Entropie analysis of floating car data systems

2005 ◽  
Vol 2 ◽  
pp. 169-174
Author(s):  
F. Gössel ◽  
E. Michler ◽  
B. Wrase
Keyword(s):  
Field Trials ◽  
Vehicle Speed ◽  
Data Systems ◽  
Traffic Condition ◽  
Time Profiles ◽  
Spatial Segmentation ◽  
Floating Car Data ◽  
Original Variable ◽  
Vehicle Velocity ◽  
Basic Prerequisite

Abstract. The knowledge of the actual traffic state is a basic prerequisite of modern traffic telematic systems. Floating Car Data (FCD) systems are becoming more and more important for the provision of actual and reliable traffic data. In these systems the vehicle velocity is the original variable for the evaluation of the current traffic condition. As real FCDsystems are operating under conditions of limited transmission and processing capacity the analysis of the original variable vehicle speed is of special interest. Entropy considerations are especially useful for the deduction of fundamental restrictions and limitations. The paper analyses velocity-time profiles by means of information entropy. It emphasises in quantification of the information content of velocity-time profiles and the discussion of entropy dynamic in velocity-time profiles. Investigations are based on empirical data derived during field trials. The analysis of entropy dynamic is carried out in two different ways. On one hand velocity differences within a certain interval of time are used, on the other hand the transinformation between velocities in certain time distances was evaluated. One important result is an optimal sample-rate for the detection of velocity data in FCD-systems. The influence of spatial segmentation and of different states of traffic was discussed.

scholarly journals Spectral analysis of Floating Car Data

2003 ◽  
Vol 1 ◽  
pp. 139-142 ◽  
Author(s):  
F. Gössel ◽  
E. Michler ◽  
B. Wrase
Keyword(s):  
Spectral Characteristics ◽  
Measurement Data ◽  
Essential Property ◽  
Time Profiles ◽  
Floating Car Data ◽  
Starting Point ◽  
Vehicle Velocity ◽  
Low Pass ◽  
Traffic Scenario ◽  
Sample Rate

Abstract. Floating Car Data (FCD) are one important data source in traffic telematic systems. The original variable in these systems is the vehicle velocity. The paper analyses the measured value “vehicle velocity" by methods of information technology. Consequences for processing, transmission and storage of FCD under condition of limited resources are discussed. Starting point of the investigation is the analysis of spectral characteristics of velocity-time-profiles. The spectra are determined by the Discrete Fourier Transform (DFT) from measurement data and simulation data of a microscopic traffic model. One essential property of velocity-time-profiles is their low-pass characteristic. The resulting cut-off-frequency is comparatively small and depends on the traffic scenario. Conclusions concerning the necessary sample rate in FCD systems and the processing of raw data are discussed. Finally the transinformation of velocity-time-profiles is analysed. This results in similar values for an optimal sample rate of FCD systems under condition of limited transmission capacity.

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>

Analysis of Speed Differences in Data from Remote Traffic Microwave Sensors and Floating Car Data Systems on Expressways

2017 ◽  
Vol 2643 (1) ◽  
pp. 112-120
Author(s):  
Jingyi Wang ◽  
Lei Yu ◽  
Yong Gao ◽  
Jianbo Zhang ◽  
Guohua Song
Keyword(s):  
Traffic Flow ◽  
Cross Sections ◽  
Travel Speed ◽  
Flow Speed ◽  
Data Systems ◽  
Floating Car Data ◽  
Microwave Sensor ◽  
The Difference ◽  
Data Collections ◽  
The Relationship

The remote traffic microwave sensor (RTMS) and the floating car data (FCD) system are two important sources of traffic data; both provide key speed information. However, these two data processes gather data differently. The RTMS detects spot speeds at specific cross sections. The FCD system collects travel speed along a segment of a road link. Although the difference between time mean speed (TMS) and space mean speed (SMS) has been discussed for decades, the speed differences between RTMS and FCD have been underestimated in many engineering applications. This study examined the speed differences between the RTMS and FCD data on expressways in Beijing. First, the differences between the two data collections over 5 days were analyzed. The correlation between the difference and the value of the speeds was investigated. The relationships between TMS and SMS in existing studies were then compared with the relationship derived from the field data. It was found that the existing relationships between TMS and SMS were not valid for representing the relationship between the RTMS and FCD speeds. The flow–speed relationship from each data group was then investigated by using the Van Aerde traffic flow model; it was found that free-flow speed and speed at capacity determined on the basis of the RTMS data were significantly overestimated. It was inaccurate to apply the RTMS speed to the analysis of fundamental traffic flow diagrams. Finally, the repeatability and stability of the relationship between these two data groups were validated.

scholarly journals Numerical methodology for evaluation the combustion and emissions characteristics on WLTP in the light duty dual-fuel diesel vehicle

2021 ◽  
Author(s):  
Zbigniew Kneba ◽  
Denys Stepanenko ◽  
Jacek Rudnicki
Keyword(s):  
Internal Combustion Engines ◽  
Test Procedure ◽  
Real Life ◽  
Dual Fuel ◽  
Velocity Versus ◽  
Engine Operation ◽  
Time Profiles ◽  
General Terms ◽  
Vehicle Velocity ◽  
Harmful Emissions

The worldwide aim of reducing environmental impact from internal combustion engines bring more and more stringent emission regulations. In 2017 by EU has been adopted new harmonized test procedure called WLTP. In general terms this test was designed for determining the levels of harmful emissions and fuel consumption of traditional and hybrid cars. This procedure contains specific driving scenarios which representing real-life driving patterns. Test cycles contain vehicle velocity versus time profiles and directly in powertrain analysis on the test benches cannot be used. In order to back calculate drive cycles to engine rpm versus torque profiles a simple longitudinal vehicle dynamics method was used in this paper. Moreover, in order to determine most representative engine operation points duing WLTP a density based grid clustering method was implemented. The experimental part of the study focuses on the comparative evaluation of the effect of various diesel to LPG substitution ratios (0% LPG, 10% LPG, 20% LPG and 30% LPG) on combustion and emission characteristics of dual-fuel diesel engine.

Fuzzy Estimation of Vehicle Speed

2005 ◽  
Author(s):  
Kyeung Heub Oh ◽  
Jin Kwon Hwang ◽  
Chul Ki Song
Keyword(s):  
Estimation Method ◽  
Experimental Result ◽  
Vehicle Speed ◽  
Wheel Slip ◽  
Worst Case ◽  
Acceleration Signal ◽  
Vehicle Velocity ◽  
Antilock Braking System ◽  
Speed Estimator ◽  
Using Data

The absolute longitudinal speed of a vehicle is estimated by using data from an accelerometer of the vehicle and wheel speed sensors of a standard 50-tooth antilock braking system. An intuitive solution to this problem is, “When wheel slip is low, calculate the vehicle velocity from the wheel speeds; when wheel slip is high, calculate the vehicle speed by integrating signal of the accelerometer.” The speed estimator weighted with fuzzy logic is introduced to implement the above concept, which is formulated as an estimation method. And the method is improved through experiments by how to calculate speed from acceleration signal and slip ratios. It is verified experimentally to usefulness o estimation speed of a vehicle. And the experimental result shows that the estimated vehicle longitudinal speed has only a 6 % worst-case error during a hard braking maneuver lasting a few seconds.

scholarly journals Automated Incident Detection Using Real-Time Floating Car Data

2017 ◽  
Vol 2017 ◽  
pp. 1-13 ◽  
Author(s):  
Maarten Houbraken ◽  
Steven Logghe ◽  
Marco Schreuder ◽  
Pieter Audenaert ◽  
Didier Colle ◽  
...  
Keyword(s):  
Traffic Safety ◽  
Large Scale ◽  
Low Cost ◽  
Field Trials ◽  
Traffic Monitoring ◽  
Sensor Data ◽  
Feasibility Trial ◽  
Incident Detection ◽  
The Road ◽  
Floating Car Data

The aim of this paper is to demonstrate the feasibility of a live Automated Incident Detection (AID) system using only Floating Car Data (FCD) in one of the first large-scale FCD AID field trials. AID systems detect traffic events and alert upcoming drivers to improve traffic safety without human monitoring. These automated systems traditionally rely on traffic monitoring sensors embedded in the road. FCD allows for finer spatial granularity of traffic monitoring. However, low penetration rates of FCD probe vehicles and the data latency have historically hindered FCD AID deployment. We use a live country-wide FCD system monitoring an estimated 5.93% of all vehicles. An FCD AID system is presented and compared to the installed AID system (using loop sensor data) on 2 different highways in Netherlands. Our results show the FCD AID can adequately monitor changing traffic conditions and follow the AID benchmark. The presented FCD AID is integrated with the road operator systems as part of an innovation project, making this, to the best of our knowledge, the first full chain technical feasibility trial of an FCD-only AID system. Additionally, FCD allows for AID on roads without installed sensors, allowing road safety improvements at low cost.

scholarly journals Route Choice of the Shortest Travel Time Based on Floating Car Data

2016 ◽  
Vol 2016 ◽  
pp. 1-11 ◽  
Author(s):  
Jingwei Shen ◽  
Yifang Ban
Keyword(s):  
Travel Time ◽  
Optimal Path ◽  
Route Choice ◽  
Edge Weight ◽  
Map Matching ◽  
Traffic Condition ◽  
Floating Car Data ◽  
Road Map ◽  
Shortest Distance ◽  
Comparison Results

Finding a route with shortest travel time according to the traffic condition can help travelers to make better route choice decisions. In this paper, the shortest travel time based on FCD (floating car data) which is used to assess overall traffic conditions is proposed. To better fit FCD and road map, a new map matching algorithm which fully considers distance factor, direction factor, and accessibility factor is designed to map all GPS (Global Positioning System) points to roads. A mixed graph structure is constructed and a route analysis algorithm of shortest travel time which considers the dynamic edge weight is designed. By comparing with other map matching algorithms, the proposed method has a higher accuracy. The comparison results show that the shortest travel time path is longer than the shortest distance path, but it costs less traveling time. The implementation of the route choice based on the shortest travel time method can be used to guide people’s travel by selecting the space-time dependent optimal path.

scholarly journals Mathematical Model for Velocity Calculation of Three Types of Vehicles in the Case of Pedestrian Crash

2018 ◽  
Vol 68 (3) ◽  
pp. 95-110
Author(s):  
Hoxha Gëzim ◽  
Shala Ahmet ◽  
Likaj Ramë ◽  
Bajrami Xhevahir
Keyword(s):  
Mathematical Model ◽  
Accurate Determination ◽  
Geometrical Parameters ◽  
Vehicle Speed ◽  
Model Formulation ◽  
Vehicle Velocity ◽  
Pedestrian Accidents ◽  
Throw Distance ◽  
Front Profile

AbstractThis paper treats influencing factors in the determination of vehicles speed on the pedestrian crash moment according to pedestrian throw distance and formulates a mathematical model for vehicle speed determination. Vehicle speed is one of the highest causes of accidents. The mathematical model formulation (as the target of this paper) for velocity calculation, in the case of pedestrian accidents, presents great help and guidance to experts of this field when dealing with accident analysis that through accurate determination of this parameter to find other circumstances as close as possible to the technical process of pedestrian accidents. The target of this paper is to define a mathematical model formulation for vehicle velocity calculation in pedestrian crash moment depending on relevant parameters. For the purpose of model formulating, we have selected three cases of real accidents that involved vehicles (“Peugeot 307”, “VW Golf ” and “Mercedes E 220”) with different geometrical parameters of the front profile and pedestrians with different heights and weights. For regression analysis we used “R” and “SPSS” software, which enables the statistical analysis of the data and mathematical model formulation. Also, for analysis of impact of relevant factors, model formulation and model testing have used “Virtual Crash” and “PC Crash” software, which enables pedestrian-vehicle crash simulation using vehicles with real technical characteristics and various pedestrian characteristics. Inductive, comparative, and deductive methods are part of the research methods in this paper.

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