Data

Predicting driver destination using machine learning techniques

Manasseh, Christian
Raja Sengupta
2013

In this paper we present a method for predicting the driver's destination with 96% accuracy. Knowing the driver's destination has many useful applications in traffic safety, traffic mobility, and influencing driver behavior. Furthermore, a software application that can predict the driver's destination can reduce the burden on the driver from manually entering the destination address on small-screen mobile devices. Current methods for predicting driver destination do that by predicting the driver's route. Those methods result in 72% accuracy if relying only on GPS traces. By providing...

Quantifying Transit Travel Experiences from the Users’ Perspective With High-Resolution Smartphone and Vehicle Location Data: Methodologies, Validation, and Example Analyses

Carrel, Andre
Lau, Peter S. C.
Mishalani, Rabi G.
Raja Sengupta
Joan Walker
2015

While transit agencies have increasingly adopted systems for collecting data on passengers and vehicles, the ability to derive high-resolution passenger trajectories and directly associate them with transit vehicles in a general and transferable manner remains a challenge. In this paper, a system of integrated methods is presented to reconstruct and track travelers usage of transit at a detailed level by matching location data from smartphones to automatic transit vehicle location (AVL) data and by identifying all out-of-vehicle and in-vehicle portions of the passengers trips. High-...

Quantifying Transit Travel Experiences from the Users’ Perspective with High-Resolution Smartphone and Vehicle Location Data: Methodologies, Validation, and Example Analyses

Carrel, Andre
Lau, Peter S. C.
Mishalani, Rabi G.
Raja Sengupta
Joan Walker
2015

While transit agencies have increasingly adopted systems for collecting data on passengers and vehicles, the ability to derive high-resolution passenger trajectories and directly associate them with transit vehicles in a general and transferable manner remains a challenge. In this paper, a system of integrated methods is presented to reconstruct and track travelers usage of transit at a detailed level by matching location data from smartphones to automatic transit vehicle location (AVL) data and by identifying all out-of-vehicle and in-vehicle portions of the passengers trips. High-...

Quantifying Transit Travel Experiences from the Users’ Perspective with High-resolution Smartphone and Vehicle Location Data: Methodologies, Validation, and Example Analyses

Carrel, Andre
Lau, Peter S. C.
Mishalani, Rabi G.
Raja Sengupta
Joan Walker
2015

While transit agencies have increasingly adopted systems for collecting data on passengers and vehicles, the ability to derive high-resolution passenger trajectories and directly associate them with transit vehicles in a general and transferable manner remains a challenge. In this paper, a system of integrated methods is presented to reconstruct and track travelers usage of transit at a detailed level by matching location data from smartphones to automatic transit vehicle location (AVL) data and by identifying all out-of-vehicle and in-vehicle portions of the passengers trips. High-...

In Pursuit of the Happy Transit Rider: Dissecting Satisfaction Using Daily Surveys and Tracking Data

Carrel, Andre
Mishalani, Rabi G.
Raja Sengupta
Joan Walker
2016

This paper demonstrates the power and value of connecting satisfaction surveys from public transportation passengers to smartphone tracking data and automatic vehicle location (AVL) data. The high resolution of the smartphone location data allows travel times to be dissected into their individual components, and the connection with AVL data provides objective information on personal-level experiences of the respondents. Analyses show how these data can provide a quantitative understanding of the relationship between planned and provisioned service, and customer satisfaction. In-vehicle...

The San Francisco Travel Quality Study: Tracking Trials and Tribulations of a Transit Taker

Carrel, Andre
Raja Sengupta
Walker, Joan L.
2017

In helping understand the dynamics of travel choice behavior and traveler satisfaction over time, multi-day panel data is invaluable (McFadden in Am Econ Rev 91(3): 351–378, 2001). The collection of such data has become increasingly feasible thanks to smartphones, which researchers can use to present surveys to travelers and to collect additional information through the phones’ location services and other sensors. This paper describes the design and implementation of the San Francisco Travel Quality Study, a multi-day research study conducted in autumn 2013 with 838 participants. The...

The San Francisco Travel Quality Study: tracking trials and tribulations of a transit taker

Carrel, Andre
Raja Sengupta
Joan Walker
2017

In helping understand the dynamics of travel choice behavior and traveler satisfaction over time, multi-day panel data is invaluable (McFadden in Am Econ Rev 91(3): 351–378, 2001). The collection of such data has become increasingly feasible thanks to smartphones, which researchers can use to present surveys to travelers and to collect additional information through the phones’ location services and other sensors. This paper describes the design and implementation of the San Francisco Travel Quality Study, a multi-day research study conducted in autumn 2013 with 838 participants. The...

Research Brief: The Changing Impacts of the COVID-19 Pandemic on Individuals and Households in the U.S.

Bouzaghrane, Mahamed Amine
Obeid, Hassan
Parker, Madeleine
Hayes, Drake
Chen, Minnie
Karen Trapenberg Frick
Daniel Rodriguez
Joan Walker
Raja Sengupta
Daniel Chatman
2021

This brief describes findings from a research effort to understand the changing impacts of the pandemic upon households from different places and backgrounds living in the United States. We investigated the effects of the pandemic along with pandemic-based restrictions and rules on people’s behavior along with their mental and emotional health, social relations, and livelihoods. Unlike other research efforts, as far as we are aware this effort is the only one to join passive data from cell phones with survey information collected from the same individuals over time. We combined these data...

Assessing the Value of Urban Air Mobility through Metropolitan-Scale Microsimulation: A Case Study of the San Francisco Bay Area

Yedavalli, Pavan S.
Onat, Emin
Peng, Xin
Raja Sengupta
Waddell, Paul
Bulusu, Vishwanath
Xue, Min
2021

Urban Air Mobility (UAM) has garnered billions of dollars in investment with early proofs-of-concept and deployments across the world. However, its viability as a transport mode will be strongly determined by benefits in travel time. Hence, before optimizing the planning and infrastructure provision for UAM’s deployment, the dynamics of UAM trips must first be simulated and understood in order to determine the total addressable market. This work contributes to the existing scholarship in several ways. First, we use an ultra-fast parallelized, GPU-based microsimulator, MANTA, to study the...

Structural Damage Detection, Localization, and Quantification Via UAV-Based 3D Imaging

Peng, Xin
Su, Gaofeng
Chen, Zhiqiang
Raja Sengupta
2022

Visual damage inspection for civil structures is a labor-intensive and timeconsuming task. We propose an autonomous UAV-based pipeline for crack and spalling detection, localization, and quantification. Through fusing 3-dimensional (3D) reconstruction and 2D damage detection after performing UAV-based imaging for an engineering structure, the process generates a damage-annotated 3D information model with rich metadata, including the size and type of damage and its location relative to the structure. The pipeline is composed of four steps: image acquisition via UAV, 3D scene reconstruction...