Abstract:The idea of corporate social responsibility has promoted bus operation agencies to rethink how to provide not only efficient but also environmentally friendly services for residents. A study on the potential of using an optimized design of skip-stop services, one of the essential operational strategies in practice, to reduce emissions is conducted in this paper. The underlying scheduling problem is formulated as a nonlinear programming problem with the primary objective of optimizing the total costs for both passengers and operating agencies, as well as with the secondary objective of minimizing bus emissions. A solution method is developed to solve the problem. A real-world case of Route 16 in Beijing is studied, in which the optimal scheduling strategy that maximizes the cost savings and environmental benefits is determined. The costs and emissions of the proposed scheduling strategy are compared with the optimal scheduling with skip-stop services without considering bus emissions. The results show that the proposed scheduling strategy outperforms the other operating strategy with respect to operational costs and bus emissions. A sensitivity study is then conducted to investigate the impact of the fleet size in operations and passenger demand on the effectiveness of the proposed stop-skipping strategy considering bus emissions.
Intense lane-changing maneuvers at weaving sections often cause traffic turbulence on expressways, especially in the presence of a concurrent medium exclusive bus lane (XBL) and general purpose lanes. Such intense lane-changing activity usually affects the operation and reduces the capacity of weaving sections in relation to their equivalent basic expressway segments. In this context, a study on the capacity model of weaving areas on an expressway with a median XBL is conducted based on the analysis of lane-change behaviors using gap acceptance theory. Two weaving sections on expressways with median XBL are selected as case studies to obtain the estimated capacity as well as the maximum traffic throughput under a certain bus saturation on the XBL. The results show that estimated capacity is larger than maximum traffic throughput because of low utilization rate of buses on the XBL, and capacity is significantly affected by weaving demand. Error measures based on the estimated and observed maximum traffic throughput are analyzed to verify the validity of the proposed model. A sensitivity analysis shows that, compared with the increase of on-ramp bus flow ratio, the increase of off-ramp bus flow ratio results in a more obvious trend of the reduction of capacity and maximum traffic throughput.
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