Design and Development of Logistics and Transport Route Control System

2011 ◽  
Vol 71-78 ◽  
pp. 4261-4264
Author(s):  
Ru Wang ◽  
San Yuan Tang ◽  
Wei Xin Sun

According that town plan is mainly drawn with software AutoCAD, this article realizes to automatically select a shortest transport route on urban road and dynamically display traffic flow based on VC++ and ObjectARX and lays a foundation for future development taking traffic limit, traffic conditions and other complex conditions into account.

2018 ◽  
Vol 2018 ◽  
pp. 1-11 ◽  
Author(s):  
Mohammad Maghrour Zefreh ◽  
Adam Torok

Road traffic noise is one of the most relevant sources in the environmental noise pollution of the urban areas where dynamics of the traffic flow are much more complicated than uninterrupted traffic flows. It is evident that different traffic conditions would play the role in the urban traffic flow considering the dynamic nature of the traffic flow on one hand and presence of traffic lights, roundabouts, etc. on the other hand. The main aim of the current paper is to investigate the effect of different traffic conditions on urban road traffic noise. To do so, different traffic conditions have been theoretically generated by the Monte Carlo Simulation technique following the distribution of traffic speed in the urban roads. The “ASJ RTN-Model” has been considered as a base road traffic noise prediction model which would deal with different traffic conditions including steady and nonsteady traffic flow that would cover the urban traffic flow conditions properly. Having generated the vehicles speeds in different traffic conditions, the emitted noise (LWA) and subsequently the noise level at receiver (LA) were estimated by “ASJ RTN-Model.” Having estimated LWA and LA for each and every vehicle in each traffic condition and taking the concept of transient noise into account, the single event sound exposure levels (SEL) in different traffic conditions are calculated and compared to each other. The results showed that decelerated traffic flow had the lowest contribution, compared to congestion, accelerated flow, free flow, oversaturated congestion, and undersaturated flow by 16%, 14%, 12%, 12%, and 10%, respectively. Moreover, the distribution of emitted noise and noise level at receiver were compared in different traffic conditions. The results showed that traffic congestion had considerably the maximum peak compared to other traffic conditions which would highlight the importance of the range of generated noise in different traffic conditions.


2015 ◽  
Vol 9 (1) ◽  
pp. 21-26
Author(s):  
Mulyadi Sinung Harjono ◽  
Wimpie A.N Aspar ◽  
Abdul Halim ◽  
Kalamullah Ramli

Abstract Research traffic dynamics modeling requires the enumeration of traffic flow data on many road network nodes. Information enumeration traffic flows are applied to the analysis model of the road network control or control the intersection area, either as a standalone junction (isolated) and the coordinative intersection. Classification of types and traffic conditions used for this control is determined by ITS transportation management policy or government. Estimation and prediction of traffic conditions in real terms are based on information obtained by traffic counting. Counting of traffic flows is aimed to determine the probability distribution function (pdf) traffic flow for the intersection of two segments, namely Jalan Kyai Haji Wahid Hasyim - Jalan Mohammad Husni Thamrin and Jalan Kebun Sirih - Jalan Mohammad Husni Thamrin, Jakarta, Indonesia. Signalized intersection is composed of roads with 12 lanes and 4 lanes with traffic signs and fixtures actuated traffic control system using historical data. Based on the evolution of the combined token, it was obtained fundamental equation for the evolution of the token. Based on the modeling, the needs of departure vehicle for red light violators and breakthrough yellow light, it would require further development to SimHPN. Modeling and simulation of hybrid Petri nets on this research are aimed to perform optimal control system for traffic flow, the number of vehicles at intersections, in order to obtain optimal current flow in the study area. Abstrak Penelitian pemodelan dinamika lalu-lintas memerlukan data pencacahan arus lalu-lintas (traffic counting) pada banyak simpul jaringan jalan. Informasi pencacahan arus lalu-lintas tersebut dipergunakan untuk analisa model pengendalian jaringan jalan ataupun pengendalian area persimpangan, baik sebagai persimpangan mandiri (isolated) maupun persimpangan koordinatif. Penggolongan jenis dan kondisi lalu-lintas yang dipergunakan untuk pengendalian ini ditentukan oleh kebijakan manajemen transportasi ITS ataupun pemerintah. Estimasi dan prediksi kondisi lalu-lintas secara riil diperoleh berdasarkan informasi hasil pencacahan arus lalu-lintas. Pencacahan arus lalulintas bertujuan untuk menentukan fungsi distribusi probabilitas (pdf) arus lalulintas untuk dua ruas persimpangan, yaitu Jalan Kyai Haji Wahid Hasyim - Jalan Mohammad Husni Thamrin dan Jalan Kebon Sirih - Jalan Mohammad Husni Thamrin, Jakarta Indonesia. Persimpangan bersinyal ini tersusun atas ruas jalan dengan 12 lajur dan 4 lajur dengan rambu lalu-lintas dan perlengkapan actuated traffic control system menggunakan data historical. Berdasarkan evolusi token gabungan diperoleh persamaan fundamental untuk evolusi token. Berdasarkan kebutuhan pemodelan keberangkatan kendaraan untuk pelanggar lampu merah dan penerobos lampu kuning, maka diperlukan pengembangan lebih lanjut terhadap SimHPN. Pemodelan dan simulasi dengan hybrid Petri nets pada penelitian ditujukan untuk melakukan sistem kendali optimal terhadap arus lalulintas, jumlah kendaraan di persimpangan, sehingga diperoleh aliran arus optimal pada area penelitian.


Author(s):  
Rajesh Kumar Gupta ◽  
L. N. Padhy ◽  
Sanjay Kumar Padhi

Traffic congestion on road networks is one of the most significant problems that is faced in almost all urban areas. Driving under traffic congestion compels frequent idling, acceleration, and braking, which increase energy consumption and wear and tear on vehicles. By efficiently maneuvering vehicles, traffic flow can be improved. An Adaptive Cruise Control (ACC) system in a car automatically detects its leading vehicle and adjusts the headway by using both the throttle and the brake. Conventional ACC systems are not suitable in congested traffic conditions due to their response delay.  For this purpose, development of smart technologies that contribute to improved traffic flow, throughput and safety is needed. In today’s traffic, to achieve the safe inter-vehicle distance, improve safety, avoid congestion and the limited human perception of traffic conditions and human reaction characteristics constrains should be analyzed. In addition, erroneous human driving conditions may generate shockwaves in addition which causes traffic flow instabilities. In this paper to achieve inter-vehicle distance and improved throughput, we consider Cooperative Adaptive Cruise Control (CACC) system. CACC is then implemented in Smart Driving System. For better Performance, wireless communication is used to exchange Information of individual vehicle. By introducing vehicle to vehicle (V2V) communication and vehicle to roadside infrastructure (V2R) communications, the vehicle gets information not only from its previous and following vehicle but also from the vehicles in front of the previous Vehicle and following vehicle. This enables a vehicle to follow its predecessor at a closer distance under tighter control.


Author(s):  
Gustavo Poot Tah ◽  
Erika Llanes Castro ◽  
José Luis López Martínez ◽  
Victor Chi Pech

This paper presents the design and development of a mobile application that uses QR codes for the inventory control of a computer center. This application was developed to support the administration of the computer center of the Multidisciplinary Unit Tizimin, with the aim to reduce costs and time of searching for articles when making an inventory, by leveraging the capabilities of smartphones and tablets. The implementation of the system was carried out using free software.


2013 ◽  
Vol 846-847 ◽  
pp. 1608-1611 ◽  
Author(s):  
Hui Jie Ding

As more and more cars are in service, the traffic jam becomes a serious problem in our society. At the same time, more and more sensors make the cars more and more intelligent, and this promotes the development of Internet of things. Real time monitoring the cars will produce massive sensing data, the Cloud computing gives us a good manner to solve this problem. In this paper, we propose a traffic flow data collection and traffic signal control system based on Internet of things and the Cloud computing. The proposed system contains two main parts, sensing data collection and traffic status control subsystem.


2022 ◽  
Vol 13 (2) ◽  
pp. 1-25
Author(s):  
Bin Lu ◽  
Xiaoying Gan ◽  
Haiming Jin ◽  
Luoyi Fu ◽  
Xinbing Wang ◽  
...  

Urban traffic flow forecasting is a critical issue in intelligent transportation systems. Due to the complexity and uncertainty of urban road conditions, how to capture the dynamic spatiotemporal correlation and make accurate predictions is very challenging. In most of existing works, urban road network is often modeled as a fixed graph based on local proximity. However, such modeling is not sufficient to describe the dynamics of the road network and capture the global contextual information. In this paper, we consider constructing the road network as a dynamic weighted graph through attention mechanism. Furthermore, we propose to seek both spatial neighbors and semantic neighbors to make more connections between road nodes. We propose a novel Spatiotemporal Adaptive Gated Graph Convolution Network ( STAG-GCN ) to predict traffic conditions for several time steps ahead. STAG-GCN mainly consists of two major components: (1) multivariate self-attention Temporal Convolution Network ( TCN ) is utilized to capture local and long-range temporal dependencies across recent, daily-periodic and weekly-periodic observations; (2) mix-hop AG-GCN extracts selective spatial and semantic dependencies within multi-layer stacking through adaptive graph gating mechanism and mix-hop propagation mechanism. The output of different components are weighted fused to generate the final prediction results. Extensive experiments on two real-world large scale urban traffic dataset have verified the effectiveness, and the multi-step forecasting performance of our proposed models outperforms the state-of-the-art baselines.


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