Reading Vehicular Messages from Smart Road Signs: A Novel Method to Support Vehicle-to-Infrastructure in Rural Settings

Vehicle-to-infrastructure (V2I) communication is essential for reliable deployment of connected automated vehicle technology, contributing to the advanced safety and optimization of our transportation networks. However, supplying and maintaining necessary wireless infrastructure is a challenging task, particularly when it comes to rural areas. This study proposes a novel methodology that uses artificial intelligence, machine vision, and smart traffic signs to support V2I in areas where availability of wireless communication infrastructure is limited. The objective of this paper is to investigate the operational challenges of the proposed low-cost solution in different V2I applications, including a MapData message in an unsignalized traffic intersection, traveler information message in a work zone, and a red-light violation warning with the help of a smart sign. The proposed system showed some important advantages, such as invulnerability to third-party alterations and robust operation under harsh environmental conditions.

Smart Region Mobility Framework

A smart city describes an urban setting which aims to effectively apply ICT technologies to help improve the well-being of its citizens and reduce the negative impacts of urbanization. The priority areas considered in the Global Smart City Index (SCI) by the Institute for Management Development’s (IMD) World Competitiveness Centre were key infrastructures and technologies in (1) health and safety, (2) mobility, (3) activities (e.g., recreational spaces), (4) opportunities (work and school), and (5) governance. A smart region is a term used to extend the concept of a smart city into both urban and rural settings to promote a sustainable planning approach at the regional level. A direction that must be considered is the adoption of a “Smart Region Mobility Framework” to effectively transform our urban and rural regional transportation networks. This research study focused on the development of the smart region mobility framework for an island region group in the Philippines. The smart region goal is to integrate intelligent transportation system (ITS) platforms such as advanced public transportation system (APTS), advanced traveler information system (ATIS), and advanced rural transportation system (ARTS) to the local public transportation route plans (LPTRP) of the region. The activities include the data collection, analysis, and evaluation of multimodal regional transportation networks and social services infrastructure. The transportation network modeling process follows the four-step transportation planning process of trip generation, trip distribution, modal-split analysis, and trip assignment. Based on the analysis of 6 provinces, 16 cities, and 114 municipalities included in the study, there are two cities identified as smart city candidates. One of the smart city candidates is designated as the smart city regional center. In the context of a smart region, the available social services (e.g., employment opportunities, education, and health services) in the designated smart cities can also be made accessible to connected cities/municipalities through ease of transportation and mobility services in the region. Lastly, the study presented the implementation of data flow architecture of the smart region mobility framework, and the regional traveler information system using mobile and web application services.

The Association between ICT-Based Mobility Services and Sustainable Mobility Behaviors of New Yorkers

The energy consumption and emissions in the urban transportation are influenced not only by technical efficiency in the mobility operations but also by the citizens’ mobility behaviors including mode choices and modal shift among sustainable and unsustainable mobility modes. Information and Communication Technologies (ICTs) can play an important role in the mobility behaviors of citizens, and it is necessary to study whether ICTs support sustainable mode choices like public transport and nonmotorized modes, which increase the total energy efficiency in the urban mobility and reduce traffic congestion and related emissions. This paper focuses on the two most popular ICT services in the urban transport, which are ATIS (Advanced Traveler Information Systems), and ridesourcing services. This study used the New York Citywide Mobility Survey (CMS) findings with a sample of 3346 participants. The associations between using these two ICT services and the mobility behaviors (mode choice with ATIS and modal shift to ridesourcing) are analyzed through a multinomial logistic regression and descriptive statistics, and the results are compared with similar international studies. The findings indicate that the respondents who use ATIS apps more frequently are more likely to use rail modes, bicycles, bus/shuttles, and rental/car sharing than private cars for their work trips. Moreover, the findings of the modal shift to ridesourcing indicate that the most replaced mobility modes by ridesourcing services are public transport (including rail modes and buses), taxis, and private cars, respectively.