Public transport trip purpose inference using smart card fare data

Alsger, Azalden; Tavassoli, Ahmad; Mesbah, Mahmoud; Ferreira, Luis; Hickman, Mark

doi:10.1016/j.trc.2017.12.016

Cited by 116 publications

(66 citation statements)

References 17 publications

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“…One of the responsibilities of the government is to collect data in order to model, manage and improve transportation networks. Information on tolls, smartcards, traffic detectors, surveys, parking and properties can be use to find new ways of shaping our mobility [46,2].…”

Section: Identification Layermentioning

confidence: 99%

A multi-layered blockchain framework for smart mobility data-markets

López

Farooq

2020

Transportation Research Part C: Emerging Technologies

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Blockchain has the potential to render the transaction of information more secure and transparent. Nowadays, transportation data are shared across multiple entities using heterogeneous mediums, from paper collected data to smartphone. Most of this data are stored in central servers that are susceptible to hacks. In some cases shady actors who may have access to such sources, share the mobility data with unwanted third parties. A multi-layered Blockchain framework for Smart Mobility Data-market (BSMD) is presented for addressing the associated privacy, security, management, and scalability challenges. Each participant shares their encrypted data to the blockchain network and can transact information with other participants as long as both parties agree to the transaction rules issued by the owner of the data. Data ownership, transparency, auditability and access control are the core principles of the proposed blockchain for smart mobility data-market. In a case study of real-time mobility data sharing, we demonstrate the performance of BSMD on a 370 nodes blockchain running on heterogeneous and geographically-separated devices communicating on a physical network. We also demonstrate how BSMD ensures the cybersecurity and privacy of individual by safeguarding against spoofing and message interception attacks and providing information access management control. Service 1 that "...(Waze will) share personal information with companies or organizations connected or affiliated with Waze...". So all the information collected by Waze could be shared with other organizations associated with Waze. However, the Terms of Service do not make it clear if the user can track with whom their information has been shared.Another point related to privacy is the access control of the information that is provided by the users. It was recently discovered that Google keeps collecting user location data even if they explicitly deactivate the tracking system in their mobiles [26]. Another example of disclosing information without the user's consent is the infamous Facebook-Cambridge Analytica scandal [9].The General Data Protection Regulation 2 (GDPR) is a step forward for privacy. Although the GDPR is valid only in the European Union, it is still expected to push multinational companies to be more transparent on how they manage people's private information. In the authors opinion, no matter how many rules and fines governments apply, given the current centralized ways of collecting people's data, some entities will always find a loophole in legislation or hackers will be able to tamper with these centralized data systems. In addition to laws, individuals have to have total control and ownership of their information. We need to be the guardians and responsible of our own privacy, unfortunately nowadays we have to trust third parties for that.Distributed ledger technologies like blockchain have the potential to give the people full control of their information, protect individual's personal mobility information and guard their privacy. The ...

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Section: Identification Layermentioning

confidence: 99%

A multi-layered blockchain framework for smart mobility data-markets

López

Farooq

2020

Transportation Research Part C: Emerging Technologies

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“…Supplementary information such as land use data and household survey data are also used for inferring land use, activity, and trip purpose [11,12,22]. For example, Long et al [22] combine smart card data with household travel surveys, as well as a parcel-level land use map to identify job-housing locations and commuting trip routes in Beijing.…”

Section: Inference Based On Individual Travel Patterns and Additionalmentioning

confidence: 99%

“…Previous studies have estimated trip purposes, land uses, and activities using individual travel patterns [9,10] and other secondary information such as household survey data and POI (point of interest) in the area [11,12]. However, these datasets also tend to be unavailable or inaccurate.…”

mentioning

confidence: 99%

Detecting and understanding urban changes through decomposing the numbers of visitors’ arrivals using human mobility data

et al. 2019

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“…Information on tolls, Smart-Card, traffic detectors, surveys, parking and property can be use to find new ways for shaping our mobility. For example, toll information and traffic detectors can be used to optimize operators objective trough dynamic toll rates Toledo et al [2017] and Smart-Card fare data can be used to indirectly infer trip purpose Alsger et al [2018].…”

Section: Data Sourcesmentioning

confidence: 99%

A blockchain framework for smart mobility

López

Farooq

2018

2018 IEEE International Smart Cities Conference (ISC2)

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A blockchain framework is presented for addressing the privacy and security challenges associated with the Big Data in smart mobility. It is composed of individuals, companies, government and universities where all the participants collect, own, and control their data. Each participant shares their encrypted data to the blockchain network and can make information transactions with other participants as long as both party agrees to the transaction rules (smart contract) issued by the owner of the data. Data ownership, transparency, auditability and access control are the core principles of the proposed blockchain for smart mobility Big Data. Figure 2: Smart contract and transactionOnce a node accepts a connection it selects the information it is willing to share. As long as the connection is present in the smart contract the receiver has access to the information. When a node requests information from another node the following steps are met:

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Public transport trip purpose inference using smart card fare data

Cited by 116 publications

References 17 publications

A multi-layered blockchain framework for smart mobility data-markets

A multi-layered blockchain framework for smart mobility data-markets

Detecting and understanding urban changes through decomposing the numbers of visitors’ arrivals using human mobility data

A blockchain framework for smart mobility

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