seeks to explore this relationship to yield better signal timing strategies for oversaturated operations. A microsimulation model of an oversaturated left-turn movement with varying storage lengths and turning proportions is used to determine these relationships and establish a mathematical model of throughput as a function of the duration of green, storage length, and turning proportion. The model outcomes are compared against real-world data.

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