A numerical model for impacts of left-turn non-motorized vehicles on through lane capacity metrics

Lieyun He; Xinming Lin; Qiang Liu; Jason X Tao

doi:10.5604/01.3001.0014.4199

Authors

Lieyun He Department of Transportation Management and Engineering, Zhejiang Police Collage Author https://orcid.org/0000-0002-8316-2333
Xinming Lin International School, Zhejiang Police Collage Author
Qiang Liu Big data-based Key Laboratory of the Ministry of Public Security, Zhejiang Police College Author
Jason X Tao Washington D.C. Department of Transportation Author https://orcid.org/0000-0002-8871-5144

DOI:

https://doi.org/10.5604/01.3001.0014.4199

Keywords:

traffic design, signalized intersectio, permissive phase, traffic lane capacity, regression analysi

Abstract

There is a conflict between through motor vehicles and the left-turn non-motorized vehicles, and the capacity of straight-line motor vehicles decreases. This study analyzes the impacts of left-turn non-motorized vehicles on the capacity of through motor vehicle lanes. A correction coefficient model for calculating the reduced capacity of through motor vehicle lanes has been developed based on analysis of the conflicting points at an intersection and the negative exponential function of traffic flow distribution. With consideration of intersection geometric design, channelization, and traffic characteristics, the cor-rection coefficient model was further enhanced by regression to capture the impacts of left-turn non-motorized vehicles from the same and the opposite directions. A simulation with VISSIM is used to validate the developed model. It shows that the calculated capacity from the correction coefficient model is close to the simulation results. The experiment indicates that the derived model is highly accurate in calculating the capacity of through motor vehicle lanes and has potential application for situations of mixed traffic in China. The study shows that the capacity of a through traffic lane at the permitted phase decreases with the increase of left-turning non-motorized vehicles, and the impact of left-turning non-motorized vehicles from the same direction is more significant. The results show that the traffic capacity of straight-line motor vehicle decreases with the increase of the left-turn non-motorized vehicles flow rate and the influence of the left-turn non-motor vehicle is more obvious. It is suggested that in practice, the correction coefficient of non-motor vehicle on the left turn should be 0.88, and the correction coefficient on the left turn should be 0.95, respectively. The study recommends coefficient values for both non-motorized vehicles from the same and opposite directions for use in real applications.

References

YANG, X., YANG, J., SHI, Y., 2012. Non-motorized Vehicle Left-turn Design at Signalized Intersections. Urban Transport of China, 10(04), 65-71+18.

SHI, Y., YANG, X., YANG, J., 2013. Comparative Research on Traffic Design Patterns of Urban Road Intersection. Traffic & Transportation, 01, 54-57.

YANG, X., ZHU, X., BAI, Y., 2018. Modeling the Impacts of Pedestrian and Non-mobile on the Left-turn Capacity of Signalized Intersections with Permitted Left-turn Phasing. China Transportation Review, 40(07), 53-58.

SUN, M., YANG, X., 2004. Research on the Theory of Traffic Design for Intersection of Mixed Traffic. Journal of Highway and Transportation Research and Development, 08, 82-86.

JAGANNATHAN,, R., BARED, J., 2005. Design and performance analysis of pedestrian crossing facilities for continuous flow intersections. Transportation Research Record, 1939, 133-144.

TANWANICHKUL, L., PITAKSRINGKARN, J., BOONCHAWEE, S., 2015. Determining the optimum distance of continuous flow intersection using traffic microsimulation. Journal of the Eastern Asia Society for Transportation Studies, 9, 1670-1683.

TARKO, A., AZAM, S., INEROWCIZ, M., 2010. Operational performance of alternative types of intersections a systematic comparison for Indiana conditions. Congress Proceedings, 32(31), 386-391.

ZHAO, J., XU, H., GAO, X., WANG, T., 2018. Optimization Design Method of Left-turn Bicycles Crossing for Continuous Flow Intersections. Journal of Transportation Systems Engineering and Information Technology, 18(06), 178-186.

ZHAO, H., HE, R., SU, J., 2018. Multi-objective optimization of traffic signal timing using non-dominated sorting artificial bee colony algorithm for unsaturated intersections. Archives of Transport, 46(2), 85–96.

CHEN, X. SHAO, C. YAO, Z., 2008. A Study on successive crossings of left-turn bicycles at typical signalized intersections. China Civil Engineering Journal, 07, 76-81.

TRB, 2000. TRANSPORTATION RE-SEARCH BOARD., 2000. Highway Capacity Manual, Special Report 209. Washington D C: National Research Council.

ZHANG, S., REN, G., YANG R., 2013. Simulation Model of Speed -Density Characteristics for Mixed Bicycle Flow-Comparison between Cellular Automata Model and Gas Dynamics Model. Physica A, 392 (10), 5110-5118.

GB, 2011. GB 50647-2011 Code for planning of intersections on urban roads., 2011. Beijing. China Planning Press.

ZHANG, S., HE, K., 2014. Expansion Effect of Left Turning Mixed Bicycle Flow and Vehicle-Bicycle Conflict at Intersections. Journal of Ningbo University of Technology, 26(02), 7-11.

XU, L.,WU, C., YANG, Z., 2001. The Methods of Computing the Capacity of Signalized Intersection. Journal of Traffic and Transportation Engineering, 01, 82-85.

YUAN, J., YUAN, Z., 2006. Comparison Analysis of Calculation Methods for Traffic Capacity at Signal Junction. Technology of Highway and Transport, 05, 123-128+132.

WOJTAL, R. M., RILETT, L. R., 2017. Development of a statistically-based methodology for analyzing automatic safety treatments at isolated high-speed signalized intersections. Archives of Transport, 44(4), 75-88.

ZHU, X. GUO, J. HUANG, W. YU, F. PARK, B., 2018. Real-time Short-term Forecasting Method of Remaining Parking Space in Urban Parking Guidance Systems. Promet Traffic & Transportation, 30(2), 173-185.