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http://dx.doi.org/10.7470/jkst.2018.36.2.098

Methodology for Determining Promising Freeway Segments for Truck Platooning  

JO, Young (Transportation and Logistics Engineering, Hanyang University)
KWON, Kyeongjoo (Transportation and Logistics Engineering, Hanyang University)
OH, Cheol (Transportation and Logistics Engineering, Hanyang University)
Publication Information
Journal of Korean Society of Transportation / v.36, no.2, 2018 , pp. 98-111 More about this Journal
Abstract
Truck platooning, which is a cluster of trucks in support of vehicle-to-vehicle communication and automated longitudinal vehicle control, is a promising method to both operational efficiency and prevent traffic crashes. Although a variety of studies have been conducted to identify the effects of vehicle platooning on traffic stream, we are not aware of any study attempting to identify promising road segments for vehicle platooning. This study aims to develop a methodology for determining the priority of freeway segments that would potentially lead to maximize the effectiveness of truck platooning. Evaluation measures derived in this study includes truck crash rates, the percentage of truck traffic, segment length, and the number of entry and exit points. Weighting values obtained from an analytical hierarchical process (AHP) method were applied to compute the proposed priority score to determine better freeway segment for truck platooning. Results suggested that a 46.9km freeway segment, from Sacheon IC to Sanin JC, was the most promising segment for maximizing the effectiveness of truck platooning. It is expected that the outcome of this study would be effectively used as a fundamental to establish operational strategies for truck platooning.
Keywords
AHP; freeway; priority; promising segment; truck platooning;
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Times Cited By KSCI : 3  (Citation Analysis)
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1 Amoozadeh M., Deng H., Chuah C. N., Zhang H. M., Ghosal D. (2015), Platoon Management With Cooperative Adaptive Cruise Control Enabled by VANET, Vehicular Communications, 2(2), 110-123.   DOI
2 Bin M. Y., Kim Y. D. (2017), Prospect of Autonomous Vehicle Introduction and Change of Environment for Traffic Use, Issue&Analysis, 300, 1-25.
3 Choi K. C., Shim S. W., Lee E. E., Kim I. S. (2009), Seclection of Expressway Ramp Metering Sites and Priority Making, Journal of The Korean Society of Civil Engineers D, 29(5D), 579-585.
4 Connecting Eroup Facility, http://inea.ec.europa.eu/en/cef/, 2018.01.15.
5 Jain Y. K., Bhandare S. K. (2011), Min Max Normalization Based Data Perturbation Method for Privacy Protection, International Journal of Computer & Communication Technology, 2(8), 45-50.
6 Lee S. Y., Oh C. (2017), Lane Change Behavior of Manual Vehicles in Automated Vehicle Platooning Environments, J. Korean Soc. Transp., 35(4), Korean Society of Transportation, 332-347.   DOI
7 Park J. Y., Oh C., Chang M. S. (2013), A Study on Variable Speed Limit Strategies in Freeway Work Zone Using Multi-criteria Decision Making Process, J. Korean Soc. Transp., 31(5), Korean Society of Transportation, 3-15.   DOI
8 Saaty T. L., Erdener E. R. E. N. (1979), A New Approach to Performance Measurement the Analytic Hierarchy Process, Design Methods and Theories, 13(2), 62-68.
9 SAE (2014), Automated Driving-What Comes First: Cars or Standards.
10 Tsugawa S., Kato S., Aoki K. (2011), An Automated Truck Platoon for Energy Saving, In Intelligent Robots and Systems (IROS), IEEE, 4109-4114.
11 Youn S. M., Oh C., Joo S. H., Jung E. B. (2016), Effectiveness Evaluation of Core Technologies for Automated Vehicle-highway Systems Based on a Meta-analysis, Transportation Technology and Policy, 13(4), Korean Society of Transportation, 30-41.
12 Yun I. S., Han E., Lee C. K., Rho J. H., Lee S. J., Kim S. B. (2013), Mobility and Safety Evaluation Methodology for the Locations of Hi-PASS Lanes Using a Microscopic Traffic Simulation Tool, The Journal of The Korea Institute of Intelligent Transport Systems, 12(1), 98-108.   DOI
13 U.S. Departmet of Transportation (2013), Transportation for a New Generation, 7-9.