In the context of automated driving, the connected and automated vehicles (CAVs) technology unlock the energy saving potential. This paper develops an LSTM‐based deep learning framework for eco‐driving adaptive identification on Intelligent vehicle multivariate time series data. The framework can be adapted for Driver Assistance Systems (DAS) to reduce fuel consumption. Specifically, considering overtaking on rural road is a critical maneuver for operation and has potential to reduce consumption, a simulated driving experiment with 30 participants was conducted to collect the multivariate time series data of the overtaking operation behaviors in conditional automation driving. Driving behaviors were classified into eco‐driving operation behaviors and high fuel consumption operation behaviors based on fuel consumption calculated by using vehicle specific power (VSP). Significance analysis based on linear regression was adopted to identify operation behaviors, and an eco‐driving behavior identification model was established with the use of long short‐term memory (LSTM) for multivariate classification theory. Meanwhile, the other four classification algorithms were used to establish identification models for comparison. The results indicated that the gear position, lane position, the acceleration pedal depth, the clutch pedal depth, and the brake pedal depth had a significant influence on fuel consumption. The eco‐driving behavior identification model of overtaking demonstrated a high classification power and robustness with a classification accuracy of 89.16%. According to the simulation results, the developed adaptive identification model is with promising performance. The conclusions provide theoretical support for developing an adaptive strategy for connected eco‐driving.

We obtain new multilinear multiplier theorems for symbols of restricted smoothness which lie locally in certain Sobolev spaces. We provide applications concerning the boundedness of the commutators of Calderón and Calderón–Coifman–Journé.

This study proposes a metro freight plan for mixed passenger and freight transportation. First, this study explores the problem of single-line metro train service under mixed passenger and freight transportation. Then, comprehensively considering the constraints of metro train freight capacity, loading and unloading time, and train schedules, a metro freight service model was established, and an efficient and accurate train schedule and freight distribution plan were developed to minimize metro freight costs. Finally, through actual case studies, an improved variable neighborhood search algorithm (VNS) was used to verify the effectiveness of the model, and the sensitivity of different train capacities, train headway, and cargo operation cost to the cost of metro freight was also discussed. The cost of cargo operation is the main factor that affects the cost of metro freight. The metro freight plan proposed in this study can provide decision support for the setting of train schedules and freight distribution plans.

To effectively explore the impacts of several key factors on taxi drivers’ traffic violations and provide traffic management departments with scientific decisions to reduce traffic fatalities and i...

Autonomous vehicles (AVs) are a vital direction for intelligent transportation; nevertheless, the current research is insufficient, and the aspects and mechanisms that influence individuals adoption of AVs require additional investigation. This study examines the acceptance of the popularity of AVs from three perspectives: personal-psychological attributes, travel characteristics attributes, and latent variables. The descriptive statistical analysis revealed that the acceptance rate of AVs was 54.6 based on 304 valid questionnaires received through online questionnaires. And the proportion of the 1850 group in the article reached 92.8; thus, this study takes the young group as the object to investigate the acceptance of AVs. A quantitative analysis of each factors impact on the acceptability of AVs was conducted using the hybrid choice model (HCM), which was utilized to observe the link between latent variables. Results from parameter estimates demonstrate that the HCMs fitting impact when latent factors are taken into account is superior to that when latent variables are not taken into account. When latent variables are taken into account, the associated goodness ratio coefficient rises by 0.2337 to 0.2898, which is greater than the model as a whole. The three factors with the highest impact on AV acceptability among the five latent variables were attitude toward use, sense of use gain, and perceived trust, with matching z-test values of 2.42, 2.44, and 2.12, respectively. The development and marketing of AVs by pertinent businesses and government agencies would benefit greatly from this research as a source of reference.

As a policy that is widely used worldwide, Vision Zero is a long-term strategic goal for road safety in China. The aim of this paper is to examine the literature in the field of Vision Zero retrieved by the Web of Science (WOS) Core Collection database from 1997 to 2021 based on mapping knowledge domain (MKD) and bibliometric methods. In this paper, we analyzed the overall development level of Vision Zero at different stages using the statistical analysis of the distribution of literature years. Based on the analysis, four major research directions of Vision Zero are obtained through keywords co-occurrence analysis, including “Vision Zero in road safety”, “vulnerable road users’ risks”, “effect of speed on severity”, and “responsibility management for crashes”. Furthermore, we explore the influence and development potential of each country and region of Vision Zero based on the number and citation frequency of the literature, and the distribution of time dimensions. Among the research topics, all countries and regions are clustered into four clusters, and the current status of Vision Zero for countries in the most influential clusters, which include Sweden, the United States, Australia, China, and Norway, have been presented. Finally, an analysis of road safety in China is carried out, which includes displaying the changes in the number of road accidents, fatalities, and serious injuries in China between 2009 and 2018, comparing the fatalities per 10,000 vehicles and the fatalities per 100,000 people between China and other countries, and describing China’s strategic routes toward Vision Zero.