Hani S. Mahmassani

• PhD MIT
• Chair at Northwestern University

The headway between vehicles is an important traffic flow characteristic affecting safety, level of service, driver behavior, and capacity of a transportation system and plays an important role in the study of a broad range of problems. The primary objective of this study is to analyze the characteristics of time headways with the presence of heavy...

The data-driven characterization of discretionary lane-changing behaviors has traditionally been hindered by the scarcity of high-resolution data that can precisely record lateral movements. In this study, we conducted an exploratory investigation leveraging the Third Generation Simulation (TGSIM) dataset to advance our understanding of discretiona...

The Northwestern University Freight Rail Infrastructure and Energy Network Decarbonization (NUFRIEND) framework is a comprehensive industry-oriented tool for simulating the deployment of new energy technologies including biofuels, e-fuels, battery-electric, and hydrogen locomotives. By classifying fuel types into two categories based on deployment...

This study examines the equity impacts of integrating shared autonomous mobility services (SAMS) into transit system redesign. Using the Greater Chicago area as a case study, we compare two optimization objectives in multimodal transit network redesign: minimizing total generalized costs (equity-agnostic) versus prioritizing service in low-income a...

This paper investigates the potential of autonomous minibuses which take on-demand directional routes for pick-up and drop-off in a grid network of wider area with low density, followed by fixed routes in areas with demand. Mathematical formulation for generalized costs demonstrates its benefits, with indicators proposed to select existing bus rout...

This paper analyzes and compares patterns of U.S. domestic rail freight volumes during, and after the disruptions caused by the 2007-2009 Great Recession and the COVID-19 pandemic in 2020. Trends in rail and intermodal shipment data are examined in conjunction with economic indicators, focusing on the extent of drop and recovery of freight volumes...

To measure the impacts on U.S. rail and intermodal freight by economic disruptions of the 2007-09 Great Recession and the COVID-19 pandemic, this paper uses time series analysis with the AutoRegressive Integrated Moving Average (ARIMA) family of models and covariates to model intermodal and commodity-specific rail freight volumes based on pre-disru...

This paper investigates managed lane (ML) toll setting and its effect under mixed traffic of connected automated vehicles (CAVs), high-occupancy vehicles (HOVs), and human-driven vehicles (HDVs), with a goal to avoid flow breakdown and minimize total social cost. A mesoscopic finite-difference traffic simulation model considers the flow-density rel...

The COVID-19 vaccine development, manufacturing, transportation, and administration proved an extreme logistics operation of global magnitude. Global vaccination levels, however, remain a key concern in preventing the emergence of new strains and minimizing the impact of the pandemic's disruption of daily life. In this paper, country-level vaccinat...

To support planning of alternative fuel technology (e.g., battery-electric locomotives) deployment for decarbonizing non-electrified freight rail, we develop a convex optimization formulation with a closed-form solution to determine the optimal number of energy storage tender cars in a train. The formulation shares a similar structure to an Economi...

This paper presents an optimization framework for the joint multimodal transit frequency and shared autonomous vehicle (SAV) fleet size optimization, a problem variant of the transit network frequency setting problem (TNFSP) that explicitly considers mode choice behavior and route selection. To address the non-linear non-convex optimization problem...

Urban air mobility (UAM) has recently emerged as a promising new transportation mode, with various potential use cases. Facility location problems are well studied and of significant importance for various transportation modes. This work introduces a vertiport location identification framework, focusing on demand coverage and infrastructure accessi...

We present an employer-side perspective on remote work through the pandemic using data from top executives of 129 employers in North America. Our analysis suggests that at least some of the pandemic-accelerated changes to the work location landscape will likely stick; with some form of hybrid work being the norm. However, the patterns will vary by...

This study addresses the urban transit pattern design problem, optimizing stop sequences, headways, and fleet sizes across multiple routes simultaneously to minimize user costs (composed of riding, waiting, and transfer times) under operational constraints (e.g., vehicle capacity and fleet size). A destination-labeled multi-commodity network flow (...

This paper develops a semi-on-demand transit feeder service using shared autonomous vehicles (SAVs) and zonal dispatching control based on reinforcement learning (RL). This service combines the cost-effectiveness of fixed-route transit with the adaptability of demand-responsive transport to improve accessibility in lower-density areas. Departing fr...

This paper investigates decarbonization alternatives for the freight rail industry, considering economic, environmental, and operational aspects. The study compares battery-electric and hydrogen fuel cell locomotives, drop-in fuels including biofuels and e-fuels, and overhead catenary electrification through abatement cost analyses. Scenario analys...

This study investigates the implementation of semi-on-demand (SoD) hybrid-route services using Shared Autonomous Vehicles (SAVs) on existing transit lines. SoD services combine the cost efficiency of fixed-route buses with the flexibility of on-demand services. SAVs first serve all scheduled fixed-route stops, then drop off and pick up passengers i...

This study examines the route design of a semi-on-demand hybrid route directional service in the public transit network, offering on-demand flexible route service in low-density areas and fixed route service in higher-density areas with Shared Autonomous Mobility Service (SAMS). The study develops analytically tractable cost expressions that captur...

As the era of autonomous vehicles (AVs) approaches, understanding how passengers' time use during a trip may change from a traditional vehicle (non-AV) to an AV is important to the adoption and use of AVs. In this study, a latent class analysis (LCA) as well as a latent transition analysis (LTA) are adopted to investigate the choice of travel activ...

Traffic behavior around major freeway weaving sections exhibits complex dynamics associated with multi-directional maneuvers such as lane changes (LCs) accompanied by shockwave-generating braking. Data to study both microscopic and macroscopic properties of congested weaving sections have been generally lacking, leaving an important lacuna in the u...

This study aims to provide accurate trajectory datasets capable of characterizing human–automated vehicle interactions under a diverse set of scenarios in diverse highway environments. Distinct methods were utilized to collect data from Level 1, Level 2, and Level 3 automated vehicles: (1) fixed location aerial videography (a helicopter hovers over...

A convex optimization formulation, with similar structure to an Economic Order Quantity (EOQ) model, is developed to determine the optimal number of energy storage tender cars in a train. For given market characteristics, cost forecasts, and technology parameters, the model captures the trade-offs between inventory carrying costs associated with tr...

Connected, automated, shared, and electric (CASE) technologies are shaping Mobility 4.0—a connected, digitized, multimodal, and autonomous system of systems that is challenging past and existing strategic transportation planning practices at state and local levels. A systematic approach is presented to aid transportation agencies in their planning...

This study addresses a large-scale multimodal transit network design problem, with Shared Autonomous Mobility Services (SAMS) as both transit feeders and an origin-to-destination mode. The framework captures spatial demand and modal characteristics, considers intermodal transfers and express services, determines transit infrastructure investment an...

Advanced air mobility (AAM) is a nascent market within the aviation sector of Illinois’ transportation system, promising enhanced movement of people and cargo to previously inaccessible or underserved locations. This project addresses AAM’s prospects and impacts in the state. The research encompasses several tasks, starting with an examination of t...

This paper develops theoretical macroscopic air traffic flow models that relate vehicle density and spacing to traffic flow (throughput) measures under different operational parameters for un-structured airspace in the Advanced Air Mobility (AAM) context. Recognizing the role of conflicts in air traffic flow, we relate vehicle density to the freque...

This study addresses a large-scale multimodal transit network design problem, with Shared Autonomous Mobility Services (SAMS) as both transit feeders and an origin-to-destination mode. The framework captures spatial demand and modal characteristics, considers intermodal transfers and express services, determines transit infrastructure investment an...

This paper proposes an integrated framework of an activity-based behavior model and a multimodal transit assignment-simulation tool that captures road network congestion dynamics. The framework has two levels: the upper level is the demand-side activity-based model that decides individual travelers’ behavioral choices based on up-to-date informatio...

This paper investigates decarbonization alternatives for the freight rail industry, considering economic, environmental, and operational aspects. The study compares battery-electric and hydrogen fuel-cell locomotives, as well as biofuels and e-fuels, through abatement cost analysis. Scenario analysis identifies the cost-effectiveness of each of the...

This study examines the route design of a semi-on-demand hybrid route directional service in the public transit network, offering on-demand flexible route service in low-density areas and fixed route service in higher-density areas with Shared Autonomous Mobility Service (SAMS). The study develops analytically tractable cost expressions that captur...

This paper addresses the problem of modeling stochastic dynamic transportation networks, where travel times are random variables with time-varying distributions and spatio-temporal dependencies. It presents a taxonomy of modeling approaches used in the literature and defines extended taxonomic categories to better capture the characteristics of tra...

A key aspect of the success of shared-use autonomous mobility systems will be the ability to price rides in real time. As these services become more prevalent, it becomes of high importance to detect shifts in behavior to quickly optimize the system and ensure system efficiency and economic viability. Therefore, (1) pricing algorithms should be abl...

On-Demand Ride-Pooling services have the potential to increase traffic efficiency compared to private vehicle trips by decreasing parking space needed and increasing vehicle occupancy due to higher vehicle utilization and shared trips, respectively. Thereby, an operator controls a fleet of vehicles that serve requested trips on-demand while trips c...

This paper introduces decentralized control concepts for drones using differential game theory. The approach optimizes the behavior of an ego drone, assuming the anticipated behavior of the opponent drones using a receding horizon approach. For each control instant, the scheme computes the Nash equilibrium control signal which is applied for the co...

Urban air mobility (UAM) systems include a network of (un)structured airspaces. The geometry and operations on these networks affect system performance across several goals including safety, efficiency, and externalities. The primary goal of this work is to find and illustrate the safety, efficiency, and externality trade-offs between different sty...

This paper investigates managed lane toll setting and its effect under mixed traffic of connected automated vehicles (CAVs), high-occupancy vehicles (HOVs), and human-driven vehicles (HDVs), with the goal of avoiding flow breakdown and minimizing total social cost. A mesoscopic finite difference traffic simulation model considers the flow-density r...

Speed harmonization is an active traffic management strategy used to delay traffic flow breakdown and mitigate congestion by changing speed limits throughout a road segment based on prevailing traffic, weather, and road conditions. Traditional implementations rely on fixed roadway sensors to collect traffic information and variable speed signs at f...

The Northwestern University Freight Rail Infrastructure & Energy Network Decarbonization (NUFRIEND) framework is a comprehensive industry-oriented tool for simulating the deployment of new energy technologies including biofuels, e-fuels, battery-electric, and hydrogen locomotives. By classifying fuel types into two categories based on deployment re...

The COVID-19 vaccine development, manufacturing, transportation, and administration proved an extreme logistics operation of global magnitude. Global vaccination levels, however, remain a key concern in preventing the emergence of new strains and minimizing the impact of the pandemic’s disruption of daily life. In this paper, country-level vaccinat...

Consumer reactions to COVID-19 pandemic disruptions have been varied, including modifications in spending frequency, amount, product categories and delivery channels. This study analyzes spending data from a sample of 720 U.S. households during the start of deconfinement and early vaccine rollout to understand changes in spending and behavior one y...

The goal of this project was to develop a tool to aid railroads and other stakeholders assess and approach the decarbonization of freight rail operations by identifying new, viable low-carbon energy storage and conversion systems for future locomotive systems and how they should be deployed on the existing US freight rail network. In the first qu...

This paper analyzes and compares patterns of U.S. domestic rail freight volumes during and after the disruptions caused by the 2007-2009 Great Recession and the COVID-19 pandemic in 2020. Trends in rail and intermodal (IM) shipment data are examined in conjunction with economic indicators, focusing on the extent of drop and recovery of freight volu...

Purpose The purpose of this paper is to develop a framework to evaluate and assess the performance of the COVID-19 vaccine distribution process that is sensitive to the unique supply-side and demand-side constraints exhibited in the US vaccine rollout. Design/methodology/approach A queuing framework that operates under two distinct regimes is form...

Activity engagement and travel behavior are dynamic concepts that are inherently complex. Recently, the generational transition from baby boomers as the largest generational cohort in the US to millennials has added a layer of complexity to our understanding of activity engagement and travel behavior. The challenge stems in part from the fact that...

This study builds conceptual explanations and empirical examinations of the vulnerability response of networks under attack. Two quantities of “vulnerability” and “uncertainty in vulnerability” are defined by scrutinizing the performance loss trajectory of networks experiencing attacks. Both vulnerability and uncertainty in vulnerability quantities...

This paper is focused on the capability of autonomous minibuses following semi-on-demand routes, mostly in low density areas, as well as operating as fixed-route carriers, in areas with concentrated demand. 217 existing fixed bus routes from two transit agencies (PACE and CTA) in Chicago, measured by generalized costs. Bus routes with low and spars...

This paper investigates managed lane (ML) toll setting and its effect under mixed traffic of connected automated vehicles (CAVs), high-occupancy vehicles (HOVs), and human-driven vehicles (HDVs), with a goal to avoid flow breakdown and minimize total social cost. A mesoscopic finite-difference traffic simulation model considers the flow-density rel...

Recognizing that the COVID-19 pandemic provided a unique natural experiment in the use of Information and Communication Technologies, this report describes a 7-wave longitudinal tracking survey conducted by the Tier I Center on Telemobility to monitor the evolving consumer spending, telework, and activity participation behavior through the COVID-19...

The COVID-19 pandemic significantly altered the remote work landscape in the U.S. and there is growing evidence that at least some portion of the remote work trends will stick beyond the pandemic. However, there are many unanswered questions regarding the individual experiences with telework through the pandemic, the evolution of remote work throug...

This paper presents and tests modified service network design formulations that account for five levels of truck automation in a daily load planning setting. Given daily updates of load information , the paths for the five deployment scenarios are adjusted using two daily updating strategies. Both strategies start with a base plan in which paths ar...

The flexible nature of on-demand ride services provided by transportation network companies (TNC) has resulted in unique supply-side challenges as the industry deals with the COVID-19 pandemic. Early during the pandemic, there was a 70% decrease in the number of drivers accepting trips on TNC platforms, as individual drivers chose to reduce their r...

This paper studies the tax intervention applied to transportation network company (TNC) trips starting on January 6, 2020 in the City of Chicago. An interrupted time series (ITS) with an autoregressive integrated moving average (ARIMA) methodology is employed to infer the causal impact of the intervention on the percentage of shared trips and the c...

To ease urban congestion, advanced air mobility (AAM) proposes the use of small aerial vehicles at low altitudes for uses such as package delivery and passenger services. In a developed state, an AAM service is predicted to involve thousands of trips daily, creating much higher densities of aircraft than currently exist in any airspace. Airspace st...

Urban air taxi (UAT) is envisioned as a point-to-point, (nearly) on-demand, and per-seat operation of passenger-carrying urban air mobility (UAM) in its mature state. A high flight load factor has been identified as one of the influential components in the successful operation of UAT. However, the uncertainties in demand, aircraft technology, and c...

This paper investigates the potential of autonomous minibuses which take on-demand directional routes for pick-up and drop-off in a grid network of wider area with low density, followed by fixed routes in areas with greater demand. Mathematical formulation for generalized costs demonstrates its benefits, with indicators proposed to select existing...

This paper studies a mixed-service operation of shared-use autonomous mobility systems (SAMS) where customers can request rides either immediately or through reservations and use the vehicle for a point-to-point service or a time-slot-based rental service, respectively. Three autonomous-vehicle-to-user assignment strategies are presented: a first-c...

This study uses GPS data of 1461 participants at a planned special event organized in Oshkosh, Wisconsin named AirVenture to characterize their spatio-temporal activity participation behavior. The GPS data is used to derive activity sequences for participants and study the attractiveness of various activities at the event site. A validation procedu...

The node-place model has been used in previous studies to categorize urban transit rail stations, and to study impacts on transit station ridership. Similar studies have not been performed for intercity rail station ridership. This study uses the node-place model to examine the station-level factors affecting station ridership on the Amtrak network...

The rapid onset of the COVID-19 pandemic in March 2020 marked a challenging time for the US and its freight industry. Manufacturing slowed, consumer purchasing patterns changed, and for many, shopping moved online. The freight industry suffered a sharp decline in shipments, followed by a surprisingly quick rebound. The industry had to adapt quickly...

To measure the impacts on rail and intermodal freight by economic disruptions of the 2007-09 Great Recession and the COVID-19 pandemic, this paper uses time series analysis with Seasonal AutoRegressive Integrated Moving Average (SARIMA) and covariates to model intermodal and commodity-specific freight volumes based on pre-disruption data. By compar...

The COVID-19 pandemic required employees and businesses across the world to rapidly transition to work from home over extended periods, reaching what is likely the upper bound of telework in many sectors. Past studies have identified both advantages and disadvantages of teleworking. The pandemic experience offers a unique opportunity to examine emp...

This paper focuses on the problem of finding optimal trajectory-adaptive routing strategies in stochastic time-varying networks with generalized spatio-temporal correlations. A representation for jointly distributed continuous link travel times across the entire network with time-varying distributions and correlation structures is presented, and th...

Digital technologies are making considerable computing power and intelligence available to individuals through ubiquitous connected mobile devices. While the first and second waves of ITS deployment have focused on infrastructure-based approaches to transportation system management, the coming wave leverages individual-level sensing, multimodal mob...

As congestion levels increase in cities, it is important to analyze people’s choices of different services provided by transportation network companies (TNCs). Using machine learning techniques in conjunction with large TNC data, this paper focuses on uncovering complex relationships underlying ridesplitting market share. A real-world dataset provi...

Transportation is undergoing deep and significant transformation, seeking to fulfill the promise of connected urban mobility for people and goods, while limiting its carbon footprint. Achieving the promise of these technologies calls for concomitant development of the underlying intelligence through advanced distributed software tools that implemen...

Large-scale planned special events (PSEs) can pose unique transportation and logistics challenges. Data collection and simulation are important tools to address these challenges, although they are often difficult because of event size and complexity. This paper discusses methods to address the challenge of multimodal simulation at large PSEs throug...

Network macroscopic fundamental diagrams (NMFD) and related network-level traffic dynamics models have received both theoretical support and empirical validation with the emergence of new data collection technologies. However, the extent to which network-level macroscopic traffic models may be ready for practical implementation remains to be ascert...

The conduct of economic and social activities through information and communication technologies enabled the world to continue functioning under an unprecedented pandemic-induced disruption in normal activity and physical mobility patterns. Virtual engagement enabled work, school, entertainment, medicine and commerce to continue for extended period...

Urban air mobility (UAM) is an emerging mode that promises to provide relief to congested urban streets. UAM relies on airspace, however, which is an exhaustible resource considering minimum aircraft separation requirements. In light of these requirements and UAM vehicle attributes, a simulation is developed to explore UAM traffic flows and congest...

One of the ways to design more effective signal control strategies is to leverage and synthesize connected vehicle generated (CVG) information to identify traffic states for the controller to operate in a predictive, yet vehicle-actuated manner. The contribution of this paper is twofold: (1) it presents a framework for an advanced, online, signal c...

Transportation research has increasingly focused on the modeling of travel time uncertainty in transportation networks. From a user’s perspective, the performance of the network is experienced at the level of a path, and, as such, knowledge of variability of travel times along paths contemplated by the user is necessary. This paper focuses on devel...

We take urban mobility to the next level by considering shared mobility services offered through automated electric vertical take-off and landing (eVTOL) vehicles (“flying taxis”), enabled by new generation of eVTOL aircraft. We present various concepts for service operations at urban/regional levels, along with algorithms adapted for the real-time...

Urban air taxi (UAT) operation has gained traction with the advancements in distributed electric propulsion and the emergence of electric vertical take-off and landing aircraft. Start-up companies and aircraft manufacturers are pursuing the possibility of operating UAT at scale in urban and suburban areas and at an affordable price. However, consid...

The rapid onset of the COVID-19 pandemic in March 2020 marked a challenging time for the country and the U.S. freight industry. Manufacturing slowed, consumer purchasing patterns changed, and for many, shopping moved online. The freight industry suffered a sharp decline in shipments, followed by a surprisingly quick rise. The movement of goods by f...

The goal of this paper is to develop a modeling framework that captures the inter-decision dynamics between mobility service providers (MSPs) and travelers that can be used to optimize and analyze policies/regulations related to MSPs. To meet this goal, the paper proposes a tri-level mathematical programming model with a public-sector decision make...

The goal of this paper is to develop a modeling framework that captures the inter-decision dynamics between mobility service providers (MSPs) and travelers that can be used to optimize and analyze policies/regulations related to MSPs. To meet this goal, the paper proposes a tri-level mathematical programming model with a public-sector decision make...

This study presents a novel ensemble learning approach called stacking for real-time short-term traffic state prediction. The approach consists of a level-1 meta-learner that combines predictions from several different level-0 models by making use of the past performance information of the level-0 models. The meta-learner consists of least square e...

A focus of road network weather management systems is on integrating emerging communication technologies into transportation agencies’ weather-responsive efforts in order to enhance their effectiveness and efficiency. An important opportunity and challenge is to bring connected vehicle (CV)-enabled technology elements into real-time operational dec...

In an era of emerging vehicle automation technologies and advanced traffic management strategies, traffic simulation has become an indispensable tool for giving agencies the insight they need for adoption and implementation decisions. The importance of calibration to ensure reliability of the simulation results cannot be over-stated. Current practi...

Connected environments offer more information, improved data availability and quality which can lead to better decision making; new meaningful information adds new functionalities and opportunities to advance operational efficiency. Can traffic signal system efficiency and mobility be measured and enhanced in innovative and meaningful ways by combi...

This paper studies the problem of estimation and computation of reliable least-time paths in stochastic time-varying (STV) networks with spatio-temporal dependencies. For a given desired confidence level α, the least-time paths from any origin to a given destination node are to be found over a desired planning horizon. In STV networks, least-time p...

1. Broadest, deepest and longest natural experiment in the use of ICT for tele-activities and e-processes in modern history. From telework to e-learning, telemedicine to e-shopping and near complete reliance on e-commerce and home delivery, activity and mobility patterns have been upended and transformed dramatically. 2. “Never let a good crisis g...

Reliability is a measure of network performance that reflects the ability of the network to provide predictable travel times. Deviations from planned travel times can increase travel costs for users. To improve the system's performance, it is crucial to identify sources of unreliability, particularly the location on the network of unreliable perfor...

Traffic flow breakdown is the abrupt shift from operation at free-flow conditions to congested conditions and is typically the result of complex interactions in traffic dynamics. Because of its stochastic nature, breakdown is commonly predicted only in a probabilistic manner. This paper focuses on using stationary aggregated traffic data to capture...

This presentation addresses impact of Covid 19 crisis on supply chains in North America, based on industry interviews and an informal sample of selected carriers and shippers. Supply chain disruptions occurred primarily at nodes rather than along links. The transportation system displayed considerable resilience and continued to deliver throughout....

Information and Communication Technologies, or ICT,have rapidly emerged asan integral element of everyday life, interactingin an essential manner with mobility and the activity patterns that engender it. The current paper reflects uponthistrendandthe opportunities and challenges itrepresents.Givenmore than three decades of research in the domain of...

Information and Communication Technologies, or ICT,have rapidly emerged asan integral element of everyday life, interactingin an essential manner with mobility and the activity patterns that engender it. The current paper reflects uponthistrendandthe opportunities and challenges itrepresents.Givenmore than three decades of research in the domain of...

Freight forecasting is essential for managing, planning operating and optimizing the use of resources. Multiple market factors contribute to the highly variable nature of freight flows, which calls for adaptive and responsive forecasting models. This paper presents a demand forecasting methodology that supports freight operation planning over short...

This paper presents a quantitative analysis of the operations of shared-ride automated mobility-on-demand services (SRAMODS). The study identifies (i) operational benefits of SRAMODS including improved service quality and/or lower operational costs relative to automated mobility-on-demand services (AMODS) without shared rides; and (ii) challenges a...

Network travel time reliability can be represented by a relationship between network space-mean travel time and the standard deviation of network travel time. The primary objective of this paper is to improve estimation of the network travel time reliability with network partitioning. We partition a heterogeneous large-scale network into homogeneou...

Opinions regarding emergent sustainable transportation alternatives, such as bikeshare and e-scooters, and more traditional green alternatives like public transit, spread through social networks via opinion diffusion mechanisms , like word-of-mouth and mass media. The impact of social media on diffusion of sustainable mobility opinions is not well-...