Informs 2015

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INFORMS Philadelphia – 2015
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3 - A Decentralized Decision Making System to Enable Resilient
Microgrid Clusters
Yong Fu, Associate Professor, Mississippi State University,
Starkville, MS, United States of America,
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,
1 - Multi-agent Based Formation Control of Connected
Autonomous Vehicles
Yongfu Li, Chongqing University of Posts and
Telecommunications, Chongqing, China, ,
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, 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
Feng Zhu, Purdue University, WEst Lafayette, IN,
United States of America,
Satish V. Ukkusuri
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
Siyuan Gong, Illinois Institute of Technology, Chicago, IL,
United States of America, , 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 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
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,
1 - Railroad Data Mining Tutorial
Aihong Wen, CSX, 500 Water St, Jacksonville, FL, 32202,
United States of America, , Jerry Kam
We will share the business use cases and modeling experiences in applying data
mining and big data techniques to railroad.
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,
1 - NHTSA Cafe Compliance Cost Optimization
Yohan Shim, Sr. Analyst, AVL Scenaria Inc, 47603 Halyard Drive,
Plymouth, MI, 48170, United States of America,
, 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, 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, , 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, , 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.
TD69