Abstract
Accurate and reliable real-time urban traffic management can benefit urban citizens’ daily life by reducing stress, travel time and carbon footprint. The provision of reliable and accurate traffic information has however proven to be a major challenge in intelligent transportation systems. Citizens carrying smartphones can be exploited as an important provider of traffic information and the mobile crowd sensing paradigm can be used as a solution to this challenge. In this paper, an urban traffic monitoring system which exploits the power of participatory sensing and cloud messaging is proposed. Crowd intelligence that is used to estimate traffic congestion levels, arrival times, and average road speed is harvested from crowd sensed data. Traffic congestion control at route level is implemented with a route guidance system. Proactive warnings or recommendations to drivers in the vicinity of or on the route to reported events are provided. The drivers can also report short-term traffic events and physical road conditions for road monitoring. Real-world experiments are conducted with a prototype implementation and the results demonstrates both system feasibility and traffic estimation accuracy.
Highlights
T RAFFIC congestion is a major challenge for our society
Real-world experiments were conducted with a prototype implementation of the system and the results demonstrate system feasibility delivering accurate traffic estimation
The results demonstrate the feasibility of this system which achieves accurate traffic estimation and journey time
Summary
T RAFFIC congestion is a major challenge for our society. The sustainable growth of our cities is hampered by waste of energy, pollution and delays caused by traffic congestion in modern transportation systems [1], [2]. ITS aims at improving mobility, safety, efficiency, air quality, and decreasing energy consumption by providing real-time traffic information to drivers and traffic authorities [5]. Mobile crowd sensing can be effectively used for the continuous measurement and monitoring of road and traffic conditions acquired from sensor equipped smart phones of the volunteered participants [14], [18], [19]. Crowd intelligence is utilized within TRMS and the values for traffic congestion levels, arrival times, average speed on a given road segment are estimated by using the crowd-sensed data. The users of TRMS can report physical road conditions such as potholes, bumps or slippery or damaged road surface, and short-lived traffic events such as traffic accident, meeting, festival, celebration or protests This would enable authorities to monitor traffic congestion and road conditions.
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