Collaborative merging strategy for freeway ramp operations in a connected and autonomous vehicles environment

Xie, Yuanchang; Zhang, Huixing; Gartner, Nathan H.; Arsava, Tuğba

doi:10.1080/15472450.2016.1248288

Cited by 126 publications

(68 citation statements)

References 23 publications

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“…Several other studies have not only reported enhanced traffic flow efficiency because of cooperation and exchange of information between vehicles (e.g. Monteil, Nantes, Billot, Sau, & El Faouzi, 2014;Wang, Daamen, Hoogendoorn, & van Arem, 2016b;Xie, Zhang, Gartner, & Arsava, 2016;Yang, Liu, Sun, & Li, 2013;Zhou, Qu, & Jin, 2016) but also between vehicles and infrastructure (e.g. variable speed limits, see Grumert, Ma, & Tapani, 2015;Wang, Daamen, Hoogendoorn, & van Arem, 2016a).…”

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

703

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

703

383

View full text Add to dashboard Cite

show abstract

“…Wu et al [6] developed a game theory-based description of drivers' interactions in U-turn scene, and the game model was imbedded into a cellular automaton model for identifying the effect of U-turn vehicle on traffic performance. In [7,8], the collaborative control models for ramp merging of freeway in CVIS environment are proposed. In [9], an adaptive traffic signal control method based on traffic flow conditions to reduce conflicts and delays at signal intersections is proposed.…”

Section: Introductionmentioning

confidence: 99%

Cooperative U-Turn Merging Behaviors and Their Impacts on Road Traffic in CVIS Environment

Sun

et al. 2020

Journal of Advanced Transportation

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U-turn behavior of vehicle is one of the main causes of urban traffic congestion and accidents. A collaborative U-turn merging control algorithm is studied with collision avoidance and delay minimization for vehicles under Cooperative Vehicle Infrastructure System (CVIS) environment. Two control strategies, zip merging and platoon merging control, are proposed. e applicability of these two strategies is compared from the perspective of efficiency and driving comfort. e cellular automaton simulation system composed of a two-way four-lane traffic flow with a U-turn facility in middle of road is established with cooperative control algorithm imbedded. e influence of cooperative U-turn merging behaviors on traffic performance is evaluated by analyzing the arrival rates of main lane and U-turn vehicles and their relationship between one another. e simulation results show that the arrival rate of vehicles on target lane has a great impact on traffic delay. e cooperative control can improve the traffic flow only in the condition that the arrival rate of vehicles on target lane is less than 0.7. It provides some practical references for transportation agencies to meet efficiency requirements of the U-turn section when they apply cooperative control strategy.

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“…Overtaking a slow front car using an opposite lane [11] imposes one or several time window (TW) constraints for speed planning in time domain at the conflict region with other road participants along the path. Merging from a freeway entrance ramp to a lane with an oncoming high-speed vehicle on expressway [12,13] does not only bring in a time window constraint but also boundary conditions such as a desired final speed and acceleration constraints to keep the pace with other traffic participants. These cases require that the car reaches a certain point on the path in the time window to avoid collision.…”

Section: Introductionmentioning

confidence: 99%

Toward a More Complete, Flexible, and Safer Speed Planning for Autonomous Driving via Convex Optimization

Zhang¹,

Chen²,

Waslander³

et al. 2018

Preprint

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In this paper, we present a complete, flexible and safe convex-optimization-based method to solve speed planning problems over a fixed path for autonomous driving in both static and dynamic environments. Our contributions are five fold. First, we summarize the most common constraints raised in various autonomous driving scenarios as the requirements for speed planner developments and metrics to measure the capacity of existing speed planners roughly for autonomous driving. Second, we introduce a more general, flexible and complete speed planning mathematical model including all the summarized constraints compared to the state-of-the-art speed planners, which addresses limitations of existing methods and is able to provide smooth, safety-guaranteed, dynamic-feasible, and time-efficient speed profiles. Third, we emphasize comfort while guaranteeing fundamental motion safety without sacrificing the mobility of cars by treating the comfort box constraint as a semi-hard constraint in optimization via slack variables and penalty functions, which distinguishes our method from existing ones. Fourth, we demonstrate that our problem preserves convexity with the added constraints, thus global optimality of solutions is guaranteed. Fifth, we showcase how our formulation can be used in various autonomous driving scenarios by providing several challenging case studies in both static and dynamic environments. A range of numerical experiments and challenging realistic speed planning case studies have depicted that the proposed method outperforms existing speed planners for autonomous driving in terms of constraint type covered, optimality, safety, mobility and flexibility.

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Collaborative merging strategy for freeway ramp operations in a connected and autonomous vehicles environment

Cited by 126 publications

References 23 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

Cooperative U-Turn Merging Behaviors and Their Impacts on Road Traffic in CVIS Environment

Toward a More Complete, Flexible, and Safer Speed Planning for Autonomous Driving via Convex Optimization

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