The need to rethink urban delivery is never more urgent. On the one hand, e-commerce in the US today has reached the size of $300 billion annual sales, five times ten years ago. As a result of the e-commerce growth, urban truck traffic has grown precipitously. The rise of truck traffic has led to many negative consequences to the urban environment: greater congestion, more pollution, faster wear-and-tear of road infrastructure, parking space shortage for trucking, to name just a few. On the other hand, urban delivery has been increasingly pushed by the development of livable urban communities to reduce truck traffic and its negative impacts. Supported by NSF and the World Bank, our research in this area seeks innovative solutions to reconcile the two conflicting trends. We are exploring new system designs that can fulfill the urban delivery in a more efficient, greener, and sustainable way.

We are very excited about the many technological advances in vehicle automation and sharing economy, which in our view are unveiling the curtain of one of the most significant revolutions in human mobility ever since the era of the Appian Way and the Silk Road. Driverless vehicles free people from concentrating on driving, making the time spent in a vehicle more productive or leisure. By reducing vehicle headway and accidents, driverless vehicles also allow roads to accommodate more traffic and be safer. Sharing economy enables travel more cost-effective, flexible, and increasingly on-demand. Sharing economy will further change, perhaps fundamentally, vehicle ownership and land use patterns. Keeping all these in mind, our research strives to understand the comprehensive effects of autonomous and shared mobility on human transportation, especially in urban areas.

TransLog Lab has rich experience in intercity transportation research, touching on a variety of issues related to competition among transportation operators and infrastructure capacity utilization. In the past Lab director Dr. Zou was extensively involved in investigating airline and air-rail competition, service pricing and frequency determination, system benefits of aviation infrastructure investment, airport slot control policies, and flight delay cost to the United States, among others. These involvements led to the development of multiple game-theoretic, network equilibrium, optimization, and econometric models for intercity transportation. We are currently investigating new modeling approaches to network equilibrium in unregulated intercity travel environment.

High performance intercity passenger rail has been gaining its momentum in the United States. However, the development of Higher Speed Rail (HrSR) systems on shared-use passenger and freight rail corridors imposes capacity and other related issues. Supported by the Urban Transportation Center at the University of Illinois at Chicago, we have developed a systematic modeling framework to consider the priority scheduling reality in the US rail sector and identify optimal timetables for passenger and freight trains running on shared-use rail tracks. The framework has been extended to investigating how rail capacity allocation is made through bargaining among different parties.

Infrastructure asset management involves predicting infrastructure deterioration, and scheduling maintenance, rehabilitation,and reconstruction (MR&R) activities that minimize life-cycle costs to the infrastructure agency and users over a time horizon. While planning MR&R actions, their negative impacts in disrupting normal traffic operations also need to be considered. Our efforts in this area focus on airport infrastructure assets, with enthusiastic support from the Chicago Department of Aviation. Using very rich historic data from O’Hare International Airport, statistical models have been estimated to predict the deterioration process of runway pavements at the Airport. Building on the statistical models, optimization tools are further developed which can aid Capital Investment Plan development for the Airport.

Recent advances in sensing, information, and communication technologies have brought significant potentials for devising innovative management schemes for urban parking management, in particular by transforming the state-of-the-practice which does not consider driver-specific characteristics and preferences to agent-based parking slot assignment. An important component in this transformation is to ensure truthful information reporting from drivers, which otherwise would deviate the parking slot allocation outcome from the desired system objective. We have developed and demonstrated the implementation of novel mechanisms that align drivers’ selfish behavior with the socially optimal outcome in both static and dynamic settings, which provoke voluntary participation of drivers with truthful information reporting.

One of the most important environmental concerns over transportation and logistics activities is their climate change impact. We have put forward multiple methodologies, both parametric and non-parametric, to assess short- and long-term fuel efficiency of major air carriers in the United States. The developed evaluation framework has been adopted by the International Council on Clean Transportation (ICCT) for their airline ranking purposes. We have also collaborated with researchers from the University of California at Berkeley, the NASA Ames Research Center, and the Universidad Carlos III in Spain to develop integer programming and optimal control models for flight trajectory design while accounting for the associated contrail effects.