Real-time Vehicle Speed Enforcement System

2021 ◽  
Author(s):  
Khalid Ammar ◽  
Abdullah Al-Emami ◽  
Amir Baher
Keyword(s):  
Real Time ◽  
Vehicle Speed ◽  
Speed Enforcement

Collecting Vehicle-Speed Data by Using Time-Lapse Video Recording Equipment

2003 ◽  
Vol 1855 (1) ◽  
pp. 97-104 ◽  
Author(s):  
Christopher Strong ◽  
Scott Lowry ◽  
Peter McCarthy
Keyword(s):  
Real Time ◽  
Video Recording ◽  
Warning System ◽  
Time Lapse ◽  
Vehicle Speed ◽  
Recording Equipment ◽  
Safety Improvement ◽  
Camera Location ◽  
Message Signs ◽  
Time Lapse Video

An innovative application of time-lapse video recording is used to assist in an evaluation of a highway safety improvement. The improvement is an icy-curve warning system near Fredonyer Summit in northern California that activates real-time motorist warnings via extinguishable message signs, based on weather readings collected from road weather information systems. A measure of effectiveness is whether motorist speed is reduced as a result of real-time warnings to drivers. Why indirect speed measurement with video was preferred over radar for this case is discussed, as is how specific methodological issues related to the custom-built equipment, including camera location and orientation, distance benchmarking, and data collection and reduction. Theoretical and empirical accuracy measurements show that the video surveillance trailers yield results comparable to radar and, hence, would be applicable for studies in which speed change is measured. Because this particular technology had not been used previously, several lessons are documented that may help determine where and how similar equipment may be optimally used in future studies.

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>

Rollover Warning of Articulated Vehicles Based on a Time-To-Rollover Metric

1999 ◽  
Author(s):  
Bo-Chiuan Chen ◽  
Huei Peng
Keyword(s):  
Real Time ◽  
The Other ◽  
Roll Angle ◽  
Vehicle Speed ◽  
Time Model ◽  
Whole Process ◽  
Articulated Vehicles ◽  
Articulated Vehicle ◽  
The One ◽  
Accuracy Problem

Abstract A Time-To-Rollover (TTR) metric is proposed as the basis to assess rollover threat for an articulated vehicle. Ideally, a TTR metric will accurately “count-down” toward rollover regardless of vehicle speed and steering patterns, so that the level of rollover threat is accurately indicated. To implement TTR in real-time, there are two conflicting requirements. On the one hand, a faster-than-real-time model is needed. On the other hand, the TTR predicted by this model needs to be accurate enough under all driving scenarios. An innovative approach is proposed in this paper to solve this dilemma and the whole process is illustrated in a design example. First, a simple yet reasonably accurate yaw/roll model is identified. A Neural Network (NN) is then developed to mitigate the accuracy problem of this simplified real-time model. The NN takes the TTR generated by the simplified model, vehicle roll angle and change of roll angle to generate an enhanced NN-TTR index. The NN was trained and verified under a variety of driving patterns. It was found that an accurate TTR is achievable across all the driving scenarios we tested.

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 Powertrain Optimization Strategy for Connected Hybrid Electrical Vehicle

2016 ◽  
Author(s):  
Mohd Azrin Mohd Zulkefli ◽  
Zongxuan Sun
Keyword(s):  
Real Time ◽  
Numerical Solutions ◽  
Computation Time ◽  
Computational Effort ◽  
Linear Functions ◽  
Traffic Information ◽  
Vehicle Speed ◽  
Connected Vehicle ◽  
Optimization Strategy ◽  
Separable Programming

Connected Vehicle (CV) technology, which allows traffic information sharing, and Hybrid Electrical Vehicles (HEV) can be combined to improve vehicle fuel efficiency. However, transient traffic information in CV environment necessitates a fast HEV powertrain optimization for real-time implementation. Model Predictive Control (MPC) with Linearization is proposed, but the computational effort is still prohibitive. The Equivalent Consumption Minimization Strategy (ECMS) and Adaptive-ECMS are proposed to minimize computation time, but unable to guarantee charge-sustaining-operation (CS). Fast analytical result from Pontryagin’s Minimum Principles (PMP) is possible but the input has to be unconstrained. Numerical solutions with Linear Programming (LP) are proposed, but over-simplifications of the cost and constraint functions limit the performance of such methods. In this paper, a nonlinear CS constraint is transformed into linear form with input variable change. With linear input and CS constraints, the problem is solved with Separable Programming by approximating the nonlinear cost with accurate linear piecewise functions which are convex. The piecewise-linear functions introduce new dimensionless variables which are solved as a large-dimension constrained linear problem with efficient LP solvers. Comparable fuel economy with Dynamic Programming (DP) is shown, with maximum fuel savings of 7% and 21.4% over PMP and Rule-Based (RB) optimizations. Simulations with different levels of vehicle speed prediction uncertainties to emulate CV settings are presented.

Research on Speed Monitoring and early Warning Method for Vehicles Based on RFID Sensor Tag

2010 ◽  
Vol 44-47 ◽  
pp. 466-470
Author(s):  
Jiang Yuan ◽  
Kui Yan ◽  
Zi Xue Qiu ◽  
Jian Xin Shao
Keyword(s):  
Real Time ◽  
Early Warning ◽  
Experimental Results ◽  
New Method ◽  
Vehicle Speed ◽  
Control Center ◽  
Average Speed ◽  
Identity Information ◽  
Monitoring And Early Warning

A new method was proposed for vehicle speed monitoring and early warning based on RFID sensor tag technology to realize real-time speed monitoring in high way. The principle of speed monitoring, the hardware and software of RFID sensor tag and reader network using GPRS technology were introduced in detail. Experimental results show that the actual velocity of vehicles can be acquired by on board RFID sensor tag, when the vehicle drives over the limited speed, the system can voice alarm to the driver. The identity information, actual speed and time of vehicle are read wirelessly by readers installed along the roadside, these messages can be upload to control center through GPRS network to monitor vehicle states, such as the position, average speed, the flow of transportation and so on.

Intelligent Correction of Shift Schedule for Dual Clutch Transmissions Based on Different Driving Conditions

2011 ◽  
Vol 121-126 ◽  
pp. 3982-3987
Author(s):  
Yong Gang Liu ◽  
Da Tong Qin ◽  
Zhen Zhen Lei ◽  
Rui Ding
Keyword(s):  
Fuzzy Logic ◽  
Real Time ◽  
Time Shift ◽  
Correction Coefficient ◽  
Vehicle Speed ◽  
Shift Schedule ◽  
Shift Control ◽  
Driving Condition ◽  
Driving Conditions ◽  
Driver’S Intention

This paper focuses on intelligent correction of shift schedule for dual clutch transmissions based on different driving conditions. The problem of standard shift schedule has been presented, and the strategy has also been proposed to avoid shift hunting and unexpected shift. The driver’s intention and driving environment have been unified recognized as different driving conditions. A fuzzy logic technology has been used in driver’s attention recognition based on the throttle opening and its derivative. The standard shift schedule has been intelligently corrected at different driving condition separately. An algorithm based on correction coefficient of throttle opening and vehicle speed is proposed for intelligent correction. The corrected shift schedule can be directly used in real time shift control with suitable correction coefficient.

scholarly journals An Empirical Study for Green Transportation Scheme of Municipal Solid Waste Based on Complex Data Model Analysis

2021 ◽  
Vol 2021 ◽  
pp. 1-17
Author(s):  
Chunlin Xin ◽  
Lingjie Wang ◽  
Bin Liu ◽  
Yu-Hsi Yuan ◽  
Sang-Bing Tsai
Keyword(s):  
Air Pollution ◽  
Municipal Solid Waste ◽  
Solid Waste ◽  
Real Time ◽  
Time Window ◽  
Complex Data ◽  
Vehicle Speed ◽  
Traffic Conditions ◽  
Real Time Traffic ◽  
Green Transportation

Solid waste management and air pollution are two pressing issues in the functioning of large cities. This paper studies the optimization problem of the green transportation route of municipal solid waste and establishes a mathematical planning model based on real-time traffic conditions of the city and consideration of a time window and multiple transfer stations with the goal of minimizing energy consumption. In the optimal green transportation process in this paper, comprehensive consideration of vehicle speed, vehicle load, road gradient, and driving distance in different road sections based on real-time traffic conditions is incorporated, which has a better fuel-saving potential than the shortest path. A green transportation program can alleviate the air pollution problem in big cities and promote energy conservation and emission reduction in solid waste transportation.

scholarly journals Research on Local Dynamic Path Planning Method for Intelligent Vehicle Lane-Changing

2019 ◽  
Vol 2019 ◽  
pp. 1-10 ◽  
Author(s):  
Zhi-qiang Liu ◽  
Teng Zhang ◽  
Yi-fan Wang
Keyword(s):  
Path Planning ◽  
Real Time ◽  
Planning Method ◽  
Local Dynamic ◽  
Vehicle Speed ◽  
Lane Changing ◽  
Dynamic Path Planning ◽  
Dynamic Path ◽  
Real Time Information ◽  
Time Information

A local dynamic path planning method is proposed to compensate for the lack of consideration of the movement state of surrounding vehicles, the poor comfort, and the low traffic efficiency when the existing vehicle changes lanes automatically. Firstly, the cubic polynomial is predefined, and the optimal track path is solved. According to the real-time information of environment perception, the model is continuously modified by acquiring real-time information in the course of path planning, and the regional safety of the vehicle is realized. The Carsim and simulink simulation results and actual vehicle verification show that, compared with the traditional nondynamic research method, this method can effectively solve the problem that the vehicle speed variation and the sudden intrusions of the vehicle leading to the compulsory operation of the vehicle during the course of lane-changing. The safety is also improved. In order to ensure the vehicle comfort and stability, the lane-changing time is shortened by 20%, and the efficiency of lane-changing is improved obviously.

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