Energy shortage and atmospheric pollution problems are getting more serious in China, and transportation is the main source of energy consumption, pollutants, and carbon emissions. This study combined the activity-based analysis method with emission models, and investigated the influence mechanism of people’s activity travel scheduling on transportation energy consumption and emissions on holid...

The transportation sector is a complex system. Collecting transportation activity and the associated emissions data is extremely expensive and time-consuming. Grey Relational Analysis provides a viable alternative to overcome data insufficiency and gives insights for decision makers into such a complex system. In this paper, we achieved three major goals: (i) we explored the inter-relationships...

This paper introduces a hierarchical Markov model that can learn and infer a user’s daily movements through an urban community. The model uses multiple levels of abstraction in order to bridge the gap between raw GPS sensor measurements and high level information such as a user’s destination and mode of transportation. To achieve efficient inference, we apply Rao-Blackwellized particle filters ...

Next-generation transportation surveys will utilize Global Positioning Systems (GPS) to collect trip data. Due to their ubiquity, GPS-enabled mobile devices are becoming promising for use as survey tools. TRAC-IT is a mobile phone application that records travel behavior by collecting real-time GPS data and requiring minimal input from the user for data such as trip purpose, mode of transportat...

This paper introduces a hierarchical Markov model that can learn and infer a user’s daily movements through an urban community. The model uses multiple levels of abstraction in order to bridge the gap between raw GPS sensor measurements and high level information such as a user’s destination and mode of transportation. To achieve efficient inference, we apply Rao-Blackwellized particle filters ...

Understanding transportation mode from GPS (Global Positioning System) traces is an essential topic in the data mobility domain. In this paper, a framework is proposed to predict transportation modes. This framework follows a sequence of five steps: (i) data preparation, where GPS points are grouped in trajectory samples; (ii) point features generation; (iii) trajectory features extraction; (iv...

Multimodal transport refers to the transportation of goods under a single contract but performed with at least two different modes transport. This research designs new method for solving Transportation Problem (TP) by introducing multimodal systems fuzzy-stochastic environment, which we refer as Fuzzy-Stochastic (FSMMTP). An algorithm is developed reduce FSMMTP deterministic TP, mainly based on...

We describe competition over space between a competitive shipping industry (truck-barge) and one with market power (the railroad). The latter prices so as to "beat the competition" in equilibrium, or else at the monopoly price, if that is lower. The monopoly price rises more slowly than do the costs of transportation (freight absorption) if the spatial demand at each point is log-concave. With ...

This paper proposed an algorithm to decrease the discrepancies between imputation and real GPS data. Based on the activity-travel pattern obtained using a Bayesian Belief Network model, the algorithm takes into account the consistency of the full activitytravel pattern within a day in the sense that the activity-travel sequence is represented in terms of a hierarchical set of tours, and the tra...