2015 Informs Annual Meeting

TD69

INFORMS Philadelphia – 2015

TD70 70-Room 202A, CC Tutorial: Railroad Predictive Analytics Sponsor: Railway Applications Sponsored Session Chair: Aihong Wen, CSX, 500 Water St, Jacksonville, FL, 32202, United States of America, aihong_wen@csx.com 1 - Railroad Data Mining Tutorial Aihong Wen, CSX, 500 Water St, Jacksonville, FL, 32202, United States of America, aihong_wen@csx.com, Jerry Kam We will share the business use cases and modeling experiences in applying data mining and big data techniques to railroad.

3 - A Decentralized Decision Making System to Enable Resilient Microgrid Clusters Yong Fu, Associate Professor, Mississippi State University, Starkville, MS, United States of America, fu@ece.msstate.edu Microgrid has been proposed to ensure resilience in power systems. The microgrid can treat connected neighboring microgrids as local energy buffers thus freely forming a cluster to share, exchange, and aggregate site-generated energy. This research proposes a decentralized decision making system to improve the microgrid clusters’ resilience capability to power disturbances and extreme events, consequently minimizing down-time for both consumers and the grid.

TD69 69-Room 201C, CC

Connected and Autonomous Vehicles I Sponsor: TSL/Intelligent Transportation Systems (ITS) Sponsored Session Chair: Yong Hoon Kim, Purdue University, United States of America, kim523@purdue.edu 1 - Multi-agent Based Formation Control of Connected Autonomous Vehicles Yongfu Li, Chongqing University of Posts and Telecommunications, Chongqing, China, laf1212@163.com, Kezhi Li, Li Zhang, Srinivas Peeta, Xiaozheng He, Hong Zheng, Taixiong Zheng This study seeks to improve network throughput and reduce energy consumption under V2V communications environment through formation control. A multi- agent systems based formation control is proposed using consensus theory. We analyze the formation of autonomous vehicles in longitudinal and lateral gaps simultaneously. Numerical experiments illustrate the effectiveness of the proposed method in terms of position and velocity consensus. 2 - Macroscopic Modeling of the Spatial-temporal Information Flow Propagation Waves under Vehicle-to-Vehicle Communications Yong Hoon Kim, Purdue University, West Lafayette, IN, United States of America, kim523@purdue.edu, Srinivas Peeta, Xiaozheng He This study proposes an integrated model consisting of integro-differential equations to describe the information flow propagation process and a partial differential equation to describe the traffic flow dynamics. It incorporates the success rate of communication with distance and interference as a probability density function, and provide a closed-form solution for the speed of the information propagation wave. Numerical experiments are conducted to analyze the performance of the proposed model. 3 - Vehicle Trajectory Reconstruction under the Mixed Connected Vehicle Environment This paper sets out to reconstruct the trajectory of non-connected vehicles based on the trajectory of connected vehicles only. The trajectory reconstruction problem is formulated in the linear state-space modeling (SSM) framework, where the state dynamics is captured by the simplified car following model. Next a modified EM (Expectation-Maximization) algorithm is developed to obtain the optimal estimation of the unknown trajectory and model parameters simultaneously. The performance of the EM algorithm is tested and validated through the simulation data. 4 - A Mathematical Model to Locate Optimal Lane Changing Zone at a Highway Off-ramp Feng Zhu, Purdue University, WEst Lafayette, IN, United States of America, zhu214@purdue.edu, Satish V. Ukkusuri

TD71 71-Room 202B, CC Transportation Planning II Contributed Session

Chair: Hadi Farhangi, Research Assistant, Missouri University of Science and Technology, 1870 Miner Cir, Rolla, MO, 65401, United States of America, hfrhc@mst.edu 1 - NHTSA Cafe Compliance Cost Optimization Yohan Shim, Sr. Analyst, AVL Scenaria Inc, 47603 Halyard Drive, Plymouth, MI, 48170, United States of America, yohan.shim@scenaria.com, Travis Tamez, Christopher Mollo, Frederic Jacquelin The United States National Highway Traffic Safety Administration (NHTSA) has issued in August 2012 final rules and regulations for Corporate Average Fuel Economy (CAFE) for model years 2017 and beyond. NHTSA sets national CAFE standards under the Energy Policy and Conservation Act to improve fuel economy for passenger cars and light trucks. We present a mathematical program model and efficient heuristics to support vehicle manufacturer’s long-term strategic decisions on CAFE credit utilization. 2 - Highway Cost Allocation for Vehicle Classes with Variable Traffic Capacity Requirements Saurav Kumar Dubey, PhD Student, Department Of Industrial And Systems Engineering, University of Tennessee at Knoxville, 1615 Laurel Avenue, Knoxville, TN, 37916, United States of America, skumardu@vols.utk.edu, Alberto Garcia-Diaz A Highway Cost Allocation model with variable traffic capacity levels is developed to distribute costs among vehicle classes. The discrete Aumann-Shapley value is used to generate costs for all coalitions in the least core model. Rules for tie breaking to get a unique allocation known as the nucleolus are discussed. 3 - Competition and Regulation of the Taxi Market with Ride-sourcing Platforms Liteng Zha, University of Florida, 365 Weil Hall, Gainesville, FL, 32611, United States of America, seuzha@gmail.com, Yafeng Yin Ride-sourcing platforms such as Uber and Lyft are eroding the traditional taxi market. Despite of their attractiveness, controversies arise over the legality and reliability of their services as well as the fairness of the competition to regular taxis. This study offers a quantitative investigation of the taxi market with ride- sourcing platforms and investigates its regulation strategies. 4 - Biobjective Efficient Driving of Electric Vehicles on an Edge of a Network Hadi Farhangi, Research Assistant, Missouri University of Science and Technology, 1870 Miner Cir, Rolla, MO, 65401, United States of America, hfrhc@mst.edu, Dincer Konur, Warren Vaz, Umit Koylu This study analyzes driving profile for an electric vehicle between two nodes, i.e., on an edge of a network. We consider acceleration, maximum speed, and deceleration as decision variables. The energy consumed and the travel time required are functions of these variables as well as the load carried and the distance traveled. We investigate the energy and time minimizing driving profiles through a bi-objective optimization approach.

Siyuan Gong, Illinois Institute of Technology, Chicago, IL, United States of America, sgong1@hawk.iit.edu, Lili Du

This research seeks to locate an optimal temporal-spatial lane change zone around a highway off-ramp. This zone will grant enough opportunities for vehicles to proposed and validated by simulation experiments.so that the resulted time delay can be minimized. A mathematical model combining traffic flow analysis is conduct smooth lane change maneuvers before an off ramp

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