An agent-based approach to modelling driver route choice behaviour under the influence of real-time information

By Hussein Dia. 2002

361 citations recorded by the source corpus.

Subfields: Automotive Engineering, Control and Systems Engineering, Transportation

View Paper: https://www.semanticscholar.org/paper/216611dd04e6a9995ffd64f60bcc8f64a63a57ce

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Automotive Engineering

1. Franziska Klügl-Frohnmeyer
2. Ana Lúcia Cetertich Bazzan
3. Harry H. Cheng

In Control and Systems Engineering

1. Franziska Klügl-Frohnmeyer
2. Ana Lúcia Cetertich Bazzan
3. Harry H. Cheng
4. Ximing Cai

In Transportation

1. Eric Molin
2. Franziska Klügl-Frohnmeyer
3. Ana Lúcia Cetertich Bazzan
4. G. V. Wee
5. Caspar G. Chorus
6. Harry H. Cheng
7. J. De Vos
8. Fei-Yue Wang

Citations in the corpus

• A Review of the Applications of Agent Technology in Traffic and Transportation Systems (2010, background): “Personal agents for each individual traveler communicate with the driver and the system to provide optimal advice to the traveler and update stored traffic information in the system.”
• An agent‐based model of farmer decision‐making and water quality impacts at the watershed scale under markets for carbon allowances and a second‐generation biofuel crop (2011, background): “…literature, decision-making rules have been defined on the basis of empirical data from surveys or controlled experiments [Castella et al., 2005; Dia, 2002], heuristics [Kerridge et al., 2001; Epstein and Axtell, 1996], neural networks [Barr and Saraceno, 2005; LeBaron, 2001], and optimization…”
• An agent-based model to study market penetration of plug-in hybrid electric vehicles (2011, background): “ABMs have become increasingly popular in studies of transportation logistics and traffic flow (Dia, 2002; Henesey et al., 2005).”
• A review on agent-based technology for traffic and transportation (2013, methodology): “In Dia (2002), survey data gathered from commuters in a congested area of Brisbane (Australia) was used to analyse relevant factors using an econo-metric analysis.”
• Travel information as an instrument to change cardrivers’ travel choices: a literature review (2006, background): “The provision of predictive and quantitative information ("due to an accident, the expected delay on route A equals 25 minutes") is found to have more effect on choices than historic and qualitative information ("due to an accident, there are delays on route A") (Khattak et al., 1996; Dia, 2003; Jou”