Leveraging technology for improving urban and regional mobility

This theme focuses on examining emerging technologies such intelligent route guidance systems, dynamic road pricing, smart parking, integrated transit fare systems, app-based shared transportation services, high-speed rail, etc., and their potential for improving passenger mobility and accessibility within and between cities. The impact of connected and autonomous vehicles in increasing safety and capacity utilization, enhancing system reliability, influencing travel behaviour, and altering location choices of households and firms will be analyzed. Innovative ways of collecting and applying big data in transportation for evidence-based planning and improved real-time operations of multi-modal systems will be explored. The role of government and public policy for better leveraging technology will be considered.

Reducing environmental impacts and enhancing resilience of transportation systems

This theme focuses on exploring ways to reduce environmental impacts of transportation while meeting or improving mobility. Research areas include: a) ways to reduce carbon footprint of transport infrastructure (e.g., roads, airports, ports, public transit systems, etc.) construction, maintenance, and operation; b) new fuel and vehicle technologies across modes, including plug-in hybrids and battery electric vehicles, that significantly reduce lifecycle emissions, and c) government actions, including pricing policies as well as mandates or restrictions, to promote supply and demand of low-carbon transportation systems. Research analyzing and suggesting improvements to the multi-modal transportation system’s preparedness for short-notice (e.g., earthquake, terrorist attack, etc.) or planned (e.g., cyclone, virus outbreak, etc.) evacuation or system management at various geographic scales, and research exploring ways to develop systems that are resilient (with respect to damages and disruptions) to both short-notice events and long-term climatic changes will be covered under this theme.

Promoting sustainable and safe urban transportation

This theme focuses on research involving strategies to promote shared (e.g., public transit, car- and ride-sharing arrangements, etc.), non-motorized/active (i.e., walking and bicycling), and low-carbon (e.g., electric vehicles) transportation in India’s megacities and high-growth regions. Strategies can range from private sector initiatives/innovations in the provision and management of sustainable transportation modes and systems, to government policies (i.e., land use planning, supply-side investments, and demand management initiatives) to influence activity-travel decisions. Methods can span across disciplines, from travel behaviour analysis using revealed preference or stated-choice surveys, to experimental approaches of evaluating the impacts of specific interventions. Issues of equitable access to jobs and other urban amenities, particularly for the transportation disadvantaged, will be addressed. Research exploring ways to make urban travel safer will also be covered under this theme. This theme is aligned with global initiatives including India’s policy priority of promoting sustainable urban development, and the creation of healthy and livable cities.

Optimizing logistics networks

This theme covers research for identifying optimal locations of facilities within a network and allocating the customer orders to each location, which is an important decision area for all retailers including e-commerce players. For last mile delivery, optimal vehicle routing and minimizing customer misses are key to business profitability. Also, during disruptions, the optimal order fulfillment policies such as the choice of the warehouse location for fulfilling a customer order with due date constraints is critical. With recent growth in electric vehicles, designing and optimizing charging network for transportation is another potential research area. Other areas of optimization include identifying optimal transportation mode, route, and time choice. The methods used in optimizing networks include integer programs, queuing theory, game theory, and simulation.

Managing terminal and warehouse operations

Managing the performance of logistics facilities such as warehouses or container terminals is critical for achieving high customer service levels. Many facilities are robotized today, and we expect more warehouses will be robotized in the future. Likewise, container terminals are undergoing automation. Performance analysis of such facilities using analytical and simulation models is a key step in the design conceptualization process. While traditional optimization and simulation methods are used to analyze decision problems in container terminals such as quay crane assignment problem, berth allocation problem, yard crane assignment problem, analytical models are also useful for long-term technology investment decisions in the terminals. Also, applications of IoT is intra-logistics will be investigated. Related research will be covered under this theme.

Sustainable urban freight and last-mile connectivity

This theme will cover research aimed at improving the efficiency and reducing the negative environmental impacts of freight activity within cities. Strategies involving technological (e.g., low-carbon or non-motorized vehicles), land use based (e.g., urban consolidation centres), analytics (e.g., optimized routing), and policy (e.g., taxes or restrictions) interventions will be evaluated. Research under this theme is significant given changes in consumer demand and preferences, and concurrent innovations in logistics and supply-chains.

Improving eco-efficiency and safety of goods transportation

In India, commercial vehicles are a dominant source of CO2 emissions. Old vehicles are not only adding to the emissions but are also causing driver attrition. While the government is implementing the vehicle scrappage policies to eliminate polluting vehicles (with age more than 15 years) from the road, the implications of the scrappage policies on vehicle demand estimation, overall CO2 emissions, and driver productivity and safety are still unknown. Moreover, electric vehicles will play a significant role to cut emissions in goods transport. Further, the location of the charging stations can also affect vehicle travel route choices. This center would conduct research on policies to improve driver safety, productivity, and retention. A project that that attempts to link driving behavior with fuel efficiency and road safety has already been initiated.

This talk is based on a research study partially supported by an Alibaba Cainiao research grant. We consider the problem of designing a sparse subgraph that supports a large matching after some nodes are randomly deleted. It is motivated by how to balance the trade-off between transportation costs and network complexity in the context of middle-mile delivery operations. We study three families of sparse graph designs (namely, Clusters, Rings, and Erdos-Renyi graphs) and show both theoretically and numerically that their performance is close to the optimal one achieved by a complete graph. We test our theoretical results using real data and conclude that adding a little flexibility to the routing network can significantly reduce transportation costs. This is joint work with Yifan Feng (National University of Singapore), René Caldentey (Chicago Booth), Yuan Zhong (Chicago Booth), Bing Wang (Alibaba Cainiao), and Haoyuan Hu (Alibaba Cainiao).

Dr. Linwei Xin is an assistant professor of Operations Management at Booth School of Business, University of Chicago. His primary research is on inventory and supply chain management: designing models and algorithms for organizations to effectively "match supply to demand" in various contexts with uncertainty. His research on stochastic inventory theory by using asymptotic analysis has been recognized with several INFORMS paper competition awards, including the Applied Probability Society Best Publication Award (2019), First Place in the George E. Nicholson Student Paper Competition (2015), Second Place in the Junior Faculty Interest Group Paper Competition (2015), and a finalist in the Manufacturing and Service Operations Management Student Paper Competition (2014). His work with JD.com on dispatching algorithms for robots in intelligent warehouses was recognized as a finalist for the INFORMS 2021 Franz Edelman Award, with an estimate of billions of dollars in savings. His other honors include winning a National Science Foundation grant as a principal investigator. His research has been published in journals such as Operations Research, Management Science, Mathematics of Operations Research, and INFORMS Journal on Applied Analytics. He currently teaches MBA and PhD courses at the University of Chicago.