While extensive research efforts have been devoted to improve the motorcycle safety, the relationship between the rider behavior and the crash risk is still not well understood.The objective of this study is to evaluate how behavioral factors influence crash risk and to identify the most vulnerable group of motorcyclists. To explore the rider behavior, a questionnaire containing 61-items of impulsive sensation seeking, aggression, and risk-taking behavior was developed. By clustering the crash risk using the medoid portioning algorithm, the log-linear model relating the rider behavior to crash risk has been developed. Results show that crash-involved motorcyclists 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 is not found to be significant. Defining personality types from aggression and risk-taking behavior, “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 be more focused in the target group as well as those who employ motorcyclists for their delivery business

In this paper, a new analytical model is proposed to determine optimal frequency for urban bus transit under variable demand by explicitly considering the interaction between different vehicles in urban mixed traffic. The effect of road congestion on in-vehicle travel time associated with each mode is explicitly considered in the formulation of link performance function. The equilibrium flow of vehicle in mixed traffic and the passenger flow on the transit network are computed using multi-modal equilibrium assignment with respect to the frequency selected by Hooke-Jeeves algorithm; finally, the optimal frequency is found by repeating the process. A numerical example is given to illustrate the application of the model and algorithm. From the convergence test and sensitivity analysis, some important conclusions are drawn. The computational result proves that the proposed model is applicable in real aspects of bus network design in mixed traffic.

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.