Nearly half of electric biker (e-biker)-related crashes caused head injuries that could be preventable by wearing a helmet. This study proposes an integrated Theory Planned Behavior, Health Belief Model, and locus control framework to investigate the underlying psychological factors influencing helmet use intention using survey data in Shanghai. Structural equation model estimation multiple group analyses were conducted understand these heterogeneous impacting factors. motivation, perceived...

Ensuring the reliable operation of all nodes in a road network is often challenging due to influence managed resources and other dynamic factors. This study proposes method for identifying critical based on multi-attribute decision-making, aimed at enhancing traffic efficiency reliability. By utilizing flow data real-time ranking node criticality, an adaptive signal optimization approach was developed establish collaborative control signals. First, quantitative analysis conducted evaluate...

To evaluate the operation of an urban transportation system by accurately analyzing reliability a road network, with aim reducing substantial fluctuation travel time, method for dynamically estimating network time is proposed. First, definition given referring to theory: possibility that all travelers in reach their destination within predetermined time. The numerically expressed as probability ratio delay (RODT) less than certain value. Then, actual data are used prove RODT vehicles obeys...

To date, electric bikers’ (e-bikers’) red-light running (RLR) behavior is often viewed as one of the main contributors to e-bike-related accidents, especially for traffic scenarios with high e-bike ridership. In this paper, we aim understand e-bikers’ RLR based on structural equation modeling. Specifically, predictive utility theory planned (TPB), prototype willingness model (PWM), and their combined form, TPB-PWM model, used analyze behavior, a comparison analysis made. The analyses three...

Based on the ideas of new information priority principle and fractional-accumulation generating operator, in this paper we propose a novel weighted fractional GM(1,1) (WFGM(1,1)) prediction model. In model, original sequence is first transformed by using which involves two parameters. With special choices these parameters, proposed WFGM(1,1) model reduces to classical (FGM(1,1)) as well (NIPGM(1,1)) studied recently. Stability property detail. practice, quantum particle swarm optimization...

Along with the increasing popularity of autonomous vehicles (AVs), urban livability and public health will be enhanced due to ecofriendly issues: alleviated traffic congestion, lower car ownership, reduced transport emissions. However, some emerging issues, including safety, trust, privacy, reliability, underdeveloped legislation, liability, may deter user intentions adopt an AV. This study introduces extensive factor, playfulness, into technology acceptance model (TAM) quantify impacts...

This paper focuses on investigating electric bikers’ (e-bikers) crossing behavior and violations based survey data of 3,126 e-bikers collected at signalized intersections in Nantong, China. We first explore e-bikers’ characteristics late crossing, incomplete violating behaviors by frequency analysis duration distribution, examine a few influential factors for red-light running (RLR) behavior, including site type, length traffic signal countdown timers (TSCTs). E-bikers’ RLR is further...

Amid an aging workforce and labor shortages, this study investigates the key factors influencing construction workers’ safety compliance behavior (SCB). SCB is categorized into three distinct types: non-compliance behavior, general behavior. The compares analyzes differences in between new generation older of workers. By integrating framework with a multi-layer perceptron (MLP) model, research develops behavior–artificial neural network (SCB-ANN) model. An enhanced method for optimizing...

Evaluating the safety risk of rural roadsides is critical for achieving reasonable allocation a limited budget and avoiding excessive installation facilities. To assess when crash data are unavailable or missing, this study proposed Bayesian Network (BN) method that uses experts’ judgments on conditional probability different factors to evaluate roadsides. Eight were considered, including seven identified in literature new factor named access point density. validate effectiveness method,...

In this paper a Bayesian method is proposed to estimate dynamic origin–destination (O–D) demand. The can synthesize multiple sources of data collected by various sensors, including link counts, turning movements at intersections, flows, and travel times on partial paths. Time-dependent demand for each O–D pair departure time assumed satisfy the normal distribution. connections among field demands all are established their variance-covariance matrices. Given prior distribution demands,...

Along with the increasing number of electric vehicles (EVs), an urban transportation network a large EVs will come true in near future. Since many countries encourage due to their environmental-friendly benefits, environmental costs have attracted much attention recent years. In this paper, besides costs, we take into account issues stochastic user equilibrium (SUE), elastic demand (ED), and driving range network. We propose SUE ED (SUEED) problem consider these EVs. An SUEED model is...

The popularity of electric bicycles in China makes them a common transportation mode for people to commute and move around. However, with the increase traffic volumes both vehicles bicycles, urban safety congestion problems are rising due conflicts between these two modes. To regulate travel behavior, it is essential analyze choice route behaviors travelers. This study proposes combined modal split multiclass user equilibrium model formulated as complementarity problem (CP) simultaneously...

Understanding the red-light running (RLR) behavior of electric bikers (e-bikers) is crucial for enhancing their safety, as majority e-bike-related accidents can be attributed to such actions. Traditional analytical methods often struggle capture non-linear dynamics inherent in traffic violation behaviors, resulting underrepresentation research. In contrast, Artificial Neural Networks (ANNs) adeptly handle these relationships but suffer from limited interpretability. This study introduces an...

Identifying safety risk in rural roadsides is critical to reasonably allocated limited funds and avoid excessive installation of facilities. There still a lack abundant data for traffic accidents on roads China, so scholars have screened the roadside factors by means empirical qualitative methods. The existing assessment models are thus greatly restricted practical applications. To overcome above shortcomings, this paper first screens based DEMATEL ISM. Next, classification model established...

This paper aims to understand and predict electric bike (e-bike) riders' traffic rule violating intention accident proneness using self-report survey data of over 2,000 e-bike riders in Shanghai. An extension the theory planned behavior (TPB) is proposed for this purpose which integrated seven new psychological factors (moral norm, perceived risk, conformity tendency, self-identify, descriptive legal past behavior) alone with three basic variables (attitude, subjective behavioral control)...