[Spatio-temporal Heterogeneity of Factors Influencing Transportation Carbon Emissions in Provinces Along the Belt and Road].

The administrative units of 17 provinces （autonomous regions and municipalities directly under the Central Government） along the "Belt and Road" were selected as basic spatial units to calculate the provincial traffic carbon emissions along the "Belt and Road" from 2000 to 2021. On the basis of analyzing the spatial and temporal characteristics of traffic carbon emissions by using the spatial autocorrelation method, the spatial and temporal heterogeneity of influencing factors of traffic carbon emissions was explored by combining a fixed-effect regression model and geographic detector. The results show that： ① The provincial traffic carbon emissions along the "Belt and Road" had significant spatial positive correlation, and the overall trend was upward.

Pre-location for temporary distribution station of urban emergency materials considering priority under COVID-19: A case study of Wuhan City, China.

In order to avoid the huge hidden dangers caused by emergencies, it is particularly vital to make a reasonable pre-location and layout of emergency logistics facilities. A multi-objective pre-location model of temporary distribution station for emergency materials was built, which considered the problems of information shortage and uncertain demand after the incident with minimum time, maximum time satisfaction, minimum delivery cost and psychological trauma to the masses. The priority of candidate points was solved by comprehensive evaluation methods, the nominal demand of served points was estimated by triangular fuzzy number theory (TFN), and the location model was solved by non-dominated sorting genetic algorithm.

Impact of Helmet-Wearing Policy on E-Bike Safety Riding Behavior: A Bivariate Ordered Probit Analysis in Ningbo, China.

At present, Chinese authorities are launching a campaign to convince riders of electric bicycles (e-bikes) and scooters to wear helmets. To explore the effectiveness of this new helmet policy on e-bike cycling behavior and improve existing e-bike management, this study investigates the related statistical distribution characteristics, such as demographic information, travel information, cycling behavior information and riders' subjective attitude information. The behavioral data of 1048 e-bike riders related to helmet policy were collected by a questionnaire survey in Ningbo, China.

Epidemic spread simulation in an area with a high-density crowd using a SEIR-based model.

Understanding the spread of infectious diseases is an extremely essential step to preventing them. Thus, correct modeling and simulation approaches are critical for elucidating the transmission of infectious diseases and improving the control of epidemics. The primary objective of this study is to simulate the spread of communicable diseases in an urban rail transit station.

The temporal stability of factors affecting driver injury severity in run-off-road crashes: A random parameters ordered probit model with heterogeneity in the means approach.

This study presents an effort to investigate the determinants of driver injury severity in run-off-road (ROR) crashes. In order to account for unobserved heterogeneity, a random parameter ordered probit with heterogeneity in the means approach is applied. The police-reported ROR crash data that occurred from 2014 to 2017 in the state of North Carolina is used.

Causation Analysis of Hazardous Material Road Transportation Accidents Based on the Ordered Logit Regression Model.

Understanding the influence factors and related causation of hazardous materials can improve hazardous materials drivers' safety awareness and help traffic professionals to develop effective countermeasures. This study investigates the statistical distribution characteristics, such as types of hazardous materials transportation accidents, driver properties, vehicle properties, environmental properties, road properties. In total, 343 data regarding hazardous materials accidents were collected from the chemical accident information network of China.

Design of a Network Optimization Platform for the Multivehicle Transportation of Hazardous Materials.

With economic development, the volume of hazardous materials is increasing, and the potential risks to human beings and the natural environment are expanding. Road transportation has become the main mode of transportation for hazardous materials. Because of the specific characteristics of hazardous materials, if an accident occurs in the transportation process, it often causes mass casualties, serious property and socioeconomic damage, and damage to the ecological environment.

Risk Riding Behaviors of Urban E-Bikes: A Literature Review.

In order to clearly understand the risky riding behaviors of electric bicycles (e-bikes) and analyze the riding characteristics, we review the research results of the e-bike risky riding behavior from three aspects: the characteristics and causes of e-bike accidents, the characteristics of users' traffic behavior, and the prevention and intervention of traffic accidents. The analysis results show that the existing research methods on risky riding behavior of e-bikes mainly involve questionnaire survey methods, structural equation models, and binary probability models. The illegal occupation of motor vehicle lanes, over-speed cycling, red-light running, and illegal manned and reverse cycling are the main risky riding behaviors seen with e-bikes.

Time-of-day Control Double-Order Optimization of Traffic Safety and Data-Driven Intersections.

This paper proposes a novel two-order optimization model of the division of time-of-day control segmented points of road intersection to address the limitations of the randomness of artificial experience, avoid the complex multi-factor division calculation, and optimize the traditional model over traffic safety and data-driven methods. For the first-order optimization-that is, deep optimization of the model input data-we first increase the dimension of traditional traffic flow data by data-driven and traffic safety methods, and develop a vector quantity to represent the size, direction, and time frequency with conflict point traffic of the total traffic flow at a certain intersection for a period by introducing a 3D vector of intersection traffic flow. Then, a time-series segmentation algorithm is used to recurse the distance amongst adjacent vectors to obtain the initial scheme of segmented points, and the segmentation points are finally divided by the combination of the preliminary scheme.

The association between musculoskeletal disorders and driver behaviors among professional drivers in China.

The main objective of this study is to explore correlations between the severity of musculoskeletal disorders (MSDs) and aberrant driving behaviors among professional taxi drivers. Questionnaires were administered to 162 taxi drivers in a Chinese city. Drivers with more severe MSDs reported more general and dangerous error behaviors and negative moods.

Path optimization of taxi carpooling.

The problem that passengers are hard to take taxis while empty driving rate is high widely exists under the traditional taxi operation mode. The implementation of taxi carpooling mode can alleviate the problem in a certain extent. The objective of this study is to optimize the taxi carpooling path.

Road screening and distribution route multi-objective robust optimization for hazardous materials based on neural network and genetic algorithm.

Route optimization of hazardous materials transportation is one of the basic steps in ensuring the safety of hazardous materials transportation. The optimization scheme may be a security risk if road screening is not completed before the distribution route is optimized. For road screening issues of hazardous materials transportation, a road screening algorithm of hazardous materials transportation is built based on genetic algorithm and Levenberg-Marquardt neural network (GA-LM-NN) by analyzing 15 attributes data of each road network section.

Investigating factors influencing drivers' speed selection behavior under reduced visibility conditions.

Objective: Driving speed is a major concern for driving safety under reduced visibility conditions. Many factors affect speed selection in low visibility, but few studies have been conducted examining drivers' characteristics, particularly in China. The present study aimed to investigate the correlation between drivers' demographic information, driving ability, and speed choice in low-visibility conditions using a sample of Chinese drivers.

Effects of mobile phone distraction on pedestrians' crossing behavior and visual attention allocation at a signalized intersection: An outdoor experimental study.

With the rapid growth in mobile phone use worldwide, traffic safety experts have begun to consider the impact of mobile phone distractions on pedestrian crossing safety. This study sought to investigate how mobile phone distractions (music distraction, phone conversation distraction and text distraction) affect the behavior of pedestrians while they are crossing the street. An outdoor-environment experiment was conducted among 28 college student pedestrians.

Distribution path robust optimization of electric vehicle with multiple distribution centers.

To identify electrical vehicle (EV) distribution paths with high robustness, insensitivity to uncertainty factors, and detailed road-by-road schemes, optimization of the distribution path problem of EV with multiple distribution centers and considering the charging facilities is necessary. With the minimum transport time as the goal, a robust optimization model of EV distribution path with adjustable robustness is established based on Bertsimas' theory of robust discrete optimization. An enhanced three-segment genetic algorithm is also developed to solve the model, such that the optimal distribution scheme initially contains all road-by-road path data using the three-segment mixed coding and decoding method.

Driving anger and its relationships with type A behavior patterns and trait anger: Differences between professional and non-professional drivers.

The present study examined the types of situations that caused Chinese professional and non-professional drivers to become angry and investigated the differences in driving-elicited anger, considering the influences of type A behavior pattern and trait anger between the two groups. The 20-item revised Driving Anger Scale (DAS) was used to assess a sample of 232 drivers (57% professional, 43% non-professional). The non-professional drivers reported significantly higher levels of anger than the professional drivers on the overall Driving Anger Scale (DAS) and the traffic obstructions and discourtesy subscales.