With the continuous development of intelligent transportation technologies, new ways of energy usage in transportation continue to emerge, which puts forward new requirements for the planning and design of energy systems. However, comprehensive analyses on the characteristics of transportation energy systems and the development trend of energy usage patterns brought by intelligent technologies have rarely been carried out so far. This paper explores this subject by reviewing the recent development and utilization of intelligent technologies in the transportation system and its impacts on energy usage. This review is carried out from three aspects, covering the representative intelligent transportation and energy technologies on vehicles, infrastructures and systems. The scope is limited within road, railway and water transport domains, with a focus on the recent developments in China as a representative. In terms of vehicles, the development trend of the power systems for new energy vehicles, the characteristics of energy usages in electric vehicles and the effects on energy saving and emission reduction are summarized. In terms of infrastructures, new technologies on smart road, smart port, intelligent railway energy system and the usage of clear energy on electric grid for transportation are reviewed, with the consideration of their potential influences on energy usages and the energy consumption characteristics of typical facilities also being analyzed. As for the transportation system, this review has focused on intelligent and connected transportation systems, train control and autonomous systems, and intelligent shipping system, with the emphasis on the energy saving and emission reduction effects of applying these intelligent technologies. The overall development trend of the transportation energy system is then analyzed based on the above materials, in particular, the future energy usage patterns in transportation system are given and the major challenges and obstacles approaching the future scenarios are also identified.

The 3D road network scene helps to simulate the distribution of road infrastructure and the corresponding traffic conditions. However, the existing road modeling methods have limitations such as inflexibility in different types of road construction, inferior quality in visual effects and poor efficiency for large-scale model rendering. To tackle these challenges, a template-based 3D road modeling method is proposed in this paper. In this method, the road GIS data is first pre-processed before modeling. The road centerlines are analyzed to extract topology information and resampled to improve path accuracy and match the terrain. Meanwhile, the road network is segmented and organized using a hierarchical block data structure. Road elements, including roadbeds, road facilities and moving vehicles are then designed based on templates. These templates define the geometric and semantic information of elements along both the cross-section and road centerline. Finally, the road network scene is built by the construction algorithms, where roads, at-grade intersections, grade separated areas and moving vehicles are modeled and simulated separately. The proposed method is tested by generating large-scale virtual road network scenes in the World Wind, an open source software package. The experimental results demonstrate that the method is flexible and can be used to develop different types of road models and efficiently simulate large-scale road network environments.

The mechanisms of collision avoidance (CA) behaviours in interweaving pedestrian flow movements are important for pedestrian space planning and emergency management but not well understood yet. In this paper, a series of controlled interweaving pedestrian flow experiments with different densities are carried out to investigate the CA behaviours, especially CA strategy choices. Four types of CA strategies are manually identified in these experiments. Nine characteristic parameters based on the trajectory data are defined to explore the characteristics of CA behaviours. The experimental results reveal that (i) the CA behaviours change with density levels; (ii) heterogeneities can be found for individual pedestrians; (iii) the defined characteristic parameters show different statistical features for different types of CA strategies, and correlations exist between most of the parameter pairs; (iv) it usually takes 0.5–2.5 s to complete a CA process with a trajectory length of 0.5–3.5 m. A multi-nomial logit (MNL) model and a long-short-term-memory (LSTM) model are established respectively for predicting pedestrians' choices of CA strategies using the selected characteristic parameters as inputs. The modelling results prove the importance of using time-series data for pedestrian behaviour modelling, and the LSTM models show advantages over the MNL model at this point.

Contemporary integrated land-use transport models (ILUTMs) explicitly consider interactions between floorspace demand/supply and rent at fine spatial scales, which requires a good understanding between floorspace use pattern and competition of locations among socioeconomic activities. Floorspace use patterns are usually represented by space use coefficients (SUCs) by activity type by zone, which are then used to develop theoretical space-use-rent curves (SURCs), in order to reflect the elasticity between rent and floorspace consumption rates. Literature review indicates that existing studies mostly use borrowed SUCs or subjective judgement methods for synthesising base-year floorspace and developing SURCs. In general, their accuracy is largely unknown and synthesised floorspace could be highly inaccurate. In this study, a linear programming method is proposed to estimate localised SUCs by assuming that zonal population, employment and floorspace total data are available. Study results show that the method can provide localised SUCs and better SURCs than traditional methods. It is found that, as the size of the homogeneous optimisation areas (HOAs) decreases, the accuracy of zonal space totals estimated increases considerably. For example, the estimation error between the observed and estimated zonal space totals reduces from 76.2% under the most aggregate case to 24.7% under the most disaggregate case. The sum of square errors (SSEs) between the optimised SUCs and the SURCs also reduces to about one-quarter of their original values. The method proposed contributes to a procedural process to estimate localised SUCs with known accuracy, which is proved to be a better alternative to traditional synthesis methods.