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Intersense: An XGBoost Model for Traffic Regulator Identification at Intersections Through Crowdsourced GPS Data

Vlachogiannis, Dimitris
Scott Moura
Jane Macfarlane
2023

Digital maps of the transportation network are the foundation of future mobility solutions. Autonomous and connected vehicles rely on real-time, at-scale updating of the environment in which they operate. Successful operation in a hybrid environment, where human and machine intelligence coexist, requires explicit knowledge of the traffic regulator infrastructure. Future generation traffic management strategies and path planning systems must be tightly integrated with the regulator infrastructure in order to improve traffic dynamics and reduce congestion in urban environments. In this...

HumanLight: Incentivizing Ridesharing via Human-Centric Deep Reinforcement Learning in Traffic Signal Control

Vlachogiannis, Dimitris
Wei, Hua
Scott Moura
Jane Macfarlane
2024

Single occupancy vehicles are the most attractive transportation alternative for many commuters, leading to increased traffic congestion and air pollution. Advancements in information technologies create opportunities for smart solutions that incentivize ridesharing and mode shift to higher occupancy vehicles (HOVs) to achieve the car lighter vision of cities. In this study, we present HumanLight, a novel decentralized adaptive traffic signal control algorithm designed to optimize people throughput at intersections. Our proposed controller is founded on reinforcement learning with the...

Light Rail System Safety Improvements Using ITS Technologies

Chira-chavala, Ted
Coifman, Ben
Empey, Dan
Mark Hansen
Lechner, Ed
Porter, Chris
1997

This report describes research which studied identifying and analyzing the effectiveness of countermeasures designed to reduce light rail crashes. Focus is in collisions with road vehicles at intersections. The light rail system for the Santa Clara County Transportation Agency in California served as the focus of the study.

Planning for Electric Vehicles Coupled with Urban Mobility

Xu, Yanyan
Çolak, Serdar
Kara, Emre C.
Scott Moura
Marta Gonzalez
2018

The rising adoption of plug-in electric vehicles (PEVs) leads to the alignment of their electricity and their mobility demands. Therefore, transportation and power infrastructures are becoming increasingly interdependent. In this work, we uncover patterns of PEV mobility by integrating for the first time two unique data sets: (i) mobile phone activity of 1.39 million Bay Area residents and (ii) charging activity of PEVs in 580,000 sessions obtained in the same region. We present a method to estimate individual mobility of PEV drivers at fine temporal and spatial resolution integrating...

Planning for Electric Vehicle Needs by Coupling Charging Profiles with Urban Mobility

Xu, Yanyan
Çolak, Serdar
Kara, Emre C.
Scott Moura
Marta Gonzalez
2018

The rising adoption of plug-in electric vehicles (PEVs) leads to the temporal alignment of their electricity and mobility demands. However, mobility demand has not yet been considered in electricity planning and management. Here, we present a method to estimate individual mobility of PEV drivers at fine temporal and spatial resolution, by integrating three unique datasets of mobile phone activity of 1.39 million Bay Area residents, census data and the PEV drivers survey data. Through coupling the uncovered patterns of PEV mobility with the charging activity of PEVs in 580,000 session...

EEZ Mobility: A Tool for Modeling Equitable Installation of Electric Vehicle Charging Stations

Clark, Callie
Ozturk, Ayse Tugba
Hong, Preston
Marta Gonzalez
Scott Moura
2022

Public electric vehicle (EV) chargers are unevenly distributed in California with respect to income, race and education-levels. This creates inequitable access to electric mobility especially for low-income communities of color, which. are less likely to have access to home charging stations. These vulnerable communities are also more likely to be located in areas with poor air quality and would therefore benefit from EV adoption. Currently programs exist in California that fund incentives for public EV chargers in “Disadvantaged Communities” but the process for identifying these...

Trajectory-Integrated Accessibility Analysis of Public Electric Vehicle Charging Stations

Ju, Yi
Wu, Jiaman
Su, Zhihan
Li, Lunlong
Zhao, Jinhua
Marta Gonzalez
Scott Moura
2025

Electric vehicle (EV) charging infrastructure is crucial for advancing EV adoption, managing charging loads, and ensuring equitable transportation electrification. However, there remains a notable gap in comprehensive accessibility metrics that integrate the mobility of the users. This study introduces a novel accessibility metric, termed Trajectory-Integrated Public EVCS Accessibility (TI-acs), and uses it to assess public electric vehicle charging station (EVCS) accessibility for approximately 6 million residents in the San Francisco Bay Area based on detailed individual trajectory data...

Study of Freeway Traffic Near an Off-Ramp

Michael Cassidy
Anani, Shadi B.
Haigwood, John M.
2000

A bottleneck with a diminished capacity is shown to have arisen on a freeway segment whenever queues from the segment's off-ramped spilled over and occupied its mandatory exit lane. It is also shown that longer exit queues from the over-saturate off-ramp were accompanied by lower discharge rates for non-exiting vehicles. The explanation appears to be rubber-necking on the part of the non-exiting drivers. Whenever the of-ramp queues were prevented from spilling over to the exit lane (by changing the logic of a nearby traffic signal), much higher flows were sustained on the freeway segment...

Automated Travel Time Measurement Using Vehicle Lengths from Loop Detector Speed Traps

Coifman, Benjamin
Michael Cassidy
2000

This report presents a vehicle reidentification algorithm for consecutive detector stations on a freeway, whereby a vehicle measurement made at a downstream detector station is matched with the vehicle's corresponding measurement at an upstream station. The algorithm should improve freeway surveillance by measuring the actual vehicle travel times; these are simply the differences in the times that each (matched) vehicle arrives to the upstream and downstream stations. Thus, it will be possible to quantify conditions between widely spaced detector stations rather than assuming that the...

Mobile Century Final Reportfor TO 1021 and TO 1029: A Traffic Sensing Field Experiment Using GPS Mobile Phones

Alexandre Bayen
2010

Traffic monitoring is most commonly accomplished with government-deployed, dedicated equipment. Adopting new technology in this paradigm can be costly and slow. However, recent advances in the mobile internet, cell phone technology, and location-based services may be leveraged to transcend the old paradigm. Doing so will reduce costs, increase coverage and yield a wealth of new data that will empower the traveling public with real-time access to current traffic conditions. Furthermore, transportation operators will gain access to an unprecedented wealth of information to help them better...