A Better Dynamic Electronic Bus Stop Sign Based on the Upcoming Order of Buses for Easier Boarding

Author(s):  
Chatsarun Aruntanavong ◽  
Nan-Ching Tai
Keyword(s):  
Bus Stop ◽  
1978 ◽  
Vol 104 (3) ◽  
pp. 267-278
Author(s):  
Mamdouh M. Bakr ◽  
Richard K. Robinson
Keyword(s):  
Bus Stop ◽  

Author(s):  
Brittany N. Campbell ◽  
John D. Smith ◽  
Wassim G. Najm
Keyword(s):  

Author(s):  
Hu Zhao ◽  
Shumin Feng ◽  
Yusheng Ci

Sudden passenger demand at a bus stop can lead to numerous passengers gathering at the stop, which can affect bus system operation. Bus system operators often deal with this problem by adopting peer-to-peer service, where empty buses are added to the fleet and dispatched directly to the stop where passengers are gathered (PG-stop). However, with this strategy, passengers at the PG-stop have a long waiting time to board a bus. Thus, this paper proposes a novel mathematical programming model to reduce the passenger waiting time at a bus stop. A more complete stop-skipping model that including four cases for passengers’ waiting time at bus stops is proposed in this study. The stop-skipping decision and fleet size are modeled as a dynamic program to obtain the optimal strategy that minimizes the passenger waiting time, and the optimization model is solved with an improved ant colony algorithm. The proposed strategy was implemented on a bus line in Harbin, China. The results show that, during the evacuation, using the stop-skipping strategy not only reduced the total waiting time for passengers but also decreased the proportion of passengers with a long waiting time (>6 min) at the stops. Compared with the habitual and peer-to-peer service strategies, the total waiting time for passengers is reduced by 31% and 23%, respectively. Additionally, the proportion of passengers with longer waiting time dropped to 43.19% by adopting the stop-skipping strategy, compared with 72.68% with the habitual strategy and 47.5% with the peer-to-peer service strategy.


Author(s):  
Yingfeng (Eric) Li ◽  
Haiyan Hao ◽  
Ronald B. Gibbons ◽  
Alejandra Medina

Even though drivers disregarding a stop sign is widely considered a major contributing factor for crashes at unsignalized intersections, an equally important problem that leads to severe crashes at such locations is misjudgment of gaps. This paper presents the results of an effort to fully understand gap acceptance behavior at unsignalized intersections using SHPR2 Naturalistic Driving Study data. The paper focuses on the findings of two research activities: the identification of critical gaps for common traffic/roadway scenarios at unsignalized intersections, and the investigation of significant factors affecting driver gap acceptance behaviors at such intersections. The study used multiple statistical and machine learning methods, allowing a comprehensive understanding of gap acceptance behavior while demonstrating the advantages of each method. Overall, the study showed an average critical gap of 5.25 s for right-turn and 6.19 s for left-turn movements. Although a variety of factors affected gap acceptance behaviors, gap size, wait time, major-road traffic volume, and how frequently the driver drives annually were examples of the most significant.


Author(s):  
Luca Bravi ◽  
Luca Kubin ◽  
Stefano Caprasecca ◽  
Douglas Coimbra de Andrade ◽  
Matteo Simoncini ◽  
...  
Keyword(s):  

Author(s):  
Lele Zhang ◽  
Jiangyan Huang ◽  
Zhiyuan Liu ◽  
Hai L. Vu

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