Integrated Design of Traditional Traffic Information Acquisition Device

Author(s):  
Sijie Chen ◽  
Cong Zhai ◽  
Zewei Li ◽  
Jiaxin Zhang ◽  
Xinghua Pan
2020 ◽  
Vol 20 (4) ◽  
pp. 2132-2144
Author(s):  
Haijian Li ◽  
Guoqiang Zhao ◽  
Lingqiao Qin ◽  
Yanfang Yang

2012 ◽  
Vol 198-199 ◽  
pp. 1250-1255
Author(s):  
Xia Yang ◽  
Kai Yin ◽  
Hai Ying Liu ◽  
Hong Da Li

In this paper, based on characteristic analysis of driver training operation, a new approach of information acquisition for driver training is found, which is through extracting acceleration information. The information acquisition device which is under MEMS three-axis acceleration transducer, based on ADXL335 and MCU, can achieve real-time and accurate measurement of vehicles’ three-dimensional acceleration. By comparing the change curve of measured acceleration with the related data of good driver, the existing problems will be found out. In this way, the driver training operation can be assessed in a timely way.


2014 ◽  
Vol 496-500 ◽  
pp. 2971-2974
Author(s):  
Wen Jun Liu ◽  
Sen Su ◽  
Fu Ping Wang ◽  
Kui Li ◽  
Zhi Yong Yin

This paper presents a method to create the traffic accident scene graphic based on electronic maps and information acquisition device (IAD). The method uses global position system (GPS) and electronic maps to get the satellite images of accident site, and it uses an IAD to obtain the angle and distance data between the origin position determined by the IAD and the locations prepared to be measured in the accident scene. With the data operation and image processing, we can create an isometric traffic accident scene graphic. This method provides the traffic accident spot data collecting, graph drawing and reason analyzing a more convenient and scientific technical means.


Author(s):  
Athena Tsirimpa ◽  
Amalia Polydoropoulou

The main objective of this article is to gain fundamental understanding on the effect of real time information acquisition, on the traffic conditions of the Athens greater area. Activity scheduling is a dynamic process, where individuals often need to modify their schedule, as a result of new insights. Research so far hasn't analyzed the effect of traffic information acquisition, in activity scheduling, although several studies have been conducted to capture the factors that influence the rescheduling of activities. An integrated latent variable model has been estimated, that predicts the probability of rescheduling activities as a function of flexibility, mode choice constraints and travel information. The analysis of the results indicates that one of the biggest impacts of traffic information acquisition is reflected in the rescheduling of activities. Therefore, traffic information not only can significantly improve the travel experience of individuals but may directly affect the performance of the transportation system.


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