Amit Kumar Singh

This paper explores public bicycle choice behavior for urban travelers and potential travelers who may use public bicycle systems. Factors influencing public bicycle choice behavior and current public bicycle usage in China were analyzed. Then primary factors of public bicycle choice behavior among those using different travel modes were studied using the binary logistic model. Influential factors were divided into internal and external factors. High prediction accuracy of the proposed model shows that BLM can predict the public bicycle choice behavior of urban residents. Results show that travel distance, convenience of transferring to public transit, and cycling safety are the three main factors that determine whether private car owners would choose the public bicycles. For walkers, walking distance and red light waiting time are the main factors. For users of public transit, travel distance, walking distance to public transit transfer, and automobile exhaust are the three main influential factors.

Survival analysis is used to analyze site data to explore vehicles’ mandatory lane changing behaviors and related influential factors. The traffic data on the mandatory lane changing durations of vehicles were collected by an unmanned aerial vehicle (UAV) in a freeway maintenance construction area. A multiplicative hazard model of mandatory lane change was established using the semi-parametric method of survival analysis. Meanwhile, the lane change data has been analyzed by Cox regression analysis. The results show that about three quarters of vehicles’ MLC duration is less than 10 sec. There is no significant evidence showing that different vehicle types have an effect on the duration of mandatory lane changing. The cumulative survival rate of MLC duration the off-peak period has been found to be significantly lower than that in the peak period and transition period. As it turns out, the cumulative survival rate of vehicles’ MLC duration in the transition period is the highest.

Walking speed is an important parameter for signal timing and safety analysis at signalized intersections. Walking speed varies significantly at different location and over time, and need to be re-calibrated for safer and efficient intersection designs. This paper documents a study performed to analyze pedestrian’s speed characteristics at signalized intersections in new urban district communities. Field data were obtained through video camera at four typical 4-leg intersections in the high-tech metropolitan area of Xi’an, China. Statistical descriptions and the distribution fittings were conducted by Statistical Product and Service Solutions （SPSS）. Results shows that the pedestrian crossing speed characteristics are influenced by both the pedestrian’s own characteristics and an intersection's geometric and operational characteristics. Male and female walking speed distributions are all in line with the normal distribution, and the youth, middle-aged, and elderly pedestrians speed distributions follow log-normal distribution. The average walking speed varies significantly with the variance of the crosswalk lengths at the same intersection.