Transportation and Urban Engineering

The Transportation and Urban Engineering group works in conjunction with the Connecticut Transportation Institute to conduct multidisciplinary research in transportation safety, urban design and regional planning. The faculty has expertise in  areas spanning sustainable transportation systems and infrastructure, complex construction projects, transportation data systems, and geographic information systems. They are dedicated researchers and teachers. They enjoy active involvement with their graduate student group. 

Featured Projects

Development and Application of a Disaggregate Artificial Realistic Data Generator for  Computationally Testing Safety Analysis Methods

Image shows a computer screen with data represented by graphs and charts.Sponsor: Federal Highway Administration, Exploratory Advanced Research Program, US DOT

Principal Investigator: John Ivan, Ph.D.

Period: 08/2019 - 08/2022

Budget: $999,999

Project Abstract

Safety analysis primarily focuses on identifying and quantifying the influence of factors contributing to traffic crash occurrence and its consequences. The traditional analysis paradigm relying on observed data only allows relative comparisons between analysis methods and is unable to say how well the methods mimic the true underlying crash generation process often unobserved or known only partially with various degrees of uncertainty. To address this limitation, the researchers plan to build a high-resolution disaggregate data generation process that mimics crash occurrence on transportation facilities. Specifically, a general framework of realistic artificial data (RAD) data generation embedded with heterogeneous causal structures for data generation is developed to synthesize crashes at a trip level while considering roadway facility, driver, and vehicle factors. These artificially generated crashes can be aggregated at any spatial or temporal resolution to mimic data from the real world and carry out systematic safety analysis methods evaluation. The proposed RAD generator is developed as a stand-alone software application. The application is customizable and can be run to prepare multiple realizations of the RAD. The proposed tool will be evaluated for two case studies involving vehicle crashes and pedestrian-related crashes.

Disaster Resilience through Diverse Evacuation and Emergency Transportation Systems

CAMMSE LogoSponsor: Center for Advanced Multimodal Mobility Solutions and Education (CAMMSE)

Principal Investigator: Jin Zhu

Period: 10/01/2019–09/30/2021

Budget: $95,069


Project Abstract

Disasters, whether natural (e.g., earthquakes, hurricanes, floods, wild fires) or man-made (e.g., terrorist attacks, chemical spills, nuclear power plant explosions), are occurring at an alarming rate in recent years. When disasters happen, evacuations move people away from high-risk areas to safer areas for the protection of life using transportation systems. In order to enhance disaster resilience, it is critical to have effective and efficiency evacuation and emergency transportation systems. While in reality, evacuations are usually realized via various transportation modes, there are limited studies on evacuee’s choice and the outcomes in multimodal transportation systems. Therefore, the objective of this proposed study is to investigate the impacts of the level of diversity of transportation systems on evacuation choice and performance. To this end, we propose to develop an integrated framework consisting of metrics and methods to quantify the diversity of transportation systems in case study communities, and investigate the potential relationships with evacuation choice based on data collected from household surveys and focus groups. The outcomes of the proposed study can be used as input into simulation models to better predict system-level evacuation under different planning scenarios in disasters. Stakeholders from various agencies (e.g., DOT, emergent management office) can benefit from this study by better assessing and improving the diversity level of transportation systems, and making informed decisions in coping with disasters considering the transportation system characteristics.

Prioritizing People - Mixed Equilibrium Assignment for AV Based on Occupancy

Self Driving CarSponsor: Center for Advanced Multimodal Mobility Solutions and Education (CAMMSE)

Principal Investigator: Nicholas Lownes

Period: 10/01/2019–09/30/2021

Budget: $46,819


Project Abstract

Autonomous Vehicles (AV) have the potential to revolutionize transportation operations mode choice. In June 2017, Connecticut Public Act No. 17-69 “An Act Concerning Autonomous Vehicles” authorized the testing of AVs on Connecticut roads. In April 2018, Connecticut launched the Fully Autonomous Vehicle Testing Pilot Program (FAVTPP), which set the permitting and testing requirements for AVs on public roads. Although there is optimism that introduction of AVs will mitigate traffic congestion and vastly improve safety, the transition to a completely AV fleet - which will take time - presents non-trivial problems. In the United States, automobiles did not begin to outnumber horses on roadways until the late 1920’s, twenty years after the first Model T rolled off the production line. If a similar timeline for AV deployment and market penetration holds, we won’t see AVs outnumber human-driven vehicles until sometime in the 1930’s and won’t see a completely autonomous fleet until somewhat later. This means that for the next 20+ years we will be operating in a mixed traffic environment including human-driven vehicles, occupied AVs and unoccupied AVs.

Some AVs will operate as part of a centrally owned, shared autonomous fleet in which vehicles are routed according to realtime requests similar to current human-driven e-hailing services. However, a not insignificant portion of AVs will continue to be owned by a single household. The availability of an AV in a household may allow them to own fewer vehicles at a considerable cost savings, as a single AV could be used to meet multiple household members’ tripmaking needs provided it could reach the next household member in time to get them to their destination on time. This means that a significant portion of the AV travel time will be unoccupied, depending on the tripmaking needs of the household. These unoccupied AVs will impact the travel times of occupied AV and human-driven vehicles.

It seems obvious that the travel needs of occupied vehicles (AV and human-driven) should be prioritized, and that empty AVs should be routed to minimize the impacts on occupied vehicles. However, if unoccupied AVs are assigned a route that is too circuitous, it may not be able to meet a household’s tripmaking needs – requiring additional vehicles and eliminating the cost savings for the household of owning an AV.

The central research question of this proposal is: How do we route unoccupied AVs to minimize the impacts on occupied vehicles without disproportionally hurting households that own an AV? The proposed research will focus on the following topics:

1) Mitigating travel delays experienced by occupied vehicles by minimizing the impact of empty AV route choice.

2) Differential route assignment for occupied versus unoccupied vehicles while considering impacts of unoccupied AV route choice on AV owners.

3) Application of the methodology on a Hartford, CT case study.