It is becoming increasingly difficult for Chinese citizens to access traditional public transport because of overcrowded community structures. Therefore, novel ideas are required to improve the transport system. In this respect, this study considers the design of a public transport scheduling model for a micro system. The model aims to minimize passenger waiting time and maximize number of passengers one bus carries, by simultaneously optimizing departure intervals and use of traditional and rapid buses. The model is superior to traditional models, as it analyzes the phenomena of vehicle overtaking, vehicle capacity limit, and passenger determination uncertainty. In addition, the model is a sophisticated nonlinear multi-objective optimization problem and contains more than one type of decision variable, therefore two composite algorithms, HPSO and GAPSO, are proposed, which are improvements of the Genetic Algorithm (GA) and Particle Swarm Optimization (PSO). These two algorithms are compared to the classical GA with respect to stability and effect, and the results show them to be strong in both respects. In addition, the simultaneous optimization method has evident advantages compared to single-method optimizations.

IEEE 802.11p/DSRC (Dedicated Short Range Communication) is considered to be a promising wireless communication standard for enhancing transportation safety and efficiency. However, IEEE 802.11p-based Vehicle-to-Vehicle (V2V) communication is still unreliable because of the complicating factors of high vehicle speed and complex radio environments. In this paper, we performed a data-based evaluation of V2V communication reliability, using real-world measurements in a typical urban expressway in Beijing. With respect to the characteristics of the urban expressway and our experimental data, we found road slope and traffic density to be the major environmental factors having a significant impact on the V2V communication’s Line-Of-Sight (LOS) conditions. On the basis of these two factors, we propose a fuzzy classification method for the LOS conditions, and separate the real-time communication environments into different LOS cases. For each LOS case, we quantify the metrics as received signal strength indication, packet delivery rate, and communication latency. The results reveal that the communication reliability in urban expressways is very unstable because of the changing LOS conditions. This study provides a useful reference for the IEEE 802.11p-based cooperative systems in urban expressways.

With rapid urbanization, subway systems are widely acknowledged as one of the best solutions to urban transportation problems. The operators or managers of subway systems should pay more attention to passenger’s perceptions of service quality to maintain its competitive position. Taking the traffic state, efficiency, and environmental impact into consideration, the concept of generalized comfort is proposed in this paper. Based on a nested logit model, the selection probability for each factor in a generalized comfort function can be estimated using a nested structure. A certain factor is considered to be more significant in a generalized comfort function than others, when the corresponding probability of this factor is higher in value. Using stated preference and revealed preference data about passenger travel behavior obtained from the Beijing subway, the parameters of generalized comfort function are estimated by maximum likelihood techniques.