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The purpose of setting up variable guidance lanes is to ease the traffic pressure on lanes with more traffic under the condition of ensuring the traffic capacity of the intersection. This study proposes a bi-level model-interactive relationship between variable guidance lane design and signal control and carry out a case study for a road in Wuhan, China. The design plan for the goal, combined with the design plan of the variable guidance lane, optimizes the signal timing plan of the intersection. A real case is modeled in VISSIM to simulate the design scheme of variable guidance lanes to verify the reliability and effectiveness of the bi-level model. The results showed that the average vehicle delay at the intersection was reduced by 20.65% after the bi-level model was optimized. The average error between model calculation results and simulation results is 9.88%. Moreover, the influencing factors of the proposed model are also carried out. The results show that when the traffic flow is greater than 1,000 pcu/h, the optimization effect of the model is more significant. When the traffic capacity gradually increases, the average vehicle delay calculated by the model is smaller. The design scheme and signal timing scheme proposed by the bi-level model can ensure the overall traffic efficiency of the intersection, improve the traffic efficiency of the traffic-stressed lanes, and further promote the space-time resource utilization of the intersection, optimize the space-time resources of the road network, and provide a scientific basis and new ideas and methods. [ABSTRACT FROM AUTHOR]

This paper proposes an improved impedance function for roads with mixed traffic. It is known that only limited studies consider the impact of nonmotorized traffic on travel impedance of a road segment, and a comparison of the impedance considering nonmotorized traffic with the classic BPR function, which does not consider the former, is scarce. Most of the previous studies targeted road conditions in developed countries, where the presence of nonmotorized traffic is negligible, and therefore limited efforts have been invested to develop improved impedance function considering mixed traffic. To overcome this limitation, this paper develops an improved impedance function and carries out a case study for a road in the city of Wuhan, China. The improved impedance function explicitly considers the interaction between motorized and nonmotorized traffic. Taxi GPS data from the case study road is used to extract and analyze the travel time of the "probe vehicles" running through the sampled segment at any time during a sampling day. The capacity of the road segment is measured, and the traffic flow of motorized vehicles and nonmotorized vehicles on the segment is counted. Based on the above data, the classic BPR function and the improved one proposed in this paper are calibrated. After comparing and analyzing the observed road impedance based on both analytical and simulation results, the classic BPR function and the proposed impedance function, the proposed impedance function is found to be more accurate to simulate the observed road impedance, with the error reducing from 14.83 s with the classic BPR impedance function to 6.50 s with the improved function. The proposed impedance function possesses a simple structure and high flexibility, and the parameters calibrated in this paper can be applied to similar roads to provide more realistic impedance than the previous ones based on the classic BPR function. The calibrated improved impedance function's transferability to other similar roads is validated by applying it to another road and the results show that the percentage error between the predicted travel times and the observed ones is only 3.8%. [ABSTRACT FROM AUTHOR]

This paper presents the results of acase study on the causes and effects of typical service disruptions in aHigh-speed rail (HSR) system in China–Wuhan–Guangzhou High-speed railway (WH-GZ HSR). With acause-specific approach, seven delay causalities leading to primary delays (PDs) are identified, and the properties and consequences of each primary delay (PD) factor is derived. The comparison of candidate distributional forms shows that the Log-normal distribution model can approximate better the length of all identified PDs. For each PD cause, the distribution of delay duration is estimated and tuned. Next, cause-specific distributional models for PDs severity are discussed. The models for the number of affected trains are presented in the form of inverse regression models with specific domains. Then, comparing five different kinds of candidate models, the results show that the Cubic is the best to approximate the distributions of total-affected time. [ABSTRACT FROM AUTHOR]