Estimating Uncertainty of Bus Arrival Times and Passenger Occupancies

Travel time reliability and the availability of seating and boarding space are important indicators of bus service quality and strongly influence users’ satisfaction and attitudes towards bus transit systems. With Automated Vehicle Location (AVL) and Automated Passenger Counter (APC) units becoming common on buses, some agencies have begun to provide real-time bus location and passenger occupancy information as a means to improve perceived transit reliability. Travel time prediction models have also been established based on AVL and APC data. However, existing travel time prediction models fail to provide an indication of the uncertainty associated with these estimates. This can cause a false sense of precision, which can lead to experiences associated with unreliable service. Furthermore, no existing models are available to predict individual bus occupancies at downstream stops to help travelers understand if there will be space available to board. The purpose of this project was to develop modeling frameworks to predict travel times (and associated uncertainties) as well as individual bus passenger occupancies. For travel times, accelerated failure-time survival models were used to predict the entire distribution of travel times expected. The survival models were found to be just as accurate as models developed using traditional linear regression techniques. However, the survival models were found to have smaller variances associated with predictions. For passenger occupancies, linear and count regression models were compared. The linear regression models were found to outperform count regression models, perhaps due to the additive nature of the passenger boarding process. Various modeling frameworks were tested and the best frameworks were identified for predictions at near stops (within five stops downstream) and far stops (further than eight stops). Overall, these results can be integrated into existing real-time transit information systems to improve the quality of information provided to passengers

Advanced flight control system study

The architecture, requirements, and system elements of an ultrareliable, advanced flight control system are described. The basic criteria are functional reliability of 10 to the minus 10 power/hour of flight and only 6 month scheduled maintenance. A distributed system architecture is described, including a multiplexed communication system, reliable bus controller, the use of skewed sensor arrays, and actuator interfaces. Test bed and flight evaluation program are proposed

Human neuromaturation, juvenile extreme energy liability, and adult cognition/cooperation

Human childhood and adolescence is the period in which adult cognitive competences (including those that create the unique cooperativeness of humans) are acquired. It is also a period when neural development puts a juvenile’s survival at risk due to the high vulnerability of their brain to energy shortage. The brain of a 4 year-old human uses ≈50% of its total energy expenditure (TEE) (cf. adult ≈12%). This brain expensiveness is due to (1) the brain making up ≈6% of a 4 year-old body compared to 2% in an adult, and (2) increased energy metabolism that is ≈100% greater in the gray matter of a child than in an adult (a result of the extra costs of synaptic neuromaturation). The high absolute number of neurons in the human brain requires as part of learning a prolonged neurodevelopment. This refines inter- and intraarea neural networks so they become structured with economical “small world” connectivity attributes (such as hub organization and high cross-brain differentiation/integration). Once acquired, this connectivity enables highly complex adult cognitive capacities. Humans evolved as hunter-gatherers. Contemporary hunter-gatherers (and it is also likely Middle Paleolithic ones) pool high energy foods in an egalitarian manner that reliably supported mothers and juveniles with high energy intake. This type of sharing unique to humans protects against energy shortage happening to the immature brain. This cooperation that protects neuromaturation arises from adults having the capacity to communicate and evaluate social reputation, cognitive skills that exist as a result of extended neuromaturation. Human biology is therefore characterized by a presently overlooked bioenergetic-cognition loop (called here the “HEBE ring”) by which extended neuromaturation creates the cooperative abilities in adults that support juveniles through the potentially vulnerable period of the neurodevelopment needed to become such adults

Ethical and Social Aspects of Self-Driving Cars

As an envisaged future of transportation, self-driving cars are being discussed from various perspectives, including social, economical, engineering, computer science, design, and ethics. On the one hand, self-driving cars present new engineering problems that are being gradually successfully solved. On the other hand, social and ethical problems are typically being presented in the form of an idealized unsolvable decision-making problem, the so-called trolley problem, which is grossly misleading. We argue that an applied engineering ethical approach for the development of new technology is what is needed; the approach should be applied, meaning that it should focus on the analysis of complex real-world engineering problems. Software plays a crucial role for the control of self-driving cars; therefore, software engineering solutions should seriously handle ethical and social considerations. In this paper we take a closer look at the regulative instruments, standards, design, and implementations of components, systems, and services and we present practical social and ethical challenges that have to be met, as well as novel expectations for software engineering.Comment: 11 pages, 3 figures, 2 table

System data communication structures for active-control transport aircraft, volume 2

The application of communication structures to advanced transport aircraft are addressed. First, a set of avionic functional requirements is established, and a baseline set of avionics equipment is defined that will meet the requirements. Three alternative configurations for this equipment are then identified that represent the evolution toward more dispersed systems. Candidate communication structures are proposed for each system configuration, and these are compared using trade off analyses; these analyses emphasize reliability but also address complexity. Multiplex buses are recognized as the likely near term choice with mesh networks being desirable for advanced, highly dispersed systems