Analyzing drivers' perceived service quality of variable message signs (VMS)

Recent advance in VMS technology has made it viable to ease traffic congestion and improve road traffic efficiency. However, the drivers’ low compliance with the posted information may limit its performance to ease traffic congestion and improve traffic safety. This paper explores drivers’ attitude to the service quality of VMS system resulted from the identified predominant influencing factors. A questionnaire is developed and used for surveying 9,600 drivers in Beijing, China. The collected data are analyzed with a multiple indicators and multiple causes (MIMIC) model considering different driver categories (e.g., private car driver, office car driver, taxi driver). The results show that the causal relationships between latent variables and socio-demographic characteristic is significant. Driving frequency, attitude towards contents of VMS, drivers’ decision-making and the effectiveness of VMS message can directly and indirectly affect driver’s perceived quality of service. The attitude towards formats of VMS indirectly affect their QoS resulting from the effectiveness of VMS message, while there is no indirect impact for taxi drivers. Besides, the drivers’ decision-making directly affects the perceived quality of service for private car drivers and office car drivers, but there is no impact for taxi drivers. The findings of this study can provide guidance and reference for urban authorities to perform the relevant actions required to meet user expectations.

Investigating factors influencing pedestrian injury severity at intersections

OBJECTIVE

Vehicle crashes that involve pedestrians at intersections have been reported occasionally. Pedestrian injury severity in these crashes is significantly related to driver and pedestrian attributes, vehicle characteristics, and the geometry of intersections. Identifying factors associated with pedestrian injury severity (PIS) is critical for reducing crashes and improving safety. For developing the proposed probit models, drivers involved in crashes are classified into 3 groups: young drivers (16 ≤ age ≤ 24), middle-aged drivers (25 ≤ age ≤ 64), and older drivers (age ≥ 65). This study determines that PIS is significantly but differently affected by these grouped drivers with different sets of explanatory variables.

METHODS

A total of 2,614 crash records (2011-2012) at intersections in Cook County, Illinois, were collected. An ordered probit modeling approach was employed to develop the proposed model and examine factors influencing PIS. The likelihood ratio test was used to assess model performance. Elasticity analysis was conducted to interpret the marginal effect of contributing factors on PIS associated with different driver groups by age.

RESULTS

The results show that 4 independent variables, including pedestrian age, vehicle type, point of first contact, and weather condition, significantly affect PIS at intersections for all drivers. Two additional independent variables (i.e., number of vehicles and traffic type) affect PIS for young and middle-aged drivers, and 2 other variables (i.e., divided type and hit-and-run related) are significant to PIS for both young and older drivers.

CONCLUSIONS

The independent variables significant to PIS at intersections for young, middle-aged, and older driver groups were identified and the marginal effect of each variable to the likelihood of PIS were assessed.

Predicting expressway crash frequency using a random effect negative binomial model: A case study in China

To investigate the relationship between crash frequency and potential influence factors, the accident data for events occurring on a 50km long expressway in China, including 567 crash records (2006-2008), were collected and analyzed. Both the fixed-length and the homogeneous longitudinal grade methods were applied to divide the study expressway section into segments. A negative binomial (NB) model and a random effect negative binomial (RENB) model were developed to predict crash frequency. The parameters of both models were determined using the maximum likelihood (ML) method, and the mixed stepwise procedure was applied to examine the significance of explanatory variables. Three explanatory variables, including longitudinal grade, road width, and ratio of longitudinal grade and curve radius (RGR), were found as significantly affecting crash frequency. The marginal effects of significant explanatory variables to the crash frequency were analyzed. The model performance was determined by the relative prediction error and the cumulative standardized residual. The results show that the RENB model outperforms the NB model. It was also found that the model performance with the fixed-length segment method is superior to that with the homogeneous longitudinal grade segment method.

Exploring factors contributing to crash injury severity on rural two-lane highways

OBJECTIVE

Crash injury results from complex interaction among factors related to at-fault driver's behavior, vehicle characteristics, and road conditions. Identifying the significance of these factors which affect crash injury severity is critical for improving traffic safety. A method was developed to explore the relationship based on crash data collected on rural two-lane highways in China.

METHODS

There were 673 crash records collected on rural two-lane highways in China. A partial proportional odds model was developed to examine factors influencing crash injury severity owing to its high ability to accommodate the ordered response nature of injury severity. An elasticity analysis was conducted to quantify the marginal effects of each contributing factor.

RESULTS

The results show that nine explanatory variables, including at-fault driver's age, at-fault driver having a license or not, alcohol usage, speeding, pedestrian involved, type of area, weather condition, pavement type, and collision type, significantly affect injury severity. In addition to alcohol usage and pedestrian involved, others violate the proportional odds assumption. At-fault driver's age of 25-39years, alcohol usage, speeding, pedestrian involved, pavement type of asphalt, and collision type of angle are found to be increased crash injury severity.

PRACTICAL APPLICATIONS

The developed logit model has demonstrated itself efficient in identifying the effect of contributing factors on the crash injury severity.

Investigating motorists' behaviors in response to supplementary traffic control devices at land surveying work sites

OBJECTIVE

Since land surveyors working alongside live traffic encounter unique safety challenges there is a great need for innovative and effective traffic control devices (TCDs) that alert motorists approaching short-term land surveying work sites. Unlike the volume of research that has been completed on traditional work zones, however, there is a limited amount of information that has been collected on how motorists respond to TCDs at land surveying work sites. This article aims to fill the void by investigating motorists' behaviors in response to the use of 2 supplementary TCDs at land surveying work sites: portable plastic rumble strips (PPRS) and warning lights.

METHOD

Extensive field tests were conducted at various land surveying work sites on 2-lane 2-way urban roadways in New Jersey. Scenarios with and without the use of the supplemental TCDs were designed. Motorists' behavior changes were then statistically examined by using surrogate safety measures including mean speed, speed variance, speed limit compliance, and braking action.

RESULTS

Statistical analyses showed that the traffic speed variations did not significantly increase when the selected supplemental TCD was used; rather, motorists significantly reduced their driving speed. When warning lights and PPRS were separately deployed at the land surveying work sites the average reduction in mean speed was 6.7 and 15.2 percent, respectively. The mean speed was reduced by 19.7 percent when both of these supplementary TCDs were used. Logistic regression models developed to examine the speeding and braking behavior also showed that motorists were more likely to comply with the speed limit and increase their braking rate when the selected TCDs were used.

CONCLUSION

The use of supplemental TCDs can greatly contribute to the changes in motorists' behaviors at surveying work sites. The changes in motorists' driving behaviors imply that the motorists reacted favorably to the deployed TCDs at the land-surveying work sites.