2021
DOI: 10.1016/j.trd.2021.103037
|View full text |Cite
|
Sign up to set email alerts
|

Planning for e-scooter use in metropolitan cities: A case study for Paris

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
1
1

Citation Types

0
25
0
2

Year Published

2021
2021
2024
2024

Publication Types

Select...
6
3

Relationship

0
9

Authors

Journals

citations
Cited by 53 publications
(27 citation statements)
references
References 21 publications
0
25
0
2
Order By: Relevance
“…In addition, many issues related to electric scooter systems have been presented superficially, without an in-depth analysis of the problem. This superficiality is often associated with the lack of available data for analyses or the use of small datasets (for example, data on the safety of scooter users are most often analyzed based on data obtained from hospitals, as many road accident recording systems do not include electric scooters; therefore, these events are often not registered in databases [7][8][9]).…”
Section: Scientific Literature Reviewmentioning
confidence: 99%
“…In addition, many issues related to electric scooter systems have been presented superficially, without an in-depth analysis of the problem. This superficiality is often associated with the lack of available data for analyses or the use of small datasets (for example, data on the safety of scooter users are most often analyzed based on data obtained from hospitals, as many road accident recording systems do not include electric scooters; therefore, these events are often not registered in databases [7][8][9]).…”
Section: Scientific Literature Reviewmentioning
confidence: 99%
“…Specifically for the topic of spatiotemporal usage patterns, which supports the opinions of users, transport planners, and policy stakeholders, data collection and analysis methods are still based on surveys rather than the suggested method of leveraging real-time vehicle big data. This type of R&D improvement will provide a plethora of data that will aid in understanding how people travel in cities [100].…”
Section: Big Data and Mobility As A Service (Maas)mentioning
confidence: 99%
“…To reduce the risk of becoming infected on public transport, people started to replace public transport with micromobility transport modes, and even the proportion of medium- and long-distance travels by micromobility services increases during the lockdown period [ 3 ]. In fact, some studies concluded that there are also indications that micromobility patterns have changed after the pandemic, from complementary modes to full trip solutions [ 4 ]. In some cities, since the lockdown, the use of e-scooters has gained significant importance, and has become a strategic means of travel [ 5 ].…”
Section: Introductionmentioning
confidence: 99%
“…However, data availability for e-scooter crashes is very limited. In fact, crashes involving e-scooters do not have dedicated labelling in crash reports for the majority of city agencies [ 4 ]. Therefore, most research is based on hospital records and visits to emergency departments [ 6 , 7 , 8 , 9 , 10 ].…”
Section: Introductionmentioning
confidence: 99%