Vehicular Cloud data collection for Intelligent Transportation Systems

2016 ◽  
Author(s):  
Moumena Chaqfeh ◽  
Nader Mohamed ◽  
Imad Jawhar ◽  
Jie Wu
Keyword(s):  
Data Collection ◽  
Intelligent Transportation Systems ◽  
Intelligent Transportation ◽  
Transportation Systems ◽  
Cloud Data ◽  
Vehicular Cloud

Applying Benefit/Cost Analysis To Identify and Measure the Benefits of Intelligent Transportation Systems

1998 ◽  
Vol 1651 (1) ◽  
pp. 23-29 ◽  
Author(s):  
Daniel Brand
Keyword(s):  
Data Collection ◽  
Customer Satisfaction ◽  
Cost Analysis ◽  
Intelligent Transportation Systems ◽  
Stated Preference ◽  
Intelligent Transportation ◽  
Transportation Systems ◽  
Benefit Cost Analysis ◽  
Benefit Cost ◽  
Model Chain

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.

Challenges and Opportunities in Vehicular Cloud Computing

2018 ◽  
pp. 57-74 ◽  
Author(s):  
Zeinab E. Ahmed ◽  
Rashid A. Saeed ◽  
Amitava Mukherjee
Keyword(s):  
Cloud Computing ◽  
Intelligent Transportation Systems ◽  
Vehicular Ad Hoc Networks ◽  
Intelligent Transportation ◽  
Transportation Systems ◽  
Vehicular Cloud Computing ◽  
Vehicular Cloud ◽  
Traffic Efficiency ◽  
Challenges And Opportunities ◽  
Hoc Networks

Vehicular ad-hoc networks (VANET) have become an important research area due to their ability to allow sharing resources among the users to carry out their application and provide services of transport and traffic management. VANET communication allows exchange of sensitive information among nearby vehicles such as condition of weather and road accidents in order to improve vehicle traffic efficiency through Intelligent Transportation Systems (ITS). Many technologies have been developed to enhance ITS. Recently, vehicular cloud computing (VCC) has been developed in order to overcome the drawbacks VANET. VCC technology provides low-cost services to vehicles and capable of managing road traffic efficiently by using the vehicular sources (such as internet) to make decisions and for storage. VCC is considered as the basis for improving and developing intelligent transportation systems. It plays a major role in people's lives due to its safety, security, trust, and comfort to passengers and drivers. This chapter investigates the vehicular cloud computing. The authors first concentrate on architectures. Then, they highlight applications and features provided by VCC. Additionally, they explain the challenges for VCC. Finally, the authors present opportunities and future for VCC.

Challenges and Opportunities in Vehicular Cloud Computing

2019 ◽  
pp. 2168-2185 ◽  
Author(s):  
Zeinab E. Ahmed ◽  
Rashid A. Saeed ◽  
Amitava Mukherjee
Keyword(s):  
Cloud Computing ◽  
Intelligent Transportation Systems ◽  
Vehicular Ad Hoc Networks ◽  
Intelligent Transportation ◽  
Transportation Systems ◽  
Vehicular Cloud Computing ◽  
Vehicular Cloud ◽  
Traffic Efficiency ◽  
Challenges And Opportunities ◽  
Hoc Networks

Vehicular ad-hoc networks (VANET) have become an important research area due to their ability to allow sharing resources among the users to carry out their application and provide services of transport and traffic management. VANET communication allows exchange of sensitive information among nearby vehicles such as condition of weather and road accidents in order to improve vehicle traffic efficiency through Intelligent Transportation Systems (ITS). Many technologies have been developed to enhance ITS. Recently, vehicular cloud computing (VCC) has been developed in order to overcome the drawbacks VANET. VCC technology provides low-cost services to vehicles and capable of managing road traffic efficiently by using the vehicular sources (such as internet) to make decisions and for storage. VCC is considered as the basis for improving and developing intelligent transportation systems. It plays a major role in people's lives due to its safety, security, trust, and comfort to passengers and drivers. This chapter investigates the vehicular cloud computing. The authors first concentrate on architectures. Then, they highlight applications and features provided by VCC. Additionally, they explain the challenges for VCC. Finally, the authors present opportunities and future for VCC.

Quality indicator of the smart city transportation and logistics system

2020 ◽  
Vol 19 (11) ◽  
pp. 2116-2135
Author(s):  
G.V. Savin
Keyword(s):  
Intelligent Transportation Systems ◽  
Smart City ◽  
Urban Areas ◽  
Human Life ◽  
Life Quality ◽  
Intelligent Transportation ◽  
Transportation Systems ◽  
Logistics System ◽  
Organization And Management

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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