Isolated intersection control for various levels of vehicle technology: Conventional, connected, and automated vehicles

Yang, Kaidi; Guler, S. Ilgin; Menéndez, Mónica

doi:10.1016/j.trc.2016.08.009

Cited by 234 publications

(150 citation statements)

References 27 publications

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“…Their simulations revealed a decrease by up to 60% in the average delay per car when the penetration rate of the control system-equipped vehicles increased by up to 60%. These researchers reported further decrease of the delays by an improved version of their intersection controller (Yang, Guler, & Menendez, 2016). Chen, Bell, and Bogenberger (2010) proposed a navigation algorithm for automated vehicles that accounts not only for travel time but also for travel time reliability.…”

Section: Literature Resultsmentioning

confidence: 99%

Policy and society related implications of automated driving: A review of literature and directions for future research

Milakis

Arem

Wee

2017

Journal of Intelligent Transportation Systems

700

383

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KEYWORDSautomated driving; first, second, and third order impacts; policy and societal implications; ripple effect ABSTRACTIn this paper, the potential effects of automated driving that are relevant to policy and society are explored, findings discussed in literature about those effects are reviewed and areas for future research are identified. The structure of our review is based on the ripple effect concept, which represents the implications of automated vehicles at three different stages: first-order (traffic, travel cost, and travel choices), second-order (vehicle ownership and sharing, location choices and land use, and transport infrastructure), and third-order (energy consumption, air pollution, safety, social equity, economy, and public health). Our review shows that first-order impacts on road capacity, fuel efficiency, emissions, and accidents risk are expected to be beneficial. The magnitude of these benefits will likely increase with the level of automation and cooperation and with the penetration rate of these systems. The synergistic effects between vehicle automation, sharing, and electrification can multiply these benefits. However, studies confirm that automated vehicles can induce additional travel demand because of more and longer vehicle trips. Potential land use changes have not been included in these estimations about excessive travel demand. Other third-order benefits on safety, economy, public health and social equity still remain unclear. Therefore, the balance between the short-term benefits and long-term impacts of vehicle automation remains an open question.

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Section: Literature Resultsmentioning

confidence: 99%

Policy and society related implications of automated driving: A review of literature and directions for future research

Milakis

Arem

Wee

2017

Journal of Intelligent Transportation Systems

700

383

View full text Add to dashboard Cite

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“…Since flow on a link cannot be directly observed by RSUs, the use of RSUs to determine link flows includes two steps. The first step is to estimate the flow on an observed link using shockwave theory and car following models on the basis of the position and speed information of each connected vehicle on that link (Yang, Guler, & Menendez, ). The second step is to infer the flow on unobserved links using node‐link flow conservation equations on the basis of observed link flows.…”

Section: Problem Statementmentioning

confidence: 99%

Road side unit location optimization for optimum link flow determination

Liang

2019

Computer aided Civil Eng

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This study addresses the problem of road side unit (RSU) location optimization for optimum link flow determination. The error of link flow determination using RSU information comes from two sources: measurement error and inference error. The inference error is caused by the propagation and accumulation of measurement error during the link flow inference process. The direct problem formulation aiming to minimize the total error is impossible because the minimization of inference error has to be indirectly formulated as the minimization of the cumulative number of unobserved links. Further, for a given number of RSU, the decrease in the cumulative number of unobserved links results in the increase of the number of observed links, and thus results in the increase of measurement error due to data packet queueing delay. Therefore, for a given RSU installation budget, the balance between the two types of error needs to be optimized in order to achieve the optimum link flow determination accuracy. To fulfill this goal, the RSU location optimization problem is formulated as a bi‐objective nonlinear binary integer programming. This programming is constrained by complete link flow determination requirements. In order to accelerate computation, an efficient ε‐constraint method is designed to generate Pareto optimal frontier. The subproblem solved at each iteration is linearized using piecewise linear approximation and solved using a constraint generation method. The proposed model and the solution algorithm are evaluated through numerical examples. The results reveal that the Pareto optimal solutions achieved by the proposed model are at least not inferior to a non‐Pareto solution obtained in the baseline scenario. Further, both the measurement error and inference error associated with some of the Pareto optimal points are lower than those associated with the non‐Pareto optimal solution.

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“…Realizing the potential long path to full vehicle automation, researchers also emphasized the possible cooperative scheme between CAVs and HVs by strategically consider the following HVs for intersection management [10]. A bi-level optimal intersection control algorithm was proposed in [11]. The algorithm performed trajectory design for CAVs as well as the prediction for HVs based on real-time CAV data.…”

Section: ) Effectiveness Of Aidsmentioning

confidence: 99%

Alternative Intersection Designs with Connected and Automated Vehicle

Zhong

Lee

2019

2019 IEEE 2nd Connected and Automated Vehicles Symposium (CAVS)

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Alternative intersection designs (AIDs) can improve the performance of an intersection by not only reducing the number of signal phases but also change the configuration of the conflicting points by re-routing traffic. However the AID studies have rarely been extended to Connected and Automated Vehicle (CAV) which is expected to revolutionize our transportation system. In this study, we investigate the potential benefits of CAV to two AIDs: the diverging diamond interchange (DDI) and the restricted crossing U-turn intersection. The potential enhancements of AID, CAV, and the combination of both are quantified via microscopic traffic simulation. We found that CAV is able to positively contribute to the performance of an intersection. However, converting an existing conventional diamond interchange (CDI) to a diverging one is a more effective way according to the simulation results. DDI improves the throughput of a CDI by 950 vehicles per hour, a near 20% improvement; whereas with full penetration of CAV, the throughput of a CDI is increased only by 300 vehicles per hour. A similar trend is observed in the average delay per vehicle as well. Furthermore, we assess the impact for the driver's confusion, a concern for deploying AIDs, on the traffic flow. According to the ANOVA test, the negative impacts of driver's confusion are of statistical significance.

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Isolated intersection control for various levels of vehicle technology: Conventional, connected, and automated vehicles

Cited by 234 publications

References 27 publications

Policy and society related implications of automated driving: A review of literature and directions for future research

Policy and society related implications of automated driving: A review of literature and directions for future research

Road side unit location optimization for optimum link flow determination

Alternative Intersection Designs with Connected and Automated Vehicle

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