On the impacts of bus stops near signalized intersections: Models of car and bus delays

Weihua Gu, Vikash V. Gayah, Michael J. Cassidy, Nathalie Saade

Research output: Journal article publicationJournal articleAcademic researchpeer-review

44 Citations (Scopus)

Abstract

Models are formulated to predict the added vehicle and person delays that can occur when a bus stop is located a short distance upstream or downstream of a signalized intersection. Included in the set of models are those that predict the expected delays that cars collectively incur when a bus blocks one of multiple lanes while loading and unloading passengers at the stop. Others in this set predict the expected added delays incurred by the bus due to car queues. Each model is consistent with the kinematic wave theory of highway traffic, as is confirmed through a battery of tests. And each accounts for the randomness in both, bus arrival times at a stop, and the durations that buses dwell there to serve passengers. Though the models are analytical in form, solutions come through iteration. Hence model applications are performed with the aid of a computer.The applications presented herein show that bus delays can often be shortened by placing the bus stop downstream of its neighboring signalized intersection, rather than upstream of it. In contrast, car delays are often shortened by placing the stop some distance upstream of the intersection, rather than downstream. We further show how exerting a measure of control on bus arrivals can further enhance these benefits to cars without further delaying the buses. The models are also used to assess the net person delays collectively incurred by car- and bus-travelers.
Original languageEnglish
Pages (from-to)123-140
Number of pages18
JournalTransportation Research Part B: Methodological
Volume68
DOIs
Publication statusPublished - 1 Oct 2014

Keywords

  • Bus delays
  • Bus holding
  • Car delays
  • Kinematic wave theory
  • Near-side and far-side bus stops

ASJC Scopus subject areas

  • Transportation
  • Management Science and Operations Research

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