This paper presents a holistic approach in level crossing safety modelling through the use of Petri nets. A Petri net is capable of dealing with multiple sequences which involve hardware, software and human failures in complex systems. This paper begins with the motivation towards the new modelling approach assessing safety risks in a level crossing. Researches around the world related with level crossing safety risks were first reviewed and highlighted. The paper then presented the research methods, safety modelling and analysis used in the study. Π-tool, which is based on the Petri nets approach, was used to build the model. The model was tested at ten critical level crossing locations in South Australia. The first model was developed using the signal failure as the accident mechanism. Results show that the rate of potential accident occurrence at selected locations is very close to the actual rate of accidents. The Π-tool appears to be a suitable tool for assessing safety and performance at level crossings.
This study aims to evaluate the comprehensive safety programs that were launched around 1990 in Japan in terms of their effectiveness in reducing traffic fatalities. Traffic fatalities (hereinafter called “fatalities”) in Japan recorded by the National Police Agency (NPA) declined from 11,415 in 1992 to 5,744 in 2007. For this period, comprehensive traffic safety programs were carried out by police agencies, road authorities, automobile manufacturers and other organizations in Japan. Penalties for drunk-driving, vehicle speed, rate of seatbelt use, road infrastructure improvements and so on are adopted as performance indicators to evaluate effects of the countermeasures. The effects of each fatality-reduction countermeasure on the corresponding number of fatalities were estimated. The comprehensive nationwide traffic safety program was shown to be highly effective in reducing traffic fatalities. In particular, it could be inferred that increasing the rate of seatbelt use and vehicle speed reduction are the most effective.
This study intends to investigate how a society appreciates road safety and the factors that influence public willingness to pay (WTP) for a reduction in risk of road safety. For this purpose, the Discrete Choice modelling technique was employed to analyze WTP data collected through a Stated Preference Contingent Valuation experiment and to establish the WTP determinants of and the attitudes toward road safety. Accordingly, eight models were developed for car and motorcycle casualties by taking into account four severity classes of casualty: slight, serious but no permanent disability, serious with permanent disability, and fatal. The analysis shows that level of education and vehicle ownership have significant relationship with public WTP. It is also found that there exists a very strong correlation between past casualty experiences and WTP.
Intersection is one of the accident-prone locations. To avoid accidents at the intersection, it may be important for drivers to observe the flashing green and non-flashing red of pedestrian signals. In this paper, safety level at the signalized intersection having a pedestrian signal is evaluated using laboratory experiment with the driver as subject. This study is based on the assumption that observing the pedestrian signal enables drivers to anticipate change of the signal to yellow. This provides allowance time for the decision to proceed or to stop, thereby leading to improved safety at intersections. Result clearly shows that driver anticipation of a signal change to yellow by observing the pedestrian signal enables the driver of a vehicle to avoid the “dilemma zone”. This improves safety level at the intersection compared to the case where such information is not provided.
While extensive research efforts have been devoted to improve the motorcycle safety, the relationship between rider behaviors and the crash risk is still not well understood. The objective of this study is to evaluate how behavioral factors influence the crash risk and to identify the most vulnerable group of motorcyclists. To explore the rider behaviors, a questionnaire containing 61-items of impulsive sensation seeking, aggression, and risk-taking behaviors was developed. By clustering the crash risk using the medoid portioning algorithm, a log-linear model relating rider behaviors to the crash risk has been developed. Results show that motorcyclists who have been involved in a crash score higher in all three behavioral traits. Aggressive and high risk-taking motorcyclists are more likely to fall under the high vulnerable group while impulsive sensation seeking behavior is not found to be significant. Defining personality types from aggression and risk-taking behaviors, “Extrovert” and “Follower” personality type of motorcyclists are more prone to crashes. The findings of this study will be useful for road safety campaign planners to identify and place more focus on target group. The results may also be useful to those who employ motorcyclists for their delivery businesses.
Existing manuals do not provide clear specifications for the required crosswalk width under different pedestrian demand volumes and characteristics. However, optimizing crosswalk configurations including width is an important concern to improve the overall performance of signalized intersections. The objective of this paper is to develop a methodology for estimating minimum required crosswalk width at different pedestrian demand volumes considering bi-directional flow and different pedestrian age groups. The developed methodology is based on modeling total pedestrian platoon crossing time which consists of discharge and crossing times. Discharge time is modeled by using shockwave theory while crossing time is modeled by applying aerodynamic drag theory. The developed models are then calibrated for crosswalks with mainly elderly or pupil pedestrian platoons. A set of criteria based on pedestrian crossing speed is developed to identify the minimum required crosswalk width. Finally, different required crosswalk widths are proposed for different pedestrian demand volumes and directional split ratios considering the effects of pupil and elderly pedestrian platoons.
This paper aims to develop automatic incident detection models based on a genetic fuzzy logiccontroller (GFLC). Two approaches are used to overcome the problem that GFLC can not consider too many state variables simultaneously. The first approach is to partially select three variables from all available traffic information (nine variables) as state variables of four GFLC models. The second approach is to extract first three principal components from the original nine variables as state variables of GFLC model, namely the Components model. For comparison, artificial neural network (ANN) incident detection models are also developed. To investigate the applicability of the proposed models, three commonly used indices: detection rate (DR), false alarm rate (FAR) and mean time to detect (MTD) are used to measure their performances. The results show that the Components model outperforms the other incident detection models with DR
This paper applies the concept of price of anarchy to define a new index, namely, traffic incident management ratio (TIMR) for identifying appropriate roads to be installed with traffic incident management program (TIMP). TIMR is defined as the ratio between the expected total travel costs of the degradable transport networks without and with TIMP. The paper assumes user equilibrium (UE) represents the degradable network without TIMP, whereas the social optimum (SO) characterizes the degradable network with TIMP. The traffic incident management location (TIML) model is then proposed for assessing the critical value of link capacity degradation on each link (i.e. road segment) and identifying the critical links for an installation of TIMP. The critical links for the TIMP are ranked by the critical values of capacity degradations, which maximize the TIMR. The proposed model and solution algorithm were tested using two networks to illustrate the application of the proposed model.