A Survey of Traditional and Customized Bus Transportation Planning Methodologies

Transportation planning is an area of public policy that is increasingly recognized for having a significant impact on human health and well-being. Passengers all across the world are choosing bus transit as one of the most cost-effective ways of transportation. The number of passengers who use this mode of transportation is steadily increasing. According to statistics, the bus was India's most popular mode of transportation in 2014. A bus was viewed as a mode of transportation by 66 percent of families in rural areas and 62 percent of households in urban areas. With increased demand, there is a concern about efficiently organizing this service. Because a lack of planning can generate major problems in the real world, such as traffic jams and high operating expenses, it is a source of concern for corporate and government entities who provide this service. In this paper, a review on various bus transit planning approaches and stages and methodologies used in each stage of the customized bus planning strategy is presented. This study will assist bus service organizing entities, whether private or public, in efficiently organizing bus service

On planning, planning theories, and practices: A critical reflection

The futility of defining planning suggests that there is no planning as a recognizable practice. Sociology of knowledge definitions imply three kinds of planning practices: (1) Generic “planning”—what people do when they are planning; (2) Knowledge-centered “something” (e.g., spatial) planning; and (3) Real planning practiced in specific contexts, from metro-regional planning for Jakarta to transportation planning for the Trans-Europe Network, and enacted in general contexts, for example, informal- or Southern planning. Planning theories are linked to different practices: generic “planning” theories and “something” (e.g., regional, community, environmental, or Southern) planning theories. Selected topics illustrate the “planning” theory discourse and spatial planning theories are briefly reviewed. Three generations of planning practice studies are reviewed: the first, a-theoretical; the second, the “practice movement,” who studied practice for their own theorizing; and the third, informed by practice theories. Five books about planning show how their planning theorist authors understand planning practice. While recognizing planning as diverse practices, they hardly apply “planning” theory to planning practices. “Planning” theories are divorced from enacted planning practices, “something” (e.g., spatial) planning theories include constructive adaptations of “planning” theories and paradigms, but knowledge about real planning practices is limited. Implications from these conclusions are drawn for planning theory, education, and practices.

INFORMATION AND TECHNOLOGICAL ASPECTS OF CARGO TRANSPORTATION PLANNING

The article considers the process of planning cargo transportation from the submission to the approval of applications for transportation, analyzes the reasons for their refusals and deviations. Measures are proposed to improve the efficiency of interaction between entities involved in the planning and implementation of cargo transportation.

From Traditional to Autonomous Vehicles: A Systematic Review of Data Availability

The increasing accessibility of mobility datasets has enabled research in green mobility, road safety, vehicular automation, and transportation planning and optimization. Many stakeholders have leveraged vehicular datasets to study conventional driving characteristics and self-driving tasks. Notably, many of these datasets have been made publicly available, fostering collaboration, scientific comparability, and replication. As these datasets encompass several study domains and contain distinctive characteristics, selecting the appropriate dataset to investigate driving aspects might be challenging. To the best of the authors’ knowledge, this is the first paper that performs a systematic review of a substantial number of vehicular datasets covering various automation levels. In total, 103 datasets have been reviewed, 35 of which focused on naturalistic driving, and 68 on self-driving tasks. The paper gives researchers the possibility of analyzing the datasets’ principal characteristics and their study domains. Most naturalistic datasets have been centered on road safety and driver behavior, although transportation planning and eco-driving have also been studied. Furthermore, datasets for autonomous driving have been analyzed according to their target self-driving tasks. A particular focus has been placed on data-driven risk assessment for the vehicular ecosystem. It is observed that there exists a lack of relevant publicly available datasets that challenge the creation of new risk assessment models for semi- and fully automated vehicles. Therefore, this paper conducts a gap analysis to identify possible approaches using existing datasets and, additionally, a set of relevant vehicular data fields that could be incorporated in future data collection campaigns to address the challenge.