We contribute to the literature on new mobilities by measuring spatial disparities in travel times for accessing essential non-work destinations via ridehailing.
Sicheng Wang
Understanding preferences for bicycling and bicycle infrastructure
Using survey data collected in New Jersey, we analyze the frequency of bicycling and respondent perceptions of the safety of various bicycling facilities.
Staying at Home Is a Privilege: Evidence from Fine-Grained Mobile Phone Location Data in the United States during the COVID-19 Pandemic
The coronavirus disease 2019 (COVID-19) has exposed and, to some degree, exacerbated social inequity in the United States.
Research: Variation in ride-hailing trips in Chengdu, China
A new paper looks at the elasticities of demand for ride-hailing service provider DiDi in Chengdu, China.
Recent Publications
Understanding How Marginalized Genders Travel Using NJ TRANSIT
Through this research, NJ TRANSIT sought to understand how women and members of the lesbian, gay, bisexual, transgender, queer plus community, sometimes referred to as sexual and gender minorities (SGMs) travel on NJ TRANSIT so the agency can provide better...
Assessing Pedestrian Stress with Biometric Sensing and Survey Responses
Recent advances in biometric sensing technologies, such as eye tracking, heart rate trackers, and galvanic skin response (GSR) sensors, offer new opportunities to measure pedestrian stress level and their travel experiences in real-time. Uncertainty remains about...
GPS-Based Street-View Greenspace Exposure and Wearable Assessed Physical Activity in a Prospective Cohort of US Women
Background Increasing evidence positively links greenspace and physical activity (PA). However, most studies use measures of greenspace, such as satellite-based vegetation indices around the residence, which fail to capture ground-level views and day-to-day dynamic...
Measuring Induced Travel Elasticities associated with Local Roads from Trip Generation
Induced travel elasticities associated with new road capacity are typically estimated for roads of higher functional classifications, such as interstate freeways and principal arterials. These are estimated as “own” elasticities, that is an increase in lane kilometers...