TY - JOUR
T1 - Controller Independent Software-in-the-Loop Approach to Evaluate Rule-Based Traffic Signal Retiming Strategy by Utilizing Floating Car Data
AU - Sharma, Salil
AU - Lussmann, Jonas
AU - So, Jaehyun
PY - 2018/1/1
Y1 - 2018/1/1
N2 - Floating car data present a cost-effective approach to observing the traffic state. This paper explores whether floating cars can substitute stationary detection devices (e.g., induction loops) for observers within traffic responsive control systems. A rule-based traffic control method at the local intersection level is proposed in this paper by utilizing the floating car data. The control method involves a three-fold approach: link-level speed forecasting, data-driven traffic flow estimation, and split optimization. To estimate traffic flow, a multivariable linear regression model is developed by utilizing forecasted link-level speed, signal control variables, and link length as predictors. The method is tested using a controller (hardware)-independent software-in-the-loop approach. Compared with the existing fixed-time control operating in Starnberg, Germany, the proposed method is able to improve the level of service of the signalized intersection when tested for different levels of market penetration of the floating cars. The findings underpin the use of floating car data in online traffic control applications; the benefits will increase with an increase in market penetration of floating cars. Overall, this paper presents a fully integrated technical system that is ready to be used in the field. The proposed system can be implemented at the tactical level of urban traffic-control hierarchy employed in Germany.
AB - Floating car data present a cost-effective approach to observing the traffic state. This paper explores whether floating cars can substitute stationary detection devices (e.g., induction loops) for observers within traffic responsive control systems. A rule-based traffic control method at the local intersection level is proposed in this paper by utilizing the floating car data. The control method involves a three-fold approach: link-level speed forecasting, data-driven traffic flow estimation, and split optimization. To estimate traffic flow, a multivariable linear regression model is developed by utilizing forecasted link-level speed, signal control variables, and link length as predictors. The method is tested using a controller (hardware)-independent software-in-the-loop approach. Compared with the existing fixed-time control operating in Starnberg, Germany, the proposed method is able to improve the level of service of the signalized intersection when tested for different levels of market penetration of the floating cars. The findings underpin the use of floating car data in online traffic control applications; the benefits will increase with an increase in market penetration of floating cars. Overall, this paper presents a fully integrated technical system that is ready to be used in the field. The proposed system can be implemented at the tactical level of urban traffic-control hierarchy employed in Germany.
KW - floating car data
KW - rule-based control.
KW - Signal re-timing
KW - software-in-the-loop simulation
KW - traffic flow estimation
KW - transport big data
KW - urban traffic control
UR - http://www.scopus.com/inward/record.url?scp=85056321731&partnerID=8YFLogxK
U2 - 10.1109/TITS.2018.2877585
DO - 10.1109/TITS.2018.2877585
M3 - Article
AN - SCOPUS:85056321731
SN - 1524-9050
VL - 20
SP - 3585
EP - 3594
JO - IEEE Transactions on Intelligent Transportation Systems
JF - IEEE Transactions on Intelligent Transportation Systems
IS - 9
ER -