scholarly journals The way ahead for London's bus priority at traffic signals

2008 ◽  
Vol 2 (3) ◽  
pp. 193 ◽  
Author(s):  
N.B. Hounsell ◽  
B.P. Shrestha ◽  
J.R. Head ◽  
S. Palmer ◽  
T. Bowen
Keyword(s):  
Traffic Signals ◽  
Bus Priority ◽  
The Way

Analysis of Cooperative Bus Priority at Traffic Signals

2020 ◽  
Vol 21 (5) ◽  
pp. 1929-1940 ◽  
Author(s):  
Marcin Seredynski ◽  
Georgios Laskaris ◽  
Francesco Viti
Keyword(s):  
Traffic Signals ◽  
Bus Priority

scholarly journals Using global positioning system for bus priority in London: traffic signals close to bus stops

2007 ◽  
Vol 1 (2) ◽  
pp. 131 ◽  
Author(s):  
N.B. Hounsell ◽  
B.P. Shrestha ◽  
F.N. McLeod ◽  
S. Palmer ◽  
T. Bowen ◽  
...  
Keyword(s):  
Global Positioning System ◽  
Traffic Signals ◽  
Positioning System ◽  
Bus Priority ◽  
Global Positioning ◽  
Bus Stops

A New Approach for Co-Operative Bus Priority at Traffic Signals

2012 ◽  
Vol 13 (1) ◽  
pp. 6-14 ◽  
Author(s):  
Nick Hounsell ◽  
Birendra Shrestha
Keyword(s):  
Traffic Signals ◽  
Bus Priority ◽  
New Approach

scholarly journals ACCIOUR: An Accident Detection and Life Saviour System using IoT

2020 ◽  
Vol 8 (5) ◽  
pp. 5012-5016
Keyword(s):  
Life Span ◽  
Short Duration ◽  
Traffic Signals ◽  
Present Condition ◽  
Font Size ◽  
Turn On ◽  
Line Spacing ◽  
Hospital Doctors ◽  
Accident Detection ◽  
The Way

At the end of the day, being alive becomes the topmost priority for anyone in their life span. We can usually see more road tragedies than any good things happening around us. There are many people who lose their precious lives after accidents due to no proper ambulance facility, no one to communicate about the accident to the hospitals or majorly due to getting stuck in the traffic of big cities. The ACCIOUR-IoT based system helps to overcome these problems. Initially, each vehicle will have a device which activates soon after an accident takes place and sends the location to the close ones and to the main server that holds the information of various nearby ambulances, and hence forwards the location to the ambulance. Ambulance on getting the information can turn on their devices that help the traffic signals along their route to know there’s emergency and hence to clear the traffic as much as possible by turning on their green lights immediately so that the patient is taken from the accident spot and later admitted to hospital within the short duration that is possible. On the way, the ambulance will take a quick check on the patient and send information regarding their present condition even before they reach the hospital so that the hospital doctors are aware of what kind of treatment that has to be provided to the patient who is on the way to their hospital. This system majorly challenges the methodology that is currently adopted and provides a better solution to overcome their limitations. Overall, ACCIOUR system is all about saving a precious life and the lives of many others who are indirectly connected to them through technology. spacing. Author Profile must be in Font Size 8, with single line spacing. Fore more details, please download TEMPLATE HELP FILE from the website.

scholarly journals Bus Priority at Traffic Signals—Evaluating Strategy Options

2003 ◽  
Vol 6 (3) ◽  
pp. 1-14 ◽  
Author(s):  
Fraser McLeod ◽  
Nick Hounsell
Keyword(s):  
Traffic Signals ◽  
Bus Priority

The Best Way to Access Gas Stations using Fuzzy Logic Controller in a Neutrosophic Environment

2020 ◽  
Vol 4 (1) ◽  
pp. 30-45
Author(s):  
Muhammad Naveed Jafar ◽  
Muhammad Saqlain ◽  
Aasia Mansoob ◽  
Asma Riffat
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Logic Controller ◽  
Traffic Signals ◽  
Soft Sets ◽  
Gas Stations ◽  
Linguistic Input ◽  
Gas Station ◽  
The Way

These days, Google Map is used to find any location and/or to define the route to any given place. Its accuracy is up to 30 meters but if neutrosophic numbers are used, it gives more accuracy. To check the implementation of neutrosophic numbers in Google Map, a system is developed based on Fuzzy Logic Controller (FLC) using neutrosophic numbers to find the gas station which is nearest, less parking car units and with few traffic signals on the way. In this way, it takes less time to reach the available gas station. This system enables the driver to find a fuel station with more accuracy. We took five linguistic inputs including distance, gas availability, parking car unit, amount of gas, and the number of traffic signals to get one output, that is, time. We assigned different neutrosophic soft sets to each linguistic input. FLC inference was designed using 108 rules based on if-then statements to select time to reach the gas station. The results were verified by MATLAB’s Fuzzy Logic Toolbox.

Method for Assessing Bus Delay in Mixed Traffic to Identify Transit Priority Improvement Locations in Cambridge, Massachusetts

2015 ◽  
Vol 2533 (1) ◽  
pp. 60-67 ◽  
Author(s):  
Jeffrey L. Rosenblum ◽  
Duncan W. Allen ◽  
Tegin L. Bennett ◽  
Ritesh K. Warade ◽  
Cleo M. Stoughton
Keyword(s):  
Traffic Signals ◽  
Bus Priority ◽  
Urban Transit ◽  
Bus Delay ◽  
Transit Services ◽  
Vehicle Delay ◽  
Site Field ◽  
Operating Space ◽  
Composite Rating ◽  
The City

Urban transit services face a number of challenges from space constraints, congestion, and delays, among other issues. Implementing bus priority at traffic signals or providing exclusive operating space for buses can increase the attractiveness of taking the bus and thereby encourage ridership. The City of Cambridge, Massachusetts, was looking to pilot such interventions to demonstrate benefits of bus ridership, but needed a prioritized list of route segments with the largest levels of excess travel time to do so. Three metrics were used to evaluate delay: vehicle delay, overall passenger delay, and system reliability. These three metrics were combined into a single composite rating system for each segment and used to identify route segments along which buses experienced the most delay. The City of Cambridge analyzed high-ridership bus routes with automatic passenger counter data to identify segments along the route where buses experienced substantial delay. The next step for this project is to conduct an on-site field visit of targeted segments to develop potential bus prioritization proposals for each. This paper outlines the method developed to calculate bus delay by segment and presents results for one route analyzed.

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