Traffic Signal Timing and Trajectory Optimization in a Mixed Autonomy Traffic Stream

Tajalli, Mehrdad; Hajbabaie, Ali

doi:10.1109/tits.2021.3058193

Cited by 53 publications

(39 citation statements)

References 47 publications

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“…However, some studies indicated that the effective combination of both methods is complex and requires significant efforts to develop methods that can balance computational complexity and control performance. For example, it is not likely that a centralized unit can handle all the required computations to cooperate between the signal controller and approaching vehicles (Tajalli & Hajbabaie, 2021). The findings from this review indicated that the applications of both autonomous or hybrid-based methods are built on some different assumptions, requirements, and constraints.…”

Section: Hybrid Based Methodsmentioning

confidence: 99%

“…This combination can significantly improve signalized intersection performance. For example, optimizing the arrival time of the vehicles to the intersection may result in better utilization of green durations (Tajalli & Hajbabaie, 2021). Another example, when the signal plans are identified, the desired speed of the AVs can be optimized to ensure that they can cross the intersection without stopping (Liang et al, 2019).…”

Section: Hybrid Based Methodsmentioning

confidence: 99%

“…Also, to collect the required information, different supported roadside units at each intersection must be installed. For example, most proposed autonomous or hybrid-based methods require various sensors to detect traffic information (Tajalli & Hajbabaie, 2021). Other methods have used different prediction models, such as kinematic wave theory and Newell's carfollowing model, to predict the information of the RVs, such as their arrival sequence and trajectories.…”

Section: Road Infrastructuresmentioning

confidence: 99%

“…To solve the related issues, some of the proposed methods have assumed specific operational configurations. A method is applied when left-turn movements operate exclusively (Tajalli & Hajbabaie, 2021). Another method assumed only one-way traffic without turning movements (Baz et al, 2020).…”

Section: Intersection and Functional Network Designmentioning

confidence: 99%

See 3 more Smart Citations

Signalized Intersection Control in Mixed Autonomous and Regular Vehicles Traffic Environment—A Critical Review Focusing on Future Control

et al. 2022

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The recent advancement in industrial technology has offered new opportunities to overcome different problems of stochastic driving behavior of humans through effective implementation of autonomous vehicles (AVs). Optimum utilization of driving behavior and advanced capabilities of the AVs has enabled researchers to propose autonomous cooperative-based methods for signalized intersection control under an AV traffic environment. In the future, AVs will share road networks with regular vehicles (RVs), representing a dynamic mixed traffic environment of two groups of vehicles with different characteristics. Without compromising the safety and level of service, traffic operation and control of such a complex environment is a challenging task. The current study includes a comprehensive review focused on the signalized intersection control methods under a mixed traffic environment. The different proposed methods in the literature are based on certain assumptions, requirements, and constraints mainly associated with traffic composition, connectivity, road infrastructures, intersection, and functional network design. Therefore, these methods should be evaluated with appropriate consideration of the underlying assumptions and limitations. This study concludes that the application of adaptive traffic signal control can effectively optimize traffic signal plans for variations of AV traffic environments. However, artificial intelligence approaches primarily focusing on reinforcement learning should be considered to better utilization of the improved AV characteristics.

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Section: Hybrid Based Methodsmentioning

confidence: 99%

Section: Hybrid Based Methodsmentioning

confidence: 99%

Section: Road Infrastructuresmentioning

confidence: 99%

Section: Intersection and Functional Network Designmentioning

confidence: 99%

See 2 more Smart Citations

Signalized Intersection Control in Mixed Autonomous and Regular Vehicles Traffic Environment—A Critical Review Focusing on Future Control

et al. 2022

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“…Several studies have incorporated connected vehicle (CV) data to develop traffic signal control systems in recent years ( 1 – 6 ); however, relying solely on CV data may not provide the desired level of accuracy in estimating traffic state (i.e., congestion level around the intersection) to make proper signal timing plans when CV market penetration rate is low ( 7 , 8 ). As such, recent studies have used secondary sources of data (i.e., inductive loop detector data) to improve traffic state estimation.…”

mentioning

confidence: 99%

Effects of Connectivity and Traffic Observability on an Adaptive Traffic Signal Control System

Islam

Tajalli

Mohebifard

et al. 2021

Transportation Research Record

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The effectiveness of adaptive signal control strategies depends on the level of traffic observability, which is defined as the ability of a signal controller to estimate traffic state from connected vehicle (CV), loop detector data, or both. This paper aims to quantify the effects of traffic observability on network-level performance, traffic progression, and travel time reliability, and to quantify those effects for vehicle classes and major and minor directions in an arterial corridor. Specifically, we incorporated loop detector and CV data into an adaptive signal controller and measured several mobility- and event-based performance metrics under different degrees of traffic observability (i.e., detector-only, CV-only, and CV and loop detector data) with various CV market penetration rates. A real-world arterial street of 10 intersections in Seattle, Washington was simulated in Vissim under peak hour traffic demand level with transit vehicles. The results showed that a 40% CV market share was required for the adaptive signal controller using only CV data to outperform signal control with only loop detector data. At the same market penetration rate, signal control with CV-only data resulted in the same traffic performance, progression quality, and travel time reliability as the signal control with CV and loop detector data. Therefore, the inclusion of loop detector data did not further improve traffic operations when the CV market share reached 40%. Integrating 10% of CV data with loop detector data in the adaptive signal control improved traffic performance and travel time reliability.

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Trajectory Controlling and Collision Warning Device Based on Self‐Healing and Conductive Castor Oil‐Based Waterborne Polyurethane in Automated Guided Vehicles

Shen

Lei

Long

et al. 2023

Adv Funct Materials

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Sustainable castor oil-based waterborne polyurethanes (WPUs) are widely applied in multiple fields, while the strategies to simultaneously realize reprocessing, self-healing, and novel applications are attractive and highly demanded. Herein, a molecular design strategy is proposed to incorporate dynamic oxime-carbamate bonds into the castor oil-based WPUs. The obtained networks exhibit excellent toughness (>44 MPa), adequate stretchability, and wonderful self-healing efficiency (>95% at 80 °C for 8 h), which stand out among the reported cases. Moreover, the WPU film retained almost 100% of the original mechanical properties after consecutive reprocessing. With the incorporation of carbon nanotubes, the films are endowed with good electric conductivity, providing a general platform for fabricating flexible electronic devices. Specifically, wonderful performance in trajectory control and collision warning is displayed, which is expected to be an alternative to minimize the utilization of expensive and complex obstacle sensors in automated guided vehicles. This study contributes to the development of sustainable and self-healing WPU-based flexible material and opens the gate for novel and identified applications.

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Traffic Signal Timing and Trajectory Optimization in a Mixed Autonomy Traffic Stream

Cited by 53 publications

References 47 publications

Signalized Intersection Control in Mixed Autonomous and Regular Vehicles Traffic Environment—A Critical Review Focusing on Future Control

Signalized Intersection Control in Mixed Autonomous and Regular Vehicles Traffic Environment—A Critical Review Focusing on Future Control

Effects of Connectivity and Traffic Observability on an Adaptive Traffic Signal Control System

Trajectory Controlling and Collision Warning Device Based on Self‐Healing and Conductive Castor Oil‐Based Waterborne Polyurethane in Automated Guided Vehicles

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