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Introduction
In-vehicle driving monitoring technologies have the potential to enable young drivers to learn from self-assessment. However, their use is largely dependent on parental involvement.Method
A total of 79 interviews were conducted with young drivers and parents regarding this technology and its use. Most had the experience of having an in-vehicle data recorder installed in the vehicle driven by the young drivers. Parents and the young drivers expressed both appreciation as well as reservations about its potential as a means to enhance the driving safety of young drivers.Results
A surprising finding was that some parents did not check the feedback and said they relied on the young driver to do so. Main concerns related to privacy, parent-young driver relationship, self-esteem and confidence, constructive use of the feedback data, and the limitations of the documentation that can be done by the technology.Conclusions
Providing parents and young drivers with a support system and tools to discuss and utilize the feedback are underscored. Challenges include addressing the invasion of young drivers’ privacy and gender differences, and using the monitoring-capacity of the technology to enhance safe driving practices. Implications for programs to enhance communication and a dialogical approach between parents and young drivers are discussed. 相似文献Introduction
Generalized linear modeling (GLM), with the assumption of Poisson or negative binomial error structure, has been widely employed in road accident modeling. A number of explanatory variables related to traffic, road geometry, and environment that contribute to accident occurrence have been identified and accident prediction models have been proposed. The accident prediction models reported in literature largely employ the fixed parameter modeling approach, where the magnitude of influence of an explanatory variable is considered to be fixed for any observation in the population. Similar models have been proposed for Indian highways too, which include additional variables representing traffic composition. The mixed traffic on Indian highways comes with a lot of variability within, ranging from difference in vehicle types to variability in driver behavior. This could result in variability in the effect of explanatory variables on accidents across locations. Random parameter models, which can capture some of such variability, are expected to be more appropriate for the Indian situation.Method
The present study is an attempt to employ random parameter modeling for accident prediction on two-lane undivided rural highways in India. Three years of accident history, from nearly 200 km of highway segments, is used to calibrate and validate the models.Results
The results of the analysis suggest that the model coefficients for traffic volume, proportion of cars, motorized two-wheelers and trucks in traffic, and driveway density and horizontal and vertical curvatures are randomly distributed across locations.Conclusions
The paper is concluded with a discussion on modeling results and the limitations of the present study. 相似文献Methods: A cross-sectional study was used to interview 3,151 electric bike/moped riders in southern China. Electric bike/moped-related road traffic injuries that occurred from July 2014 to June 2015 were investigated. Data were collected by face-to-face interviews and analyzed between July 2015 and June 2017.
Results: The prevalence of electric bike/moped-related road traffic injuries among the investigated riders was 15.99%. Electric bike/moped-related road traffic injuries were significantly associated with category of electric bike (adjusted odds ratio [AOR] = 1.36, 95% confidence interval [CI], 1.01–1.82), self-reported confusion (AOR = 1.77, 95% CI, 1.13–2.78), history of crashes (AOR = 6.14, 95% CI, 4.68–8.07), running red lights (AOR = 3.57, 95% CI, 2.42–5.25), carrying children while riding (AOR = 1.96, 95% CI, 1.37–2.85), carrying adults while riding (AOR = 1.68, 95% CI, 1.23–2.28), riding in the motor lane (AOR = 2.42, 95% CI, 1.05–3.93), and riding in the wrong traffic direction (AOR = 1.63, 95% CI, 1.13–2.35). In over 77.58% of electric bike/moped-related road traffic crashes, riders were determined by the police to be responsible for the crash. Major crash-causing factors included violating traffic signals or signs, careless riding, speeding, and riding in the wrong lane.
Conclusion: Traffic safety related to electric bikes/moped is becoming more problematic with growing popularity compared with other 2-wheeled vehicles. Programs need to be developed to prevent electric bike/moped-related road traffic injuries in this emerging country. 相似文献
Method: The methodology has been designed for the transformation of a real system to small subgraphs that represent the maneuvers in roundabouts, approximated as roads and lanes of incorporation. Places within the roundabout have been located and defined as continuous places from their influence and visibility toward adjacent conditions. The transitions have been modeled by time and inhibitory arcs, which represent priorities and areas where drivers must pay attention. The created networks represent a faithful model of vehicle flow trajectories in the roundabouts.
Results: The methodology is applied to the same real road intersection. The case study is a recent transformation from roundabout to turbo roundabout. The roundabout network complexity is corroborated by a greater number of entries and exits that lead to each roundabout place (reflected in the maneuvers that can be performed) and a greater number of inhibiting arcs. In most of the turbo roundabout places, the driver’s only option is reduced to occupying next place. The possibility of choosing between several places supposes a greater trajectory intersection and an increased time for decision making. The only situation where the complexity is the same between both systems is when a vehicle accesses the inner lane of the roundabout from the left lane on a single-lane road. The main maneuvers causing accidents have been modeled and their solution in a turbo roundabout is presented.
Conclusions: The reduced complexity of the turbo roundabout is due to the strict limitations in lane changes, turning turbo roundabouts into a safer model: A lower number of possible movements that can be performed by drivers and a smaller number of trajectories with collision risk. Petri nets have proven to be perfectly applicable to the representation of traffic circular systems (such as roundabouts and turbo roundabouts) and to measure the complexity and security of the system. 相似文献