Optimizing bus stop locations for walking access
Stops-first design of a feeder route to enhance a residential plan
Bibliographic Data
| ID | 21247537 |
|---|---|
| Authors | John Taplin (0000-0002-7218-1950, The University of Western Australia, corresponding author), John HE Taplin (The University of Western Australia), Yuchao Sun (0000-0002-6749-6309, The University of Western Australia) |
| Year | 2020 |
| Volume | 47 |
| Issue | 7 |
| Pages | 1237-1259 |
| Publication date | 2020-09-01 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Environment and Planning B Urban Analytics and City Science (JOURNAL) |
| Journal identifiers | ISSN: 2399-8083 • E-ISSN: 2399-8091 |
| Publisher | SAGE Publications (PUBLISHER • US) |
| DOI | 10.1177/2399808318824108 |
| OpenAlex | W2914082641 |
| Language | EN |
| Citations received | 2 |
| References cited | 46 |
Feeder buses provide a small but important part of the public transport system by carrying people between residential areas and transport interchanges. A feeder bus to a train station planned in advance will attract new residents of a housing development to use the bus. The bus route can influence the location choice of a buyer concerned about access for children, the elderly or anyone not wishing to drive a car. Our bus route modelling starts with the bus stops – not the route – to be reached from each dwelling by the shortest possible walk. In demand terms, people locating close to bus stops are more likely to use the service than those choosing more distant locations, and the nearby residences have higher values. The stops-first application determines a feeder bus route to enhance an irregular residential plan covering an area of one square kilometre. The planned road and housing lot locations provide the data for calculating the access measure from each dwelling to each potential bus stop, the closest stop being used. A genetic algorithm tests potential bus stops to find demand maximizing locations, the propensity to use the bus being formulated as an exponential (increasing elasticity) function of walking distance. Then a ‘travelling salesman’ genetic algorithm finds the shortest route linking the stops, so that an efficient circuit route is generated for each alternative number of bus stops, ranging from 7 to 11. More stops not only give better access but also increase the route length, so that total accessibility must be assessed against route length. The distribution of walking distances shows most between 150 and 240 metres, with none more than 400 metres. The results indicate that planning policy should require prior design of a bus route to achieve good walking accessibility, so that residents become accustomed to the convenience of using the bus. This study shows that, at the planning stage, estimating a bi-objective model giving a Pareto front between accessibility and route length can reveal a policy compromise that shortens the route with little reduction in expected patronage
Business · Geography · Public transport · Transport engineering · Computer Science · Engineering · Smart Parking Systems Research · Transportation Planning and Optimization · Urban Transport and Accessibility
The Social Logic of Space
The sustainable mobility paradigm
Adapting principles of developmental biology and agent-based modelling for automated urban residential layout design
New evidence on walking distances to transit stops
Walking to the bus
Transit accessibility for commuters considering the demand elasticities of distance and transfer
Transit ridership forecasting at station level
Effective ways to grow urban bus markets – a synthesis of evidence
Bus stop, property price and land value tax
| Citations per year | 0.5 |
|---|---|
| Citation span | 2022 - 2023 (2) |
| Highly cited | No |