The Urban Mobility and Equity Center

Archived UMEC Reports

• A Knowledge-Based Expert System for Pedestrian Safety Improvement at Intersections

  This study introduces an enhanced Knowledge-Based Expert System (KBES) designed to efficiently generate optimal cost-benefit countermeasures for improving pedestrian safety at intersections by analyzing contributing factors and optimizing countermeasure selection.

• Optimum Connected Vehicle Speed Control on Signalized Roadways in Mixed Flow

  The proposed research effort will be the first study to develop a general eco-driving strategy for vehicles with mixed engine types at signalized intersections.

• A Comparative Study of Pedestrian Crossing Behavior and Safety in Baltimore and Washington, D.C., Using Video Surveillance

  This UMEC project uses video surveillance of locations in Baltimore, Maryland, and Washington, D.C., to compare pedestrian-related travel behavior in the two neighboring cities, information needed to reduce pedestrian deaths.

• Quantifying the Impact of Cellular Vehicle-to-everything (C-V2X) on Transportation System Efficiency, Energy and Environment

  This project examines how V2X-based eco-routing can be used to reduce fuel consumption and increase fuel efficiency in a simulated traffic environment.

• Analysis of Interrelated Network Improvement Alternatives

  This research develops methods for optimizing the selection, sequencing and scheduling for various types of improvements for road networks.

• The Effect of COVID-19 on Mobility and Equity: A Case Study on Transit Users in Baltimore, Maryland

  This UMEC research investigates the effect of the COVID-19 pandemic on public transit riders and operators in the Baltimore Metropolitan Area.

• User Preference Analysis for Mobility-as-a-Service (MaaS) and Its Impact in Maryland

  Maas will be a major mobility trend in the future and this research will show its future benefits.

• Two-Dimensional Modeling of Bicycle Behavior

  This study develops a descriptive model that is capable of capturing the inherent non-lane-based trafficbehavior characteristics of bicycles and presents a naturalistic dataset for future bicycle motion modeling.

• Integrated Optimal Transit Network Design with MaaS Implementation

  This research develops mathematical modeling for MaaS implementation.

• Optimal Trajectory Planning Algorithm for Connected and Autonomous Vehicles Towards Uncertainty of Actuated Traffic Signals

  This report aims to develop an optimization algorithm for vehicle speed control in the vicinity of actuated signalized intersections.

• Investigating Walking and Biking Activities Among Low-Income African Americans

  This study provides deeper insights into bike travel and bike travel behavior among different income groups and races in the U.S.

• Public Education about Occupant ProtectionTechnologies and Protecting Occupants with Disabilities

  Exploring occupant protection technologies designed to protect those with disabilities.

• Shared Bus/Bike Lane Safety Analysis: Assessing Multimodal Access and Conflicts (Collaborative Project)

  Dedicated bus facilities are being installed, and many jurisdictions allows cyclists to use them. This study will analyze cyclist safety in shared bus-bike lanes.

• Educating the Public about Distracted Driving and Evaluating Distraction-Prevention Technologies

  Research and public outreach initiatives to address distracted driving and prevention technologies.

• Developing an Intelligent Connected Vehicle based Traffic State Estimator

  This work should provide a smart, real-time approatch to tranportation agencies to estimate the number of vehicles on the road.

• Investigating the Effect of Connected Vehicles (CV) Route Guidance on Mobility and Equity (Collaborative Project)

  This research developed and calibrated a microscopic traffic simulation model to replicate the fairly realistic behavior of connected vehicles in the traffic simulation environment.

• Bicyclist Longitudinal Motion Modeling

  This UMEC research effort proposes to model bicyclist longitudinal motion while accounting for bicycle interactions using vehicular traffic flow techniques.

• How Mobility and Accessibility Affect Crime Rates: Insights from Mobile Device Location Data

  This study investigates possible correlations between mobility, accessibility and crime rate.

• EQUITABLE COMPLETE STREETS: Data and Methods for Optimal Design Implementation

  This UMEC project analyzes different components of Complete Streets design and use with the goal of creating fast, low-cost, and high impact (transportation) changes in our communities.

• Impact of COVID-19 on Ridehailing and Other Modes of Transportation

  This research explores the changes in ridesharing travel during COVID-19 and the associated changes in other transportation modes.

• Integrated Optimization of Vehicle Speed Control and Traffic Signal Timing: System Development and Testing

  The proposed approach in this UMEC project entails designing two integrated control systems for connected automated vehicles (CAVs) and connected vehicles (CVs), which will be tested in a microscopic traffic simulation software and a driving simulator, respectively.

• Multi-depot and Multi-school Bus Scheduling Problem with School Bell Time Optimization

  This research studies the multi-depot and multi-school bus scheduling problem with school bell time optimization (MDBSPBO) with the goal of minimizing the total number of buses and the total deadhead duration.

• Managing the Impacts of Different CV/AV Penetration Rates on Recurrent Freeway Congestion From the Perspective of Traffic Management: A Case Study of MD-100

  This study established that at each AV penetration level, there exists a set of optimal behavioral mechanisms for the AV flows to coordinate with non-AV flows to best use the roads and reduce congestion.

• Innovative Methods for Delivering Fresh Foods to Underserved Populations (Collaborative Project)

  This study considered six options for last-mile fresh food delivery systems for individuals in food deserts, optimized them and analyzed costs.

• Development of Multimodal Traffic Signal Control (Core Project)

  The study developed a novel multi-modal traffic signal control system that integrates connected and automated vehicle (CAV) applications.

• Optimization of Emergency Traffic Patrols (ETP) Operations (Collaborative Project)

  Effective incident management relies on many tools to lessen the impact of crashes, road debris and disabled vehicles. This model can be used to design an effective network.

• Evaluating Equity Issues for Managed Lanes: Methods for Analysis and Empirical Results

  Managed lanes can mitigate congestion without building new infrastructure, but such policies should also be evaluated for equity considerations, especially for drivers with lower incomes.

• Sustainable Design of Concrete Bus Pads to Improve Mobility in Baltimore City

  This research project, which included a case study, examined concrete bus pads in Baltimore City to determine why they required more than routine maintenance due to surface cracks and local failure.

• Dynamic (Time Dependent) Green Vehicle Routing Problem

  This research summarizes recent studies on two versions of the Vehicle Routing Problem, i.e., the time-dependent vehicle routing problem (TD-VRP) and the green vehicle routing problem (G-VRP), for which a time-dependent version was also developed.

• Optimal Automated Demand Responsive Feeder Transit Operation and Its Impact

  This research developed an algorithm for the optimal flexible feeder bus routing, which will be come more realistic as automated vehicles become available.

• Traffic State Prediction: A Traveler Equity and Multi-modal Perspective (Core Project)

  This research addresses transportation system state prediction problems considering private vehicles, public transit, and bike share services within the context of a multimodal transportation system.

• Optimized Development Of Urban Transportation Networks (Core Project)

  This project develops general-purpose methods for optimizing the selection, sequencing, and scheduling of interrelated improvement projects in transportation networks, with special emphasis on relatively dense urban networks.

• Investigating the Impact of Distracted Driving among Different Socio-Demographic Groups (Core Project) (formerly "Hands on Wheel, Eyes on Road" Campaign)

  Distracted driving is a major source of crashes in the U.S. and Maryland. As part of this study, which uses driving simulators and eye-tracking software to study the effects of distracted driving, an educational video was produced to illustrate the dangers of distracted driving.

• Driver's Interactions with Advanced Vehicles in Various Traffic Mixes and Flows (connected and autonomous vehicles (CAVs) electric vehicles (EVs), V2X, trucks, bicycles and pedestrians) - Phase I: Driver Behavior Study and Parameters Estimation

  This research investigated the behaviors of ACVs and V2Xs in the road network to establish parameters for these new types of vehicles in traffic simulation.

• Fare Free Public Transportation: A full-scale real-world experiment in Alexandria, Virginia

  This project offers the unique opportunity to monitor an ambitious project that aims at providing a fare free, frequent service that offers larger coverage and increased connectivity.

• E3: Evaluating Equity in Evacuation: A Practical Tool and A Case Study (Collaborative Project)

  This project allows officials to accurately account for vulnerable populations in the event of a natural disaster and plan accordingly.

• Developing and Testing an ECO-Cooperative Adaptive Cruise Control System for Buses (Collaborative Project)

  This research extends the Eco-Cooperative Adaptive Cruise Control (Eco-CACC) system previously developed by the research team for light duty vehicles (LDVs) to heavy duty vehicles (HDVs) such as diesel and hybrid electric buses.

• Understanding Access to Grocery Stores in Food Deserts in Baltimore City

  Using the results of a survey of 573 people, this study identified user-generated data-driven indicators with statistical significance for developing a novel food desert metric using CHAID decision trees.

• Developing a Connected Vehicle Transit Signal Priority System (Part I)

  This study developed an advanced decentralized transit signal priority (TSP) system using a cycle-free Nash bargaining (NB) signal control system.

• Improving Public School Bus Operations Boston and Baltimore County Public Schools

  This project coupled historical and real-time traffic data with an advanced routing algorithm to improve service.

• Developing an Eco-Cooperative Adaptive Cruise Control System for Electric Vehicles (Collaborative Project)

  This research develops an Eco-Cooperative Adaptive Cruise Control System for electric vehicles, extending the system previously developed by the research team for internal combustion engines.

• Energy Efficient Transportation Modeling (Core Project)

  This project, which creates a dynamics-based cycling acceleration model, focuses on both bicycles and rail transportation.

• Developing and Testing an Advanced Hybrid Electric Vehicle Eco-Cooperative Adaptive Cruise Control System at Multiple Signalized Intersections (Collaborative Project)

  This research proposes to develop an advanced Eco-Cooperative Adaptive Cruise Control System (Eco-CACC) for hybrid electric vehicles (HEVs) to pass signalized intersections with energy-optimized speed profiles, with the consideration of impacts by multiple signalized intersections.

• Optimized Development of Urban Transportation Networks 2.0

  This project helps officials evaluate, select and plan projects in a transportation network.

• A Study of the Impact of Ride-hailing on Public Transit Ridership

  This study explores the considerable impact of ride-hailing on transit.

• Estimating Traffic Stream Density Using Connected Vehicle Data

  This research develops a machine-learning model to provide real-time estimates of the level of market penetration and improve the accuracy of vehicle counts.

• Equity in Accessibility to Opportunities: Insights, Measures, and Solutions based on Mobile Device Location Data

  This study is the first of its kind to use this type of data to measure access to opportunities.

• E-Bikes' Effect on Mode and Route Choice: A Case Study of Richmond, VA Bike Share

  This case study examined e-bike use as Richmond, Virginia's, bike share program incorporated e-bikes into its fleet.

• Adoption and Diffusion of Electric Vehicles in Maryland

  Reliable predictions are needed as a basis for strategic decisions for both private companies and public policies in favor of EVs.

• Developing Optimal Peer-to-Peer Ridesharing Strategies

  This research optimizes the vehicle-rider matching and vehicle routing and develops sustainable financial policies including financial incentives for ridesharing providers, adequate costs for the ridesharing recipients, and potential subsidies in order to promote P2P ridesharing.

• Estimating switching times of Actuated Coordinated Traffic Signals: A deep learning approach

  This study uses data from signalized intersections with multiple deep learning and machine learning technique to provide estimates of traffic signal switching times; these estimates enable more fuel-efficient operations.