Abstract
The integration of internet and mobile phones has opened the door to a new wave of utilizing private vehicles as probes not only for performance evaluation but for traffic control as well, gradually replacing the role of traffic surveillance systems as the dominant source of traffic data. To prepare for such a paradigm shift, one needs to overcome some key institutional barriers, in particular, the privacy issue. A Highway Voting System (HVS) is proposed to address this issue in which drivers provide link- and/or path-based vehicle data to the traffic management system in the form of "votes" in order to receive favorable service from traffic control. The proposed HVS offers a platform that links data from individual vehicles directly with traffic control. In the system, traffic control responds to voting vehicles in a way similar to the current system responding to prioritized vehicles and providing the requested services accordingly. We show in the paper that the proposed "voting" system can effectively resolve the privacy issue which often hampers traffic engineers from getting detailed data from drivers. Strategies to entice drivers into "voting" so as to increase the market penetration level under all traffic conditions are discussed. Though the focus of the paper is on addressing the institutional issues associated with data acquisition from individual vehicles, other research topics associated with the proposed system are identified. Two examples are given to demonstrate the impact of the proposed system on algorithm development and traffic control.
Original language | English (US) |
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Pages (from-to) | 149-160 |
Number of pages | 12 |
Journal | Transportation Research Part C: Emerging Technologies |
Volume | 56 |
DOIs | |
State | Published - Jul 1 2015 |
Keywords
- Algorithm development
- Data collection
- Equitability
- Privacy issues
- Sustainability
- System optimum
- Traffic control
ASJC Scopus subject areas
- Transportation
- Automotive Engineering
- Civil and Structural Engineering
- Management Science and Operations Research