Internet of Things Solution for Motorcycle Riders to Overcome Traffic Jam in Jakarta Using EBkSP

Development of civilization makes people have higher mobility. Traffic jam is a problem that struck land transportation especially in Jakarta, capital city of Indonesia. With slightly increased roads and the number of private vehicles increased each year by 8-10% then the congestion also getting worse. To reach the destination faster, many people prefer to use the motorcycle because in addition to the price is much cheaper than the car, also can pass many narrow streets in Jakarta. They use narrow streets as a shortcut that cannot be passed by car, also avoid congestion on the main road. The problem is that many bikers have not got access to a navigation system that suits their needs, i.e., a navigation system that can show shortcuts that the car cannot pass. In this paper a navigation system for Internet of Things platform to meet the needs of motorcycle riders on the streets of Jakarta is designed. The system utilizes PostgreSQL databases and uses the routing mechanisms entropy-balanced k shortest paths (EBkSP) which is a modification of the existing kSP methods available in the pg Routing. The distances in this navigation system is 5% to 44% better compared against Google Maps for motorcycle riders and EBkSP method for car drivers on specific routes.

[1]  George Suciu,et al.  Vehicular mobile data collection platform to support the development of Intelligent Transportation Systems , 2016, 2016 24th Telecommunications Forum (TELFOR).

[2]  Sven Maerivoet Modelling Traffic on Motorways: State-of-the-Art, Numerical Data Analysis, and Dynamic Traffic Assignment (Modelleren van verkeer op autosnelwegen: State-of-the-Art, numerieke data analyse, en dynamische verkeerstoedeling) , 2006 .

[3]  Peter C. Y. Chen,et al.  LSTM network: a deep learning approach for short-term traffic forecast , 2017 .

[4]  Sanjay E. Sarma,et al.  A Survey of the Connected Vehicle Landscape—Architectures, Enabling Technologies, Applications, and Development Areas , 2017, IEEE Transactions on Intelligent Transportation Systems.

[5]  Veselin Rakocevic,et al.  Distributed road traffic congestion quantification using cooperative VANETs , 2014, 2014 13th Annual Mediterranean Ad Hoc Networking Workshop (MED-HOC-NET).

[6]  Jie Wu,et al.  GUI: GPS-Less Traffic Congestion Avoidance in Urban Areas with Inter-Vehicular Communication , 2014, 2014 IEEE 11th International Conference on Mobile Ad Hoc and Sensor Systems.

[7]  Carlos J. Bernardos,et al.  ABEONA Monitored Traffic: VANET-Assisted Cooperative Traffic Congestion Forecasting , 2014, IEEE Vehicular Technology Magazine.

[8]  Karine Zeitouni,et al.  Proactive Vehicle Re-routing Strategies for Congestion Avoidance , 2012, 2012 IEEE 8th International Conference on Distributed Computing in Sensor Systems.