The Effects of the "White Phase" on Intersection Performance with Mixed-Autonomy Traffic Stream

被引:0
作者
Niroumand, Ramin [1 ]
Tajalli, Mehrdad [1 ]
Hajibabai, Leila [2 ]
Hajbabaie, Ali [1 ]
机构
[1] North Carolina State Univ, Dept Civil Construct & Environm Engn, Raleigh, NC 27695 USA
[2] North Carolina State Univ, Dept Ind & Syst Engn, Raleigh, NC 27695 USA
来源
2020 IEEE 23RD INTERNATIONAL CONFERENCE ON INTELLIGENT TRANSPORTATION SYSTEMS (ITSC) | 2020年
关键词
Connected automated vehicles; White phase; Mixed-autonomy traffic; Self-driving vehicles; OPTIMIZATION; VEHICLES;
D O I
暂无
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
This study investigates the effects of the "white phase" on the performance of isolated signalized intersections. During the white phase, connected automated vehicles (CAV) control traffic flow through an intersection, and connected human-driven vehicles (CHV) follow their front vehicle (either CAV or CHV). Traffic controller ensures collision-free movement of vehicles through the intersection by determining 1) the sequence and duration of phases (green and white) and 2) trajectory of CAVs during white phases. White phases can be assigned to conflicting movements simultaneously. We have formulated this problem as a mixed-integer non-linear program (MINLP) and solved it using a receding horizon algorithm. Two demand patterns with five different CAV market penetration rates are used to evaluate the effects of the white phase on mobility and safety in an isolated intersection. Each case study is tested with three different control scenarios: 1) No-white-phase, 2) white-phase-only, and 3) optimal-white-phase activation (combination of white, green, and red phases). The results indicate that the white phase yields significant improvement in intersection performance while maintaining the same safety level.
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页数:6
相关论文
共 43 条
[1]  
[Anonymous], 2010, DELAYED RESPONSE POL
[2]   Predictive Cruise Control: Utilizing Upcoming Traffic Signal Information for Improving Fuel Economy and Reducing Trip Time [J].
Asadi, Behrang ;
Vahidi, Ardalan .
IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY, 2011, 19 (03) :707-714
[3]  
Askari A, 2016, ARXIV161108973
[4]   Distributed coordinated signal timing optimization in connected transportation networks [J].
Bin Al Islam, S. M. A. ;
Hajbabaie, Ali .
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES, 2017, 80 :272-285
[5]   Toward a new professionalism in Saudi Arabia: could council for exceptional children standards be a catalyst for change in special education? [J].
Binammar, Sara .
INTERNATIONAL JOURNAL OF LEADERSHIP IN EDUCATION, 2020, 23 (06) :655-670
[6]  
Dresner K., 2004, AUT AG MULT SYST INT, V2, P530
[7]   A multiagent approach to autonomous intersection management [J].
Dresner, Kurt ;
Stone, Peter .
JOURNAL OF ARTIFICIAL INTELLIGENCE RESEARCH, 2008, 31 :591-656
[8]   Spatiotemporal intersection control in a connected and automated vehicle environment [J].
Feng, Yiheng ;
Yu, Chunhui ;
Liu, Henry X. .
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES, 2018, 89 :364-383
[9]   Surrogate safety measures from traffic simulation models [J].
Gettman, D ;
Head, L .
STATISTICAL METHODS AND MODELING AND SAFETY DATA, ANALYSIS, AND EVALUATION: SAFETY AND HUMAN PERFORMANCE, 2003, (1840) :104-115
[10]   Urban traffic signal control with connected and automated vehicles: A survey [J].
Guo, Qiangqiang ;
Li, Li ;
Ban, Xuegang .
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES, 2019, 101 :313-334