published journal article
working paper
Ownership and management for urban mass transit organizations have taken many forms over the years, with publicly-owned and managed systems now dominant. In recent years, however, strong economic and political forces have increased pressures for privatizing urban mass transit services. This review analyzes twenty studies from three countries on the relationship between organizational form and transit performance. It concludes that previous research has not made a persuasive case for the whole-scale privatization of either ownership or management of urban mass transit organization.
published journal article
published journal article
published journal article
Recent research has demonstrated and established the viability of applying path-based algorithms to the traffic equilibrium problem in reasonably large networks. Much of the attention has been focused on two particular algorithms: the disaggregate simplicial decomposition (DSD) algorithm and the gradient projection (GP) algorithm. The purpose of this paper is to evaluate the performance of these two path-based algorithms using networks of realistic size. Sensitivity analysis is performed on randomly generated networks to examine the performance of the algorithms with respect to network sizes, congestion levels, number of origin-destination (OD) pairs, and accuracy levels. In order to be empirically convincing, a realistic large-scale network, known as the ADVANCE network, is also used to show that path-based algorithms are a viable alternative in practice. (C) 2002 IMACS. Published by Elsevier Science B.V. All rights reserved.
published journal article
This work assesses the feasibility of Solid Oxide Fuel Cell-Gas Turbine (SOFC-GT) hybrid power systems for use as the prime mover in freight locomotives. The available space in a diesel engine-powered locomotive is compared to that required for an SOFC-GT system, inclusive of fuel processing systems necessary for the SOFC-GT. The SOFC-GT space requirement is found to be similar to current diesel engines, without consideration of the electrical balance of plant. Preliminary design of the system layout within the locomotive is carried out for illustration. Recent advances in SOFC technology and implications of future improvements are discussed as well. A previously-developed FORTRAN model of an SOFC-GT system is then augmented to simulate the kinematics and power notching of a train and its locomotives. The operation of the SOFC-GT-powered train is investigated along a representative route in Southern California, with simulations presented for diesel reformate as well as natural gas reformate and hydrogen as fuels. Operational parameters and difficulties are explored as are comparisons of expected system performance to modern diesel engines. It is found that even in the diesel case, the SOFC-GT system provides significant savings in fuel and CO2 emissions, making it an attractive option for the rail industry. (C) 2012 Elsevier B.V. All rights reserved.
conference paper
A new facility location model and a solution algorithm are proposed that feature 1) itinerary-interception instead of flow-interception; 2) stochastic demand as dynamic service requests; and 3) queueing delay. These features are essential to analyze battery-powered electric shared-ride taxis operating in a connected, centralized dispatch manner. The model and solution method are based on a bi-level, simulation-optimization framework that combines an upper level multiple-server allocation model with queueing delay and a lower level dispatch simulation based on earlier work by Jung and Jayakrishnan. The solution algorithm is tested on a fleet of 600 shared-taxis in Seoul, Korea, spanning 603 km2, a budget of 100 charging stations, and up to 22 candidate charging locations, against a benchmark â??naïveâ?? genetic algorithm that does not consider cyclic interactions between the taxi charging demand and the charger allocations with queue delay. Results show not only that the proposed model is capable of locating charging stations with stochastic dynamic itinerary-interception and queue delay, but that the bi-level solution method improves upon the benchmark algorithm in terms of realized queue delay, total time of operation of taxi service, and service request rejections. Furthermore, the authors show how much additional benefit in level of service is possible in the upper-bound scenario when the number of charging stations is unbounded.
published journal article
Phd Dissertation
This assignment problem is investigated in several steps. First, a myopic deterministic version is studied in which travel time, service time and the demands are fixed. A new non-decreasing partitioning scheme to deal with time window constraints for this problem is developed. A feasible option for solving the dynamic assignment problem is to repeatedly apply this deterministic algorithm in a dynamic setting in a rolling horizon framework whenever new information is available. The deterministic algorithm provides a basis for further consideration of stochastic factors including queuing times, handling times and travel times under traffic congestion. Several stochastic models are proposed and discussed. The discussion indicates that direct adoption of stochastic models aimed at other problems involves great difficulty because of the complex nature of this problem. Therefore, approximation models are preferable. Further, by incorporating additional requirements of trailer repositioning, a more general problem of multi-layered resource allocation is defined. Multi resource allocation problems have wide practical implications in air, rail and maritime carrier fleet operations. The discussion of these models highlights a promising opportunity for future research. All the methods and ideas motivated by this specific assignment problem can be easily extended to other routing and scheduling problems. As part of this research, we further investigated some NP-hard problems that generally underlie such applications. A special case of TSP problem, titled “the TSP with separation requirement”, is examined and a new formulation is presented. The formulation takes the TSP with precedence constraints and the time dependent TSP as special cases. Additionally, a new general cutting plane method is proposed. It applies, but is not limited to, integer programming problem with binary variables. We believe that this method has some advantages over its counterpart, Gomory’s method. However, further effort is needed to test its performance.
conference paper
In Autonomous Vehicles (AVs), one fundamental pillar is perception, which leverages sensors like cameras and LiDARs (Light Detection and Ranging) to understand the driving environment. Due to its direct impact on road safety, multiple prior efforts have been made to study its the security of perception systems. In contrast to prior work that concentrates on camera-based perception, in this work we perform the first security study of LiDAR-based perception in AV settings, which is highly important but unexplored. We consider LiDAR spoofing attacks as the threat model and set the attack goal as spoofing obstacles close to the front of a victim AV. We find that blindly applying LiDAR spoofing is insufficient to achieve this goal due to the machine learning-based object detection process. Thus, we then explore the possibility of strategically controlling the spoofed attack to fool the machine learning model. We formulate this task as an optimization problem and design modeling methods for the input perturbation function and the objective function. We also identify the inherent limitations of directly solving the problem using optimization and design an algorithm that combines optimization and global sampling, which improves the attack success rates to around 75%. As a case study to understand the attack impact at the AV driving decision level, we construct and evaluate two attack scenarios that may damage road safety and mobility. We also discuss defense directions at the AV system, sensor, and machine learning model levels.