A Safety Index for Smart Mobility using Real-Time Crowdsourced Data
| Autor: | Edgar J. Escobedo, Ruey Long Cheu, Victor M. Larios, Oscar Mondragon, Natalia Villanueva-Rosales, Jonatan M. Contreras, Neale A. Smith, Adriana C. Camacho |
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| Rok vydání: | 2020 |
| Předmět: |
050210 logistics & transportation
Computer science 05 social sciences 0211 other engineering and technologies 021107 urban & regional planning Crash 02 engineering and technology Safety index Transport engineering Work (electrical) Information and Communications Technology Component (UML) 0502 economics and business Mobile technology Metric (unit) Dijkstra's algorithm |
| Zdroj: | ISC2 |
| Popis: | Smart Mobility is an important component of Smart Cities with most of the current approaches focusing on crash incidents for safety within Smart Mobility. The Safe Community System (SCS) aims to collect and provide information to city residents about events beyond crash incidents using mobile technology. The work reported in this manuscript aims to manage and provide information to residents in a meaningful way to support their decision making. This paper describes our efforts in extending an initial proof-of-concept of the SCS by establishing a Safety Index (SI)-a derived metric that aggregates the value of resident-submitted reports to generate real-time safety levels for streets within a city considering the lifespan and verification of these reports. The SCS mobile application has been refined to provide further information about a specific incident. The SCS updated design also proposes a Safe Path Algorithm (SPA) which is a modified Dijkstra’s algorithm that uses the SI to compute a safe path for the resident. The goal of the SCS is to support resident’s decision-making when choosing a route and thus fostering safety for Smart Mobility. Efforts like the SCS contribute to converting cities to Smart Cities. |
| Databáze: | OpenAIRE |
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