SISTEM GANJIL GENAP PADA PINTU TOL TAMBUN TERHADAP KEMACETAN LALU LINTAS DI TOL JAKARTA-CIKAMPEK

Kemacetan tol Jakarta-Cikampek semakin parah karena banyaknya proyek pembangunan di sekitar jalan tol Jakarta-Cikampek. Untuk menekan angka kemacetan lalu lintas di jalan tol Jakarta-Cikampek Menteri Perhubungan Republik Indonesia mengeluarkan kebijakan dengan membuat Peraturan Menteri Nomor PM 18 Tahun 2018 Tentang Pengaturan Lalu Lintas Selama Masa Pembangunan Proyek Infrastruktur Strategis Nasional Di Ruas Jalan Tol Jakarta Cikampek. Pemberlakuan sistem ganjil genap pelat kendaraan di Gerbang Tol Tambun mulai diberlakukan pada tanggal 03 Desember 2018 bagi kendaraan dari arah Bekasi menuju Jakarta. Penelitian ini dilakukan untuk mengetahui seberapa besar efektifitas dari penerapan sistem ganjil genap pada Gerbang Tol Tambun terhadap penurunan jumlah volume lalu lintas dan kenaikan kecepatan kendaraan di tol Jakarta-Cikampek. Penelitian dilakukan selama 5 hari kerja yaitu hari Senin-Jum’at jam 06.00-09.00 WIB. Metode yang digunakan untuk menghitung jumlah volume lalu lintas yaitu dengan cara survei langsung di lapangan. Sedangkan untuk mengetahui kecepatan kendaraan pada ruas tol Cibitung-Bekasi Timur dilakukan dengan metode survei individu (individual speed). Hasil penelitian menunjukkan penerapan sistem ganjil genap pelat kendaraan pada Gerbang Tol Tambun dapat mengurangi volume kendaraan sebesar 43,09%. Hasil penelitian dengan metode survei individual speed menunjukkan kenaikan kecepatan kendaraan pada ruas tol Cibitung-Bekasi Timur sebesar 7,62%

Predicting motorway traffic performance by data fusion of local sensor data and electronic toll collection data

Heilmann B, El Faouzi N-E, Mouzon de O, et al. Predicting motorway traffic performance by data fusion of local sensor data and electronic toll collection data. Computer-Aided Civil and Infrastructure Engineering. 2011;26(6):451-463

Real-time Traffic Flow Detection and Prediction Algorithm: Data-Driven Analyses on Spatio-Temporal Traffic Dynamics

Traffic flows over time and space. This spatio-temporal dependency of traffic flow should be considered and used to enhance the performance of real-time traffic detection and prediction capabilities. This characteristic has been widely studied and various applications have been developed and enhanced. During the last decade, great attention has been paid to the increases in the number of traffic data sources, the amount of data, and the data-driven analysis methods. There is still room to improve the traffic detection and prediction capabilities through studies on the emerging resources. To this end, this dissertation presents a series of studies on real-time traffic operation for highway facilities focusing on detection and prediction.First, a spatio-temporal traffic data imputation approach was studied to exploit multi-source data. Different types of kriging methods were evaluated to utilize the spatio-temporal characteristic of traffic data with respect to two factors, including missing patterns and use of secondary data. Second, a short-term traffic speed prediction algorithm was proposed that provides accurate prediction results and is scalable for a large road network analysis in real time. The proposed algorithm consists of a data dimension reduction module and a nonparametric multivariate time-series analysis module. Third, a real-time traffic queue detection algorithm was developed based on traffic fundamentals combined with a statistical pattern recognition procedure. This algorithm was designed to detect dynamic queueing conditions in a spatio-temporal domain rather than detect a queue and congestion directly from traffic flow variables. The algorithm was evaluated by using various real congested traffic flow data. Lastly, gray areas in a decision-making process based on quantifiable measures were addressed to cope with uncertainties in modeling outputs. For intersection control type selection, the gray areas were identified and visualized