Title: Impacts of micromobility on car displacement with evidence from a natural experiment and geofencing policy
Abstract
Micromobility, such as electric scooters and electric bikes—an estimated US$300 billion global market by 2030—will accelerate electrification efforts and fundamentally change urban mobility patterns. However, the impacts of micromobility adoption on traffic congestion and sustainability remain unclear. Here we leverage advances in mobile geofencing and high-resolution data to study the effects of a policy intervention, which unexpectedly banned the use of scooters during evening hours with remote shutdown, guaranteeing near perfect compliance. We test theories of habit discontinuity to provide statistical identification for whether micromobility users substitute scooters for cars. Evidence from a natural experiment in a major US city shows increases in travel time of 9–11% for daily commuting and 37% for large events. Given the growing popularity of restrictions on the use of micromobility devices globally, cities should expect to see trade-offs between micromobility restrictions designed to promote public safety and increased emissions associated with heightened congestion.
Evidence from a policy experiment shows that public safety bans on electric scooters and electric bikes can generate unintended traffic congestion in city centres. The studied ban is found to increase travel times by 9–11% for daily evening commutes and by 37% following stadium events.
We consider the problem of multi-robot path planning in a complex, cluttered environment with the aim of reducing overall congestion in the environment, while avoiding any inter-robot communication or coordination. Such limitations may exist due to lack of communication or due to privacy restrictions (for example, autonomous vehicles may not want to share their locations or intents with other vehicles or even to a central server). The key insight that allows us to solve this problem is to stochastically distribute the robots across different routes in the environment by assigning them paths in different topologically distinct classes, so as to lower congestion and the overall travel time for all robots in the environment. We outline the computation of topologically distinct paths in a spatio-temporal configuration space and propose methods for the stochastic assignment of paths to the robots. A fast replanning algorithm and a potential field based controller allow robots to avoid collision with nearby agents while following the assigned path. Our simulation and experiment results show a significant advantage over shortest path following under such a coordination-free setup.
Tian, Disi; Ryan, Andrew D.; Craig, Curtis M.; Sievert, Kelsey; Morris, Nichole L.(
, International Journal of Environmental Research and Public Health)
Electric scooters (or e-scooters) are among the most popular micromobility options that have experienced an enormous expansion in urban transportation systems across the world in recent years. Along with the increased usage of e-scooters, the increasing number of e-scooter-related injuries has also become an emerging global public health concern. However, little is known regarding the risk factors for e-scooter-related crashes and injury crashes. This study consisted of a two-phase survey questionnaire administered to a cohort of e-scooter riders (n = 210), which obtained exposure information on riders’ demographics, riding behaviors (including infrastructure selection), helmet use, and other crash-related factors. The risk ratios of riders’ self-reported involvement in an e-scooter-related crash (i.e., any crash versus no crash) and injury crash (i.e., injury crash versus non-injury crash) were estimated across exposure subcategories using the Negative Binomial regression approach. Males and frequent users of e-scooters were associated with an increased risk of e-scooter-related crashes of any type. For the e-scooter-related injury crashes, more frequently riding on bike lanes (i.e., greater than 25% of the time), either protected or unprotected, was identified as a protective factor. E-scooter-related injury crashes were more likely to occur among females, who reported riding on sidewalks and non-paved surfaces more frequently. The study may help inform public policy regarding e-scooter legislation and prioritize efforts to establish suitable road infrastructure for improved e-scooter riding safety.
Pettet, Geoffrey; Mukhopadhyay, Ayan; Kochenderfer, Mykel J.; Dubey, Abhishek(
, 12th ACM/IEEE International Conference on Cyber-Physical Systems,)
null
(Ed.)
A classical problem in city-scale cyber-physical systems (CPS) is resource allocation under uncertainty. Spatial-temporal allocation of resources is optimized to allocate electric scooters across urban areas, place charging stations for vehicles, and design efficient on-demand transit. Typically, such problems are modeled as Markov (or semi-Markov) decision processes. While online, offline, and decentralized methodologies have been used to tackle such problems, none of the approaches scale well for large-scale decision problems. We create a general approach to hierarchical planning that leverages structure in city-level CPS problems to tackle resource allocation under uncertainty. We use emergency response as a case study and show how a large resource allocation problem can be split into smaller problems. We then create a principled framework for solving the smaller problems and tackling the interaction between them. Finally, we use real-world data from a major metropolitan area in the United States to validate our approach. Our experiments show that the proposed approach outperforms state-of-the-art approaches used in the field of emergency response.
Mulky, Rajath Swaroop; Koganti, Supradeep; Shahi, Sneha; Liu, Kaikai(
, 2018 IEEE International Conference on Cognitive Computing (ICCC))
Despite the technical success of existing assistive technologies, for example, electric wheelchairs and scooters, they are still far from effective enough in helping the blind and elderly navigate to their destinations in a hassle-free manner. Riders often face challenges in driving scooters in some indoor and crowded places, especially on sidewalks with numerous obstacles and other pedestrians. People with certain disabilities, such as the blind, are often unable to drive their scooters well enough. In this paper, we propose to improve the safety and autonomy of the navigation by designing a cutting-edge autonomous scooter, which allows people with mobility challenges to navigate independently and safely in possibly unfamiliar surroundings. We focus on the localization and navigation challenges for the autonomous scooter where the current location, maps, and nearby obstacles are unknown. Solving these challenges will enable the scooter to both travel within buildings and perform tight maneuvers in densely crowds automatically.
Asensio, Omar Isaac, Apablaza, Camila Z., Lawson, M. Cade, Chen, Edward W., and Horner, Savannah J. Impacts of micromobility on car displacement with evidence from a natural experiment and geofencing policy. Nature Energy 7.11 Web. doi:10.1038/s41560-022-01135-1.
Asensio, Omar Isaac, Apablaza, Camila Z., Lawson, M. Cade, Chen, Edward W., & Horner, Savannah J. Impacts of micromobility on car displacement with evidence from a natural experiment and geofencing policy. Nature Energy, 7 (11). https://doi.org/10.1038/s41560-022-01135-1
Asensio, Omar Isaac, Apablaza, Camila Z., Lawson, M. Cade, Chen, Edward W., and Horner, Savannah J.
"Impacts of micromobility on car displacement with evidence from a natural experiment and geofencing policy". Nature Energy 7 (11). Country unknown/Code not available: Nature Publishing Group. https://doi.org/10.1038/s41560-022-01135-1.https://par.nsf.gov/biblio/10377409.
@article{osti_10377409,
place = {Country unknown/Code not available},
title = {Impacts of micromobility on car displacement with evidence from a natural experiment and geofencing policy},
url = {https://par.nsf.gov/biblio/10377409},
DOI = {10.1038/s41560-022-01135-1},
abstractNote = {Abstract Micromobility, such as electric scooters and electric bikes—an estimated US$300 billion global market by 2030—will accelerate electrification efforts and fundamentally change urban mobility patterns. However, the impacts of micromobility adoption on traffic congestion and sustainability remain unclear. Here we leverage advances in mobile geofencing and high-resolution data to study the effects of a policy intervention, which unexpectedly banned the use of scooters during evening hours with remote shutdown, guaranteeing near perfect compliance. We test theories of habit discontinuity to provide statistical identification for whether micromobility users substitute scooters for cars. Evidence from a natural experiment in a major US city shows increases in travel time of 9–11% for daily commuting and 37% for large events. Given the growing popularity of restrictions on the use of micromobility devices globally, cities should expect to see trade-offs between micromobility restrictions designed to promote public safety and increased emissions associated with heightened congestion.},
journal = {Nature Energy},
volume = {7},
number = {11},
publisher = {Nature Publishing Group},
author = {Asensio, Omar Isaac and Apablaza, Camila Z. and Lawson, M. Cade and Chen, Edward W. and Horner, Savannah J.},
}
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