Private Car O-D Flow Estimation Based on Automated Vehicle Monitoring Data: Theoretical Issues and Empirical Evidence

Data on the daily activity of private cars form the basis of many studies in the field of transportation engineering. In the past, in order to obtain such data, a large number of collection techniques based on travel diaries and driver interviews were used. Telematics applied to vehicles and to a broad range of economic activities has opened up new opportunities for transportation engineers, allowing a significant increase in the volume and detail level of data collected. One of the options for obtaining information on the daily activity of private cars now consists of processing data from automated vehicle monitoring (AVM). Therefore, in this context, and in order to explore the opportunity offered by telematics, this paper presents a methodology for obtaining origin–destination flows through basic info extracted from AVM/floating car data (FCD). Then, the benefits of such a procedure are evaluated through its implementation in a real test case, i.e., the Veneto region in northern Italy where full-day AVM/FCD data were available with about 30,000 vehicles surveyed and more than 388,000 trips identified. Then, the goodness of the proposed methodology for O-D flow estimation is validated through assignment to the road network and comparison with traffic count data. Taking into account aspects of vehicle-sampling observations, this paper also points out issues related to sample representativeness, both in terms of daily activities and spatial coverage. A preliminary descriptive analysis of the O-D flows was carried out, and the analysis of the revealed trip patterns is presented.

Vehicle Monitoring System based On IOT, Using 4G/LTE

In our World of today, the quest to get rich at all cost without working for our money has led some of our youth into crimes such as robbery and kidnapping. As a result of this and by the sheer fact that vehicles are now very expensive to buy these days, there is a need for people to safeguard their vehicles against these hoodlums to avoid loss of their precious Assets to these rampaging criminals. Tracking is technology that is used by many companies and individuals to track a vehicle, an individual or an asset by using many ways like GPS that operates using satellites and ground-based stations or by using our approach which depends on the cellular mobile towers. Vehicle tracking system is a system that can be used in monitoring and locating a vehicle, avoid theft or recover a stolen vehicle, for monitoring of vehicle routes to ensure strict compliance to an already defined vehicle routes, monitor driver’s behavior, predict bus arrival as well as for fleet management. Internet of things has made it very possible to devices to inter communicate amongst themselves and exchange information, helping in acquiring and analyzing information faster that we used to know in the past and this has helped more especially in vehicle monitoring to ensure that vehicle owners feel safe about their investments without fearing about their loss. In this paper, we propose a vehicle monitoring system based on IOT technology, using 4G/LTE to get the get the coordinate, speed, and overall condition of the vehicle, process and send to a remote server to be analyzed and used in locating the vehicle and monitor its other configured parameters. This is realized using Raspberry pi, 4G/LTE, GPS, Accelerometer and other sensors with communicate amongst themselves to get the environmental parameters which is processed and sent to a remote server where it is analyzed and represented on a map to locate the vehicle and monitor the other set parameters. 4G/LTE provides fast internet connectivity with