Enhancing traffic efficiency and alleviating(even circumventing) traffic congestion with advanced traffic signal control(TSC) strategies are always the main issues to be addressed in urban transportation systems. Sinc...Enhancing traffic efficiency and alleviating(even circumventing) traffic congestion with advanced traffic signal control(TSC) strategies are always the main issues to be addressed in urban transportation systems. Since model predictive control(MPC) has a lot of advantages in modeling complex dynamic systems, it has been widely studied in traffic signal control over the past 20 years. There is a need for an in-depth understanding of MPC-based TSC methods for traffic networks. Therefore, this paper presents the motivation of using MPC for TSC and how MPC-based TSC approaches are implemented to manage and control the dynamics of traffic flows both in urban road networks and freeway networks. Meanwhile, typical performance evaluation metrics, solution methods, examples of simulations,and applications related to MPC-based TSC approaches are reported. More importantly, this paper summarizes the recent developments and the research trends in coordination and control of traffic networks with MPC-based TSC approaches. Remaining challenges and open issues are discussed towards the end of this paper to discover potential future research directions.展开更多
I.I NTRODUCTION W ITH the advent of low-carbon economy,there has been a growing interest in harnessing renewable energy resources particularly for electricity generation.Renewable energy resources are advocated for th...I.I NTRODUCTION W ITH the advent of low-carbon economy,there has been a growing interest in harnessing renewable energy resources particularly for electricity generation.Renewable energy resources are advocated for the economic and environ-展开更多
Letα(F_(q)^(d),p)denote the maximum size of a general position set in a p-random subset of F_(q)^(d).We determine the order of magnitude ofα(F_(q)^(2),p)up to polylogarithmic factors for all possible values of p,imp...Letα(F_(q)^(d),p)denote the maximum size of a general position set in a p-random subset of F_(q)^(d).We determine the order of magnitude ofα(F_(q)^(2),p)up to polylogarithmic factors for all possible values of p,improving the previous results obtained by Roche-Newton and Warren(2022)and Bhowmick and Roche-Newton(2024).For d≥3,we prove upper bounds forα(F_(q)^(d),p)that are essentially tight within certain ranges for p.We establish the upper bound 2^((1+o(1))q) for the number of general position sets in F_(q)^(d),which matches the trivial lower bound 2q asymptotically in the exponent.We also refine this counting result by proving an asymptotically tight(in the exponent)upper bound for the number of general position sets with a fixed size.The latter result for d=2 improves the result of Roche-Newton and Warren(2022).Our proofs are grounded in the hypergraph container method.In addition,for d=2,we also leverage the pseudorandomness of the point-line incidence graph of F_(q)^(2).展开更多
Purpose–To support the standardized evaluation of bicyclist automatic emergency braking(AEB)systems,test scenarios,test procedures and test system hardware and software tools have been investigated and developed by t...Purpose–To support the standardized evaluation of bicyclist automatic emergency braking(AEB)systems,test scenarios,test procedures and test system hardware and software tools have been investigated and developed by the Transportation Active Safety Institute(TASI)at Indiana University-Purdue University Indianapolis.This paper aims to focus on the development of test scenarios and bicyclist surrogate for evaluating vehicle–bicyclist AEB systems.Design/methodology/approach–The harmonized general estimates system(GES)/FARS 2010-2011 crash data and TASI 110-car naturalistic driving data(NDD)are used to determine the crash geometries and environmental factors of crash scenarios including lighting conditions,vehicle speeds,bicyclist speeds,etc.A surrogate bicyclist including a bicycle rider and a bicycle surrogate is designed to match the visual and radar characteristics of bicyclists in the USA.A bicycle target is designed with both leg pedaling and wheel rotation to produce proper micro-Doppler features and generate realistic motion for camera-based AEB systems.Findings–Based on the analysis of the harmonized GES/FARS crash data,five crash scenarios are recommended for performance testing of bicyclist AEB systems.Combined with TASI 110-car naturalistic driving data,the crash environmental factors including lighting conditions,obscuring objects,vehicle speed and bicyclist speed are determined.The surrogate bicyclist was designed to represent the visual and radar characteristics of the real bicyclists in the USA.The height of the bicycle rider mannequin is 173 cm,representing the weighted height of 50th percentile US male and female adults.The size and shape of the surrogate bicycle were determined as 26-inch wheel and mountain/road bicycle frame,respectively.Both leg pedaling motion and wheel rotation are suggested to produce proper micro-Doppler features and support the camera-based AEB systems.Originality/value–The results have demonstrated that the developed scenarios,test procedures and bicyclist surrogate will provide effective objective methods and necessary hardware and software tools for the evaluation and validation of bicyclist AEB systems.This is crucial for the development of advanced driver assistance systems.展开更多
基金supported in part by the National Natural Science Foundation of China(61603154,61773343,61621002,61703217)the Natural Science Foundation of Zhejiang Province(LY15F030021,LY19F030014)Open Research Project of the State Key Laboratory of Industrial Control Technology,Zhejiang University,China(ICT1800407)
文摘Enhancing traffic efficiency and alleviating(even circumventing) traffic congestion with advanced traffic signal control(TSC) strategies are always the main issues to be addressed in urban transportation systems. Since model predictive control(MPC) has a lot of advantages in modeling complex dynamic systems, it has been widely studied in traffic signal control over the past 20 years. There is a need for an in-depth understanding of MPC-based TSC methods for traffic networks. Therefore, this paper presents the motivation of using MPC for TSC and how MPC-based TSC approaches are implemented to manage and control the dynamics of traffic flows both in urban road networks and freeway networks. Meanwhile, typical performance evaluation metrics, solution methods, examples of simulations,and applications related to MPC-based TSC approaches are reported. More importantly, this paper summarizes the recent developments and the research trends in coordination and control of traffic networks with MPC-based TSC approaches. Remaining challenges and open issues are discussed towards the end of this paper to discover potential future research directions.
文摘I.I NTRODUCTION W ITH the advent of low-carbon economy,there has been a growing interest in harnessing renewable energy resources particularly for electricity generation.Renewable energy resources are advocated for the economic and environ-
基金supported by European Research Council Advanced Grant(Grant No.101020255)Leverhulme Research Project Grant(Grant No.RPG-2018-424)+3 种基金supported by National Natural Science Foundation of China(Grant No.123B2012)supported by European Research Council Advanced Grants“GeoScape”(Grant No.882971)and“ERMiD”(Grant No.101054936)Jonathan Tidor for stimulating discussions at 2023 University of California San Diego Workshop on Ramsey Theoryinitiated while Ji Zeng was visiting Shanghai Center for Mathematical Sciences at the kind invitation of Hehui Wu.
文摘Letα(F_(q)^(d),p)denote the maximum size of a general position set in a p-random subset of F_(q)^(d).We determine the order of magnitude ofα(F_(q)^(2),p)up to polylogarithmic factors for all possible values of p,improving the previous results obtained by Roche-Newton and Warren(2022)and Bhowmick and Roche-Newton(2024).For d≥3,we prove upper bounds forα(F_(q)^(d),p)that are essentially tight within certain ranges for p.We establish the upper bound 2^((1+o(1))q) for the number of general position sets in F_(q)^(d),which matches the trivial lower bound 2q asymptotically in the exponent.We also refine this counting result by proving an asymptotically tight(in the exponent)upper bound for the number of general position sets with a fixed size.The latter result for d=2 improves the result of Roche-Newton and Warren(2022).Our proofs are grounded in the hypergraph container method.In addition,for d=2,we also leverage the pseudorandomness of the point-line incidence graph of F_(q)^(2).
文摘Purpose–To support the standardized evaluation of bicyclist automatic emergency braking(AEB)systems,test scenarios,test procedures and test system hardware and software tools have been investigated and developed by the Transportation Active Safety Institute(TASI)at Indiana University-Purdue University Indianapolis.This paper aims to focus on the development of test scenarios and bicyclist surrogate for evaluating vehicle–bicyclist AEB systems.Design/methodology/approach–The harmonized general estimates system(GES)/FARS 2010-2011 crash data and TASI 110-car naturalistic driving data(NDD)are used to determine the crash geometries and environmental factors of crash scenarios including lighting conditions,vehicle speeds,bicyclist speeds,etc.A surrogate bicyclist including a bicycle rider and a bicycle surrogate is designed to match the visual and radar characteristics of bicyclists in the USA.A bicycle target is designed with both leg pedaling and wheel rotation to produce proper micro-Doppler features and generate realistic motion for camera-based AEB systems.Findings–Based on the analysis of the harmonized GES/FARS crash data,five crash scenarios are recommended for performance testing of bicyclist AEB systems.Combined with TASI 110-car naturalistic driving data,the crash environmental factors including lighting conditions,obscuring objects,vehicle speed and bicyclist speed are determined.The surrogate bicyclist was designed to represent the visual and radar characteristics of the real bicyclists in the USA.The height of the bicycle rider mannequin is 173 cm,representing the weighted height of 50th percentile US male and female adults.The size and shape of the surrogate bicycle were determined as 26-inch wheel and mountain/road bicycle frame,respectively.Both leg pedaling motion and wheel rotation are suggested to produce proper micro-Doppler features and support the camera-based AEB systems.Originality/value–The results have demonstrated that the developed scenarios,test procedures and bicyclist surrogate will provide effective objective methods and necessary hardware and software tools for the evaluation and validation of bicyclist AEB systems.This is crucial for the development of advanced driver assistance systems.
