Evidence map›Paper›PMID 30404175›Full record

ArticleSensors (Basel, Switzerland)2018

A System for Generating Customized Pleasant Pedestrian Routes Based on OpenStreetMap Data.

Tessio Novack, Zhiyong Wang, Alexander Zipf

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Review
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Tessio NovackGIScience Research Group, Institute of Geography, Heidelberg University, 69120 Heidelberg, Germany. novack@uni-heidelberg.de.ORCID 0000-0003-2817-5972
Zhiyong WangGIScience Research Group, Institute of Geography, Heidelberg University, 69120 Heidelberg, Germany. zhiyong.wang@uni-heidelberg.de.ORCID 0000-0003-2219-5542
Alexander ZipfGIScience Research Group, Institute of Geography, Heidelberg University, 69120 Heidelberg, Germany. zipf@uni-heidelberg.de.ORCID 0000-0003-4916-9838

Funding

Deutsche Forschungsgemeinschaft 276698709
6 · The paper itself

Abstract

In this work, we present a system that generates customized pedestrian routes entirely based on data from OpenStreetMap (OSM). The system enables users to define to what extent they would like the route to have green areas (e.g., parks, squares, trees), social places (e.g., cafes, restaurants, shops) and quieter streets (i.e., with less road traffic). We present how the greenness, sociability, and quietness factors are defined and extracted from OSM as well as how they are integrated into a routing cost function. We intrinsically evaluate customized routes from one-thousand trips, i.e., origin⁻destination pairs, and observe that these are, in general, as we intended-slightly longer but significantly more social, greener, and quieter than the respective shortest routes. Based on a survey taken by 156 individuals, we also evaluate the system's usefulness, usability, controlability, and transparency. The majority of the survey participants agree that the system is useful and easy to use and that it gives them the feeling of being in control regarding the extraction of routes in accordance with their greenness, sociability, and quietness preferences. The survey also provides valuable insights into users requirements and wishes regarding a tool for interactively generating customized pedestrian routes.

Indexed as

Geographic Information SystemsAccidents, TrafficAdultFemaleHumansMalePedestriansSafetySurveys and QuestionnairesYoung Adulthuman–computer interactionpedestrian routingvolunteered geographic information

Identifiers

PMID30404175
PMCPMC6263876

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.