published journal article
working paper
Growing concerns about traffic congestion and rapid suburban expansion (also known as sprawl) have reignited interest in the ways in which highway spending affects metropolitan growth patterns. This discussion paper extracts the best evidence to date on how highway investments distribute growth and economic activity across metropolitan areas. The paper also offers ideas on how transportation financing and policies can better respond to the various costs and benefits of highway projects in a region.
conference paper
To enable high-level driving automation [1], the Autonomous Driving (AD) system in an Autonomous Vehicle (AV) needs to perform centimeter-level localization of its own global positions on the map [2]. Such localization function is highly security and safety critical in the AV context, since positioning errors can directly cause an AV to drive off road or onto a wrong way. For outdoor localization, GPS is the de facto location source, and thus a direct threat is GPS spoofing, a long-existing but still unsolved security problem with practicality proven on many end systems. Fortunately, AV systems today predominantly use Multi-Sensor Fusion (MSF) algorithms [3] that are generally believed to have potential to practically defeat GPS spoofing [4]. However, no prior work has studied whether today’s MSF algorithms are indeed sufficiently secure under GPS spoofing, especially in AV settings. In this work, we perform the first study to fill this critical gap. We consider the attack goal as using GPS spoofing to cause large lateral deviations in the MSF output, i.e., deviating to left or right. This can cause the AV to drive off road or onto a wrong way.
Phd Dissertation
This dissertation proposes a set of coherent cognition-based paradigms to allow greater sensitivity and adaptability to the emerging technologies and behavioral policies. These paradigms are derived from a cognition-based framework that explicates information source, medium, sensation, perception, and learning. The feasibility of the framework is demonstrated through an analytical example of multi-stakeholder decision processes and human-machine systems where the two types of entities can be incorporated into the same modeling scheme. Using the framework as guidance also reduces the challenges from information intractability and data redundancy of agent-based modeling practice.The first paradigm follows the strict definition of information in Information Theory and models it as the change of uncertainty, which is applied in quantifying traveler information for the evaluation of dynamic message boards that present various contents at candidate locations in Los Angeles traffic networks.The second paradigm is developed for a utility-based decision model under risk around the proposed concept, Elastic Surprise. This concept makes feasible the differentiation between probability misperception and perceived uncertainty. It is shown that conventional methods of decisions under risk such as Expected Utility Theory and Cumulative Prospect Theory are special cases. In addition, a specific form of Elastic Surprise under particular assumption on human’s cognition leads to Shannon’s information entropy and, hence, connects with the first Paradigm. The method is tested in conjunction with the Cumulative Prospect Theory on travel time equivalency under risk in a survey study. The results show improvement in data fitting and output interpretability.Finally, guided by the framework, the paradigms are tested on a case study of multi-class multi-criteria dynamic traffic assignment where heterogeneous travelers’ risk preference on travel time is explicitly modeled. The algorithm approaches the user equilibrium through a stochastic quasi-gradient projection-based algorithm that shows the improvement in computational efficiency and cognitive implication of the agents’ decision rules. I also discuss the potential strategies and policies implication for system improvement.
conference paper
This paper investigates the effect of airline emissions charges on airline service quality, airfares, aircraft design features, and network structure, using a realistic and detailed theoretical model of competing duopoly airlines. These impacts are derived by analyzing the effects of an increase in the effective price of fuel, which is the path by which emissions charges will alter airline choices. The results show that emission charges will raise fares, reduce flight frequency, increase load factors, and raise aircraft fuel efficiency, while having no effect on aircraft size. Given that these adjustments occur in response to the treatment of an emissions externality that is currently unaddressed, they represent efficient changes that move society closer to a social optimum.
conference paper
published journal article
working paper
Changing economic conditions facing American transit since World War II are reviewed and strategies for coping with current problems are analysed. The most critical issues are financial. The cost of producing transit has been rising at about twice the rate of inflation, while local, state and federal assistance has begun to taper off after a dramatic increase in the early 1970s. Management’s response to hard times is analysed: transit performance is being monitored more critically; peak‐period alternatives to regular transit are being implemented and new fare structures which are more effective and equitable are being introduced. Strategies are integrated into a budget‐based, financial planning cycle in which capital acquisitions and service deployment are related to anticipated revenues. Part 1 reviews the changing objectives between 1950 and 1980. Part 2, which will appear in the next issue, outlines management’s response to the need for improved efficiency.
research report
LiDAR is an emerging technology that can provide detailed point-cloud measurements of objects. The purpose of this study is to investigate the use of LiDAR technology for accurate classification of trucks according to the established FHWA scheme along rural highway corridors as an alternative to in-pavement detector infrastructure – such as inductive loop sensors and piezo-based automatic vehicle classifiers which is not widely deployed along many rural highway corridors – and temporary sensors such as pneumatic road tubes, which expose workers to live traffic. This research will also investigate anonymous tracking of trucks with LiDAR across two locations using advanced algorithms. This can be used to measure spatial activity and travel time performance of trucks along instrumented corridors.
working paper |
Aug 2020
published journal article