Moshe Ben-Akiva

Massachusetts Institute of Technology | MIT

In the rapidly advancing field of automated driving systems, the automated vehicle subscription (AVS) can provide the easiness of trialing the latest automated vehicle (AV) technologies at a monthly cost and gather significant customer interest. However, a gap in the literature remains regarding attitudes and willingness to pay (WTP) towards this i...

This paper proposes a multi-day needs-based model for activity and travel demand analysis. The model captures the multi-day dynamics in activity generation, which enables the modeling of activities with increased flexibility in time and space (e.g., e-commerce and remote working). As an enhancement to activity-based models, the proposed model captu...

Conventional shipment data collection methods are limited due to intense labor, and lack of details on shipment paths and stops. In this view, we develop an innovative shipment survey methodology using Future Mobility Sensing (FMS)—Freight to collect shipment data at path-based origin–destination level and minimize respondent burden. FMS—Freight is...

This study applies an agent-based approach to investigate the potential individual-level demand for and system-wide impacts of Urban Air Mobility (UAM) in the short- to long-term, in two U.S. metropolitan areas. The UAM service we envision in this research provides mobility to on-demand requests from one vertiport to another. The investigations con...

In most cities, transit consists solely of fixed-route transportation, whence the inherent limited Quality of Service for travellers in suburban areas and during off-peak periods. On the other hand, completely replacing fixed-route (FR) with demand-responsive (DR) transit would imply a huge operational cost. It is still unclear how to integrate DR...

Through the vast adoption and application of emerging technologies, the intelligence and autonomy of smart mobility can be substantially elevated to address more diversified demands and supplies. Along with this trend, a systematic collaboration among three essential elements of smart mobility services, namely devices, data and functions, is being...

Congestion pricing is a standard approach to mitigate traffic congestion in a number of urban networks around the world. The advancement of satellite technology has spurred interest in distance-based congestion pricing schemes, which obviate the need for fixed infrastructure such as gantries that are used in area- and cordon-based pricing. Moreover...

Tradable credit schemes (or tolling in tokens) are a form of quantity control, which promise to be an appealing alternative to congestion pricing (or tolling in dollars) owing to considerations of revenue neutrality, equity, reduced infrastructure costs, and political acceptability. The comparative performance of the two instruments under uncertain...

Discrete choice models (DCMs) require a priori knowledge of the utility functions, especially how tastes vary across individuals. Utility misspecification may lead to biased estimates, inaccurate interpretations and limited predictability. In this paper, we utilize a neural network to learn taste representation. Our formulation consists of two modu...

The e-commerce market has grown rapidly in the past two decades. The need for predicting e-commerce demand and evaluating relevant policies and solutions is increasing. However, the existing simulation models for e-commerce demand are still limited and do not consider the impacts of delivery options and their attributes that shoppers face on multip...

This study extends the current literature on tradable credit schemes (TCS) for congestion management with a %distance-, travel time- and trip- and area-based design, examining its efficiency, effectiveness and properties in the context of the morning commute problem using a trip-based Macroscopic Fundamental Diagram model. In our proposed TCS, the...

The emergence of ride-sourcing services has radically changed travel behavior and has important implications for future urban mobility. However, despite the growing market for mobility-on-demand (MOD), empirical studies on the operational characteristics of ride-sourcing systems are sparse. This paper provides an exploratory analysis of the operati...

Calibration is an essential process in making an agent-based simulator operational. In particular, the calibration for freight demand is challenging because of the model complexity and the shortage of available freight demand data compared with passenger data. This paper proposes a novel calibration method that relies solely on screenline counts, n...

A growing body of research looks specifically at freight vehicle parking choices for purposes of deliveries to street retail, and choice impacts on travel time/uncertainty, congestion, and emissions. However, little attention was given to large urban freight traffic generators, e.g., shopping malls and commercial buildings with offices and retail....

The use of on-demand ride services has continued to grow rapidly in recent years. At some point, given current technologies of automation, it is plausible that these rides will be driverless, termed automated mobility-on-demand (AMoD). This research examines how eager people are to adopt AMoD ride services and whether they will change their travel...

In most cities, transit consists of fixed-route transportation only, whence the inherent limited Quality of Service for travellers in sub-urban areas and during off-peak periods. On the other hand, completely replacing fixed-route with demand-responsive (DR) transit would imply huge operational cost. It is still unclear how to ingrate DR transporta...

Collecting accurate travel data is vital for transportation planning purposes. Regional travel demand forecasts as well as transportation system analyses depend on datasets that provide origins and destinations of travel for various modes, purposes of travel, socio-economic characteristics of the system users, and other attributes critical for unde...

Time-sensitive parcel deliveries—shipments requested for delivery in a day or less—are an increasingly important aspect of urban logistics. It is challenging to deal with these deliveries from a carrier perspective. These require additional planning constraints, preventing the efficient consolidation of deliveries that is possible when demand is we...

Calibration is an essential process to make an agent-based simulator operational. Especially, the calibration for freight demand is challenging due to the model complexity and the shortage of available freight demand data compared with passenger data. This paper proposes a novel calibration method that relies solely on screenline counts, named Scre...

Autonomous vehicle (AV) technologies are under constant improvement with pilot programs now underway in several urban areas worldwide. Modeling and field-testing efforts are demonstrating that shared mobility coupled with AV technology for automated mobility on-demand (AMoD) service may significantly impact levels of service and environmental outco...

Simulation-based Dynamic Traffic Assignment models have important applications in real-time traffic management and control. The efficacy of these systems rests on the ability to generate accurate estimates and predictions of traffic states, which necessitates online calibration. A widely used solution approach for online calibration is the Extended...

Simulation-based Dynamic Traffic Assignment models have important applications in real-time traffic management and control. The efficacy of these systems rests on the ability to generate accurate estimates and predictions of traffic states, which necessitates online calibration. A widely used solution approach for online calibration is the Extended...

The rapid growth in online shopping and associated parcel deliveries prompts investigation of the factors that contribute to parcel delivery demand. In this study, we evaluated the influence of locational and household characteristics on e-commerce home delivery demand. While past research has largely focused on the impacts of the adoption of onlin...

Advancements in information and communication technologies (ICT) and the advent of novel mobility solutions have brought about drastic changes in the urban mobility environment. Pervasive ICT devices acquire new sources of data that can inform detailed transportation simulation models, and are useful in analyzing new policies and technologies. In t...

Technological advancements have focused increasing attention on Automated Mobility-on-Demand (AMOD) as a promising solution that may improve future urban mobility. During the last decade, extensive research has been conducted on the design and evaluation of AMOD systems using simulation models. This paper adds to this growing body of literature by...

Advances in urban freight modeling and the availability of freight vehicle operations data have enabled the use of disaggregate models to evaluate urban delivery policies and solutions. This research assesses different model specifications for urban freight simulation and their influence on flow reproducibility, with a focus on trip- and tour-based...

This paper discusses capabilities that are essential to models applied in policy analysis settings and the limitations of direct applications of off-the-shelf machine learning methodologies to such settings. Traditional econometric methodologies for building discrete choice models for policy analysis involve combining data with modeling assumptions...

In cities around the world, transit is currently provided with fixed route transportation only, whence the inherent limited Quality of Service (QoS) for travelers in sub-urban areas and during off-peak. On the other hand, it has been shown that completely replacing fixed-route with demand-responsive transit fails to serve the high transportation de...

Integrating Fixed and Demand-Responsive Transportation for Flexible Transit Network Design

Mobility-as-a-Service (MaaS) is based on the notion that consumers and transport providers access a centralized platform for the planning, payment, and management of trips and combines multiple modes of transportation designed to increase the efficiency of the system. MaaS offers substantial societal benefits, including the reduction of emissions,...

The emergence of ride-sourcing platforms has brought an innovative alternative in transportation, radically changed travel behaviors, and suggested new directions for transportation planners and operators. This paper provides an exploratory analysis on the operations of a ride-sourcing service using large-scale data on service performance. Observat...

Technological advancements have brought increasing attention to Automated Mobility on Demand (AMOD) as a promising solution that may improve future urban mobility. During the last decade, extensive research has been conducted on the design and evaluation of AMOD systems using simulation models. This paper adds to this growing body of literature by...

The e-commerce delivery demand has grown rapidly in the past two decades and such trend has accelerated tremendously due to the ongoing coronavirus pandemic. Given the situation, the need for predicting e-commerce delivery demand and evaluating relevant logistics solutions is increasing. However, the existing simulation models for e-commerce delive...

Time-sensitive parcel deliveries, shipments requested for delivery in a day or less, are an increasingly important research subject. It is challenging to deal with these deliveries from a carrier perspective since it entails additional planning constraints, preventing an efficient consolidation of deliveries which is possible when demand is well kn...

The growing demand for urban mobility highlights the need for relevant and sustainable solutions in cities worldwide. Thus, we develop and implement a framework to analyze the systemic impacts of future urban mobility trends and policies. We build on prior work in classifying the world’s cities into 12 urban typologies that represent distinct land-...

While collecting data for estimating discrete-choice models, researchers often encounter missing information in observations. In addition, endogeneity can occur whenever the error term is not independent of the observed variables. Both problems result in inconsistent estimators of the model parameters. The problems of missing information and endoge...

Real-time network control strategies such as congestion pricing have been used in a number of metropolitan areas around the world for traffic congestion mitigation. Recent advances in Global Navigation Satellite System (GNSS) technology have led to increasing interest in distance- or usage-based road pricing as an effective alternative to tradition...

Peak and off-peak pricing strategies are an important policy tool used to spread peak demand in public transportation systems. This study uses an agent-based simulator (SimMobility Mid-term) to examine the impact of pricing (off-peak fare discounts) strategies used in Singapore. The aim of the paper is to demonstrate the capabilities of the simulat...

This study addresses the problem of calibrating utility-maximizing nested logit activity-based travel demand model-systems. After estimation, it is common practice to use aggregate measurements to calibrate the estimated model-system’s parameters prior to their application in transportation planning, policy making, and operations. However, calibrat...

This paper introduces a new data-driven methodology for nested logit structure discovery. Nested logit models allow the modeling of positive correlations between the error terms of the utility specifications of the different alternatives in a discrete choice scenario through the specification of a nesting structure. Current nested logit model estim...

Peak and off-peak pricing strategies are an important policy tool used to spread peak demand in public transportation systems. This study uses an agent-based simulator (SimMobility Mid-term) to examine the impact of pricing (off-peak fare discounts) strategies used in Singapore. The aim of the paper is to demonstrate the capabilities of the simulat...

The advent of autonomous vehicle technologies and the emergence of new ride-sourcing business models has spurred interest in Automated Mobility-on-Demand (AMOD) as a prospective solution to meet the challenges of urbanization. AMOD has the potential of providing a convenient, reliable and affordable mobility service through more competitive cost st...

Despite significant advances in freight transport modeling in recent years, there is still lack of available tools for evaluating novel logistics solutions. We introduce the framework of SimMobility Freight, which is part of SimMobility, a multi-scale agent-based urban transportation simulation platform. SimMobility Freight is capable of simulating...

This paper presents a methodology for enhancing discrete choice models for managed lane travel behavior with personal trip history. We refer to this process as personalization and the enhanced model as a personalized choice model. With the objective of better understanding managed lane choices and improving the model’s prediction capability, person...

Urban deliveries are traditionally carried out with vans or trucks. These vehicles tend to face parking difficulties in dense urban areas, leading to traffic congestion. Smaller and nimbler vehicles by design, such as cargo-cycles, struggle to compete in distance range and carrying capacity. However, a system of cargo-cycles complemented with strat...

Understanding factors that drive the parking choice of commercial vehicles at delivery stops in cities can enhance logistics operations and the management of freight parking infrastructure, mitigate illegal parking, and ultimately reduce traffic congestion. In this paper, we focus on this decision-making process at large urban freight traffic gener...

Recent advancements in automated vehicle technology and the concurrent emergence of ride-hailing services have focused increasing attention on Automated Mobility-on-Demand (AMOD; a system of shared driverless taxis) as a potential solution for sustainable future urban mobility. However, the impacts of an unrestricted deployment of AMOD are as yet u...

As demand for urban mobility continues to grow and given that over 60% of the world's population is expected to be urban by 2050, increasingly innovative solutions must be devised to adequately meet the transportation needs of global metropolitan areas. Our objective is to therefore develop and implement a framework to analyze the systemic impacts...

Modeling shipment size for intra-city shipments is a subject that has not been sufficiently addressed in past research, despite its growing importance in disaggregate freight modeling. While past research on shipment size estimation mainly focuses on inter-city shipments, intra-city shipments differ from them in various aspects. In filling this res...

Freight forecasting models have been significantly improved in recent years, especially in the field of goods vehicle behavior modeling. On the other hand, the improvements to commodity flow modeling, which provide inputs for goods vehicle simulations, were limited. Contributing to this component in urban freight modeling systems, we propose an err...

Urban freight transport is primarily fulfilled by commercial road vehicles. Within cities, overnight parking is a critical element influencing commercial vehicle operations, particularly for heavy vehicles with limited parking options. Providing adequate overnight parking spaces for commercial vehicles tends to be a challenge for urban planners. In...

Endogeneity arises in discrete choice models due to several factors and results in inconsistent estimates of the model parameters. In adaptive choice contexts such as choice-based recommender systems and adaptive stated preferences (ASP) surveys, endogeneity is expected because the attributes presented to an individual in a specific menu (or choice...

Urban traffic congestion has led to an increasing emphasis on management measures for more efficient utilization of existing infrastructure. In this context, this paper proposes a novel framework that integrates real-time optimization of control strategies (tolls, ramp metering rates, etc.) with the generation of traffic guidance information using...

Discrete choice models (DCMs) and neural networks (NNs) can complement each other. We propose a neural network embedded choice model - TasteNet-MNL, to improve the flexibility in modeling taste heterogeneity while keeping model interpretability. The hybrid model consists of a TasteNet module: a feed-forward neural network that learns taste paramete...

This research presents the data collection, specification and estimation of a route choice model for intercity truck trips, with a focus on toll road usage. The data was obtained from driver-validated and enhanced GPS records. A mixed logit model with a path-size factor is specified. It accounts for heterogeneity among drivers using distributed coe...

This paper introduces a new data-driven methodology for estimating sparse covariance matrices of the random coefficients in logit mixture models. Researchers typically specify covariance matrices in logit mixture models under one of two extreme assumptions: either an unrestricted full covariance matrix (allowing correlations between all random coef...

We propose the use of feature-variant clustering methods, OPTICS and HDBSCAN*, as a systematic approach for tolling zone definition to operationalize distance-based tolling schemes. We develop a framework for predictive distance-based toll optimization to evaluate network performance for various tolling zone definitions derived from feature-variant...

Shipment size modeling for intra-city shipments is one of the subjects which have not been sufficiently addressed in past research, despite its growing importance on disaggregate freight modeling. While the past research on shipment size estimation mainly focuses on inter-city shipments, intra-city shipments are different from the inter-city shipme...

This paper presents a systematic way of understanding and modeling traveler behavior in response to on-demand mobility services. We explicitly consider the sequential and yet inter-connected decision-making stages specific to on-demand service usage. The framework includes a hybrid choice model for service subscription, and three logit mixture mode...

Freight vehicle tours and tour-chains are essential elements of state-the-art agent-based urban freight simulations as well as key units to analyse freight vehicle demand. GPS traces are typically used to extract vehicle tours and tour-chains and became available in a large scale to, for example, fleet management firms. While methods to process thi...

Logit mixture models have gained increasing interest among researchers and practitioners because of their ability to capture unobserved taste heterogeneity. Becker et al. (2018) proposed a Hierarchical Bayes (HB) estimator for logit mixtures with inter- and intra-consumer heterogeneity (defined as taste variations among different individuals and am...

In this paper, we simulate the impacts of Automated Mobility-on-Demand (AMoD) using SimMobility, an integrated land-use transport micro-simulation platform. Using data for Singapore, we examined the future scenarios in which AMoD is added as an additional mode on top of existing modes, or as an exclusive one. We found that AMoD may lead to changes...

In this paper, we simulate the impacts of Automated Mobility-on-Demand (AMoD) using SimMobility, an integrated land-use transport micro-simulation platform. Using data for Singapore, we examined the future scenarios in which AMoD is added as an additional mode on top of existing modes, or as an exclusive one. We found that AMoD may lead to changes...

In studies of human mobility, there is a need for a holistic system for collection of sensing data, management of data flows, fusion of multiple data sources, and visualization of integrated data to better understand travel behavior. We have designed and implemented a generic Future Mobility Sensing (FMS) system to serve these purposes. FMS harness...

Urban mobility significantly contributes to global carbon dioxide emissions. Given the rapid expansion and growth in urban areas, cities thus require innovative policies to ensure efficient and sustainable mobility. Urban typologies can serve as a vehicle for understanding dynamics of cities, which exhibit high variability in form, economic output,...

The paper presents the system optimization (SO) framework of Tripod, an integrated bi-level transportation management system aimed at maximizing energy savings of the multi-modal transportation system. From the user’s perspective, Tripod is a smartphone app, accessed before performing trips. The app proposes a series of alternatives, consisting of...

Mobility on demand (MoD) systems have recently emerged as a promising paradigm for sustainable personal urban mobility in cities. In the context of multi-agent simulation technology, the state-of-the-art lacks a platform that captures the dynamics between decentralized driver decision-making and the centralized coordinated decision-making. This wor...