Vehicular mobile data collection platform to support the development of Intelligent Transportation Systems

Author(s):  
George Suciu ◽  
Marius Vochin ◽  
Alexandru Vulpe ◽  
Octavian Fratu
Author(s):  
Daniel Brand

The guidance provided by benefit/cost analysis (BCA) is used to identify the measures appropriate for assessing the benefits of intelligent transportation systems (ITS) investments using BCA. Proper recognition of how ITS differs from conventional transportation improvements can avoid expensive data collection, serious underestimates of the benefits of ITS, and mistakes in our planning and investment policies. The steps in BCA are described, including its strict rules governing the inclusion of benefit measures. An ITS causal model chain is presented that links the five traditional ITS goals (efficiency, mobility, safety, productivity, and energy/environment). The model chain varies from the conventional planning model because the ITS mobility and productivity benefit measures do not vary directly with its safety, energy, and environmental impacts. Recommendations are given for avoiding double counting ITS mobility and productivity benefits, and for identifying them correctly. Errors in valuing the mobility benefit using observed data on travel and ITS product and service buying behavior are described, as is the potential for serious underestimates of ITS mobility benefits from using observed or predicted travel time savings as the primary mobility benefit measure. Instead, direct measurement and valuation of the ITS mobility benefit using customer satisfaction (stated preference) survey methods avoid the problems of ( a) how exactly to measure the utility-generating features of ITS user benefits, and ( b) observing the behavioral responses to ITS information, which involve expensive data collection. Measuring customer satisfaction directly can also simplify other areas of ITS evaluation, including avoiding traditional transportation modeling in some instances.


2020 ◽  
Vol 19 (11) ◽  
pp. 2116-2135
Author(s):  
G.V. Savin

Subject. The article considers functioning and development of process flows of transportation and logistics system of a smart city. Objectives. The study identifies factors and dependencies of the quality of human life on the organization and management of stream processes. Methods. I perform a comparative analysis of previous studies, taking into account the uniquely designed results, and the econometric analysis. Results. The study builds multiple regression models that are associated with stream processes, highlights interdependent indicators of temporary traffic and pollution that affect the indicator of life quality. However, the identified congestion indicator enables to predict the time spent in traffic jams per year for all participants of stream processes. Conclusions. The introduction of modern intelligent transportation systems as a component of the transportation and logistics system of a smart city does not fully solve the problems of congestion in cities at the current rate of urbanization and motorization. A viable solution is to develop cooperative and autonomous intelligent transportation systems based on the logistics approach. This will ensure control over congestion, the reduction of which will contribute to improving the life quality of people in urban areas.


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