scholarly journals Android Application of Traffic Density Visualization Based on Vehicle Speed

2017 ◽  
Vol 1 (1) ◽  
pp. 7
Author(s):  
Widyadi Setiawan ◽  
I Nyoman Budiastra ◽  
Sri Andriati Asri
Keyword(s):  
Real Time ◽  
Data Retrieval ◽  
Traffic Density ◽  
Vehicle Speed ◽  
Android Application ◽  
Computational Process ◽  
Time Data ◽  
Speed Measurement ◽  
Frame Difference ◽  
The City

This paper presents a system to display traffic density in real time based on speed of vehicles on the main roads in the city of Denpasar. With this application, users who are in a vehicle can get the density of roads information. The software will run on the Android platform created with the help of Google maps with visualization density of roads are being reviewed. Measurement of vehicle speed using the frame difference method, so the computational process can be run quickly and in real time. The trial results of this paper, user (vehicle speed measurement) produces the same data as the data is received by the client (viewer visualization) with the display format is the name of the location, vehicle speed, date and time data retrieval.

scholarly journals Android Application of Traffic Density Visualization Based on Vehicle Speed

2017 ◽  
Vol 1 (1) ◽  
pp. 7
Author(s):  
Widyadi Setiawan ◽  
I Nyoman Budiastra ◽  
Sri Andriati Asri
Keyword(s):  
Real Time ◽  
Data Retrieval ◽  
Traffic Density ◽  
Vehicle Speed ◽  
Android Application ◽  
Computational Process ◽  
Time Data ◽  
Speed Measurement ◽  
Frame Difference ◽  
The City

This paper presents a system to display traffic density in real time based on speed of vehicles on the main roads in the city of Denpasar. With this application, users who are in a vehicle can get the density of roads information. The software will run on the Android platform created with the help of Google maps with visualization density of roads are being reviewed. Measurement of vehicle speed using the frame difference method, so the computational process can be run quickly and in real time. The trial results of this paper, user (vehicle speed measurement) produces the same data as the data is received by the client (viewer visualization) with the display format is the name of the location, vehicle speed, date and time data retrieval.

scholarly journals Android Application of Traffic Density Visualization Based on Vehicle Speed

2017 ◽  
Vol 1 (1) ◽  
pp. 7
Author(s):  
Widyadi Setiawan ◽  
I Nyoman Budiastra ◽  
Sri Andriati Asri
Keyword(s):  
Real Time ◽  
Data Retrieval ◽  
Traffic Density ◽  
Vehicle Speed ◽  
Android Application ◽  
Computational Process ◽  
Time Data ◽  
Speed Measurement ◽  
Frame Difference ◽  
The City

This paper presents a system to display traffic density in real time based on speed of vehicles on the main roads in the city of Denpasar. With this application, users who are in a vehicle can get the density of roads information. The software will run on the Android platform created with the help of Google maps with visualization density of roads are being reviewed. Measurement of vehicle speed using the frame difference method, so the computational process can be run quickly and in real time. The trial results of this paper, user (vehicle speed measurement) produces the same data as the data is received by the client (viewer visualization) with the display format is the name of the location, vehicle speed, date and time data retrieval.

scholarly journals Sistem Pengamatan Kondisi Lalu Lintas Berbasis Data GPS pada Smartphone (Studi Kasus : Kota Denpasar)

2020 ◽  
Vol 7 (4) ◽  
pp. 667
Author(s):  
Gede Herdian Setiawan ◽  
I Ketut Dedy Suryawan
Keyword(s):  
Real Time ◽  
Traffic Congestion ◽  
Data Retrieval ◽  
Traffic Information ◽  
Vehicle Speed ◽  
Observation Model ◽  
Economic Activities ◽  
Traffic Condition ◽  
Traffic Conditions ◽  
Real Time Traffic

<p>Pertumbuhan jumlah kendaraan yang semakin meningkat setiap tahunnya mengakibatkan volume kendaraan yang melintasi ruas jalan semakin padat yang kerap mengakibatkan kemacetan lalu lintas. Kemacetan lalu lintas dapat menjadi beban biaya yang signifikan terhadap kegiatan ekonomi masyarakat. Informasi lalu lintas yang dinamis seperti informasi kondisi lalu lintas secara langsung <em>(real time)</em> akan membantu mempengaruhi aktivitas masyarakat pengguna lalu lintas untuk melakukan perencanaan dan penjadwalan aktivitas yang lebih baik. Penelitian ini mengusulkan model pengamatan kondisi lalu lintas berbasis data GPS pada <em>smartphone</em>, untuk informasi kondisi lalu lintas secara langsung. GPS <em>Receiver</em> pada <em>smartphone</em> menghasilkan data lokasi secara instan dan bersifat mobile sehingga dapat digunakan untuk pengambilan data kecepatan kendaraan secara langsung. Kecepatan kendaraan diperoleh berdasarkan jarak perpindahan koordinat kendaraan dalam satuan detik selanjutnya di konversi menjadi satuan kecepatan (km/jam) kemudian data kecepatan kendaraan di proses menjadi informasi kondisi lalu lintas. Secara menyeluruh model pengamatan berfokus pada tiga tahapan, yaitu akuisisi data kecepatan kendaraan berbasis GPS pada <em>smartphone</em>, pengiriman data kecepatan dan visualisasi kondisi lalu lintas berbasis GIS. Pengujian dilakukan pada ruas jalan kota Denpasar telah mampu mendapatkan data kecepatan kendaraan dan mampu menunjukkan kondisi lalu lintas secara langsung dengan empat kategori keadaan lalu lintas yaitu garis berwarna hitam menunjukkan lalu lintas macet dengan kecepatan kendaraan kurang dari 17 km/jam, merah menunjukkan padat dengan kecepatan kendaraan 17 km/jam sampai 27 km/jam, kuning menunjukkan sedang dengan kecepatan kendaraan 26 km/jam sampai 40 km/jam dan hijau menunjukkan lancar dengan kecepatan kendaraan diatas 40 km/jam.</p><p> </p><p><em><strong>Abstract</strong></em></p><p class="Abstract"><em>The growth in the number of vehicles that is increasing every year has resulted in the volume of vehicles crossing the road increasingly congested which often results in traffic congestion. Traffic congestion can be a significant cost burden on economic activities. Dynamic traffic information such as information on real time traffic conditions will help influence the activities of the traffic user community to better plan and schedule activities. This study proposes a traffic condition observation model based on GPS data on smartphones, for information on real time traffic conditions. The GPS Receiver on the smartphone produces location and coordinate data instantly and is mobile so that it can be used for direct vehicle speed data retrieval. Vehicle speed is obtained based on the displacement distance of the vehicle's coordinates in units of seconds and then converted into units of speed (km / h), the vehicle speed data is then processed into information on traffic conditions. Overall, the observation model focuses on three stages, namely GPS-based vehicle speed data acquisition on smartphones, speed data delivery and visualization of GIS-based traffic conditions. Tests carried out on the Denpasar city road segment have been able to obtain vehicle speed data and are able to show traffic conditions directly with four categories of traffic conditions, namely black lines indicating traffic jammed with vehicle speeds of less than 17 km / h, red indicates heavy with speed vehicles 17 to 27 km / h, yellow indicates medium speed with vehicles 26 km/h to 40 km / h and green shows fluent with vehicle speeds above 40 km / h.</em></p><p><em><strong><br /></strong></em></p>

scholarly journals Study on Fractal Multistep Forecast for the Prediction of Driving Behavior

2020 ◽  
Vol 2020 ◽  
pp. 1-10
Author(s):  
Longhai Yang ◽  
Hong Xu ◽  
Xiqiao Zhang ◽  
Shuai Li ◽  
Wenchao Ji
Keyword(s):  
Prediction Model ◽  
Real Time ◽  
Time Series Data ◽  
Back Propagation ◽  
Series Data ◽  
Vehicle Speed ◽  
Trajectory Data ◽  
Time Data ◽  
Characteristic Analysis ◽  
Real Time Data

The application and development of new technology make it possible to acquire real-time data of vehicles. Based on these real-time data, the behavior of vehicles can be analyzed. The prediction of vehicle behavior provides data support for the fine management of traffic. This paper proposes speed and acceleration have fractal features by R/S analysis of the time series data of speed and acceleration. Based on the characteristic analysis of microscopic parameters, the characteristic indexes of parameters are quantified, the fractal multistep prediction model of microparameters is established, and the BP (back propagation neural networks) model is established to estimate predictable step of fractal prediction model. The fractal multistep prediction model is used to predict speed acceleration in the predictable step. NGSIM trajectory data are used to test the multistep prediction model. The results show that the proposed fractal multistep prediction model can effectively realize the multistep prediction of vehicle speed.

Real-Time Bus-Holding Control Strategy to Reduce Passenger Waiting Time

2017 ◽  
Vol 2647 (1) ◽  
pp. 9-16 ◽  
Author(s):  
Mohamadamin Asgharzadeh ◽  
Yousef Shafahi
Keyword(s):  
Real Time ◽  
Waiting Time ◽  
Control Strategy ◽  
Gradient Descent ◽  
Waiting Times ◽  
Heuristic Method ◽  
Bus Rapid Transit ◽  
Time Data ◽  
Using Data ◽  
The City

This paper presents research on a real-time bus-holding control strategy that minimizes passenger waiting time. This bus-holding strategy forces buses to hold at stations for a while after a passenger exchange is finished. A mathematical model is proposed to determine the optimal holding time. Both onboard and on-station passenger waiting times have been taken into account. Given the real-time nature of the problem, a heuristic method based on gradient descent algorithms was developed. The proposed control strategy was evaluated by using data derived from a shuttle bus rapid transit (BRT) line in the city of Mashhad, Iran. The BRT line was simulated and calibrated by available empirical and real-time data from the automatic vehicle location and automatic passenger counting systems. The results indicate that the proposed bus-holding strategy reduces total passenger waiting time by 8.65%.

scholarly journals Analisis Internet Group Management Protocol (IGMP) Menggunakan Software Wireshark dalam Layanan Live Streaming IPTV pada Multi Service Access Network (MSAN) di Area Darmo, Surabaya

2018 ◽  
Vol 4 (4) ◽  
pp. 176
Author(s):  
Filda Ayu Afrida ◽  
Suci Rahmatia
Keyword(s):  
Real Time ◽  
Internet Protocol ◽  
Data Retrieval ◽  
Live Streaming ◽  
Service Access ◽  
Time Data ◽  
Group Management ◽  
Media Player ◽  
Management Protocol ◽  
Internet Protocol Television

<p><em>Abstrak</em> – <strong>Internet Protocol Television (IPTV) dengan data real time sangat sensitif terhadap paket yang hilang dan terlambat jika koneksi IPTV tidak begitu cepat. IPTV menggunakan Internet Protocol (IP) melewati jaringan broadband untuk pengiriman sinyal televisi digital yang mempunyai kecepatan data tinggi. Pengamatan dan analisa lebih fokus pada pengukuran live streaming dan pengambilan data secara real time di area Darmo, Surabaya. Pengukuran tersebut meliputi pengambilan data melalui aplikasi VLC Media Player dengan bantuan capture software wireshark dan implementasi layanan IPTV berbasis Internet Group Management Protocol (IGMP). Layanan IPTV ini menggunakan data realtime yaitu waktu live streaming, source, destination, protocol, dan length.</strong></p><p><strong></strong><br /><em>Abstract</em> - <strong>Internet Protocol Television (IPTV) with real time data is very sensitive to lost and late packets if the IPTV connection is not so fast. IPTV uses Internet Protocol (IP) over broadband networks to transmit digital television signals that have high data rates. Observation and analysis focus more on live streaming measurements and data retrieval in real time in the Darmo area, Surabaya. These measurements include taking data through the VLC Media Player application with the help of capture Wireshark software and implementing IPTV services based on Internet Group Management Protocol (IGMP). This IPTV service uses realtime data, live streaming time, source, destination, protocol, and length.</strong></p><p><em><strong>Keywords</strong> - IPTV, IGMP, software wireshark, bandwith</em></p>

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