Designing IDA - An Intelligent Driver Assistant for Smart City Parking in Singapore

Niculescu, Andreea I.; Lim, Mei Quin; Wibowo, Seno A.; Yeo, Kheng Hui; Lim, Boon Pang; Popow, Michael; Chia, Wei Ming Dan; Banchs, Rafael E.

doi:10.1007/978-3-319-22723-8_50

Cited by 9 publications

(6 citation statements)

References 1 publication

(1 reference statement)

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“…For some countries, such as Singapore, using mobile phones or tablets is strictly prohibited while driving. Niculescu et al [120] proposed an intelligent driver assistant to help drivers find quickly suitable parking in Singapore. The driver assistant uses speech to interact with drivers and becomes an active help during navigation by checking periodically the chosen car park availability.…”

Section: Parking System Deploymentmentioning

confidence: 99%

A Survey of Smart Parking Solutions

Lin

Rivano

Mouël

2017

IEEE Trans. Intell. Transport. Syst.

421

185

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Section: Parking System Deploymentmentioning

confidence: 99%

A Survey of Smart Parking Solutions

Lin

Rivano

Mouël

2017

IEEE Trans. Intell. Transport. Syst.

421

185

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“…IDA: 36 An Intelligent Driver Assistant System (IDA) provides parking services that interact with the driver through natural language dialogs presented by the researchers of the STAR Institute for Infocomm Research Singapore. Once the driver decides to park the vehicle the IDA starts observing available parking slots continuously once in a minute and if the number of slots reaches a critical level, the IDA suggests the driver to an alternate parking space.…”

Section: Prominent Smart Parking Systemsmentioning

confidence: 99%

A survey on smart parking systems in urban cities

Zulfiqar

Haque

Tariq

et al. 2021

Concurrency and Computation

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Summary Parking vehicles in densely populated areas are often challenging, stressful, and sometimes it becomes a monotonous job for the drivers in jam‐packed areas. There are several reasons for the delay in finding parking spaces such as scarcity of parking slots, disordered or unmanaged parking of vehicles, lacking or unaware of parking information at the destination, which further leads to the wastage of time, fuel, energy and increase in environmental pollution. Literature has revealed a significant number of smart parking solutions based on the Internet of Things (IoT) and context‐awareness with the incorporation of routing strategies and vehicle detection techniques in a pervasive computing environment. With the rapid escalation of the smart and intelligent devices along with their applicability in a highly decentralized environment, real‐time traffic monitoring, and finding parking spaces have become quite trivial. Smart parking sensors and technologies assist drivers in finding vacant parking slots while they are on the way to their destination. Considering the needs, wants, and demands of metropolitan cities, in this article, we have reviewed the recently published articles, mostly from the last 5 years, on smart parking systems augmented with sensors, embedded systems, context‐awareness capability, and IoT which yields in saving time, fuel, energy, and reduces the stress of the drivers. To accomplish this, we have reviewed different models on smart parking solutions based on algorithmic formalisms, theoretical frameworks, formal models, smart device‐based prototypes as well as real‐time applications, and verifying the correctness properties of the system. The results shown may provide a base for the state of the art future research directions.

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“…A smart city application that faces all these challenges can be studied in Singapore, where it tries to alleviate the problem of parking space searching. In this article we describe the app's functionality and in parti cular its capabilities to predict the availability of parking spaces at the destination even before the trip starts [3]. Furthermore, the application assists in navigation, updates its prediction on the go, and recommends alternative car parks in the vicinity of the destination.…”

Section: Initial Situationmentioning

confidence: 99%