An aggregate method to calibrate the reference point of cumulative prospect theory-based route choice model for urban transit network

The use of Cumulative Prospect Theory (CPT) in decision making related to transportation risk is still much debated. Mainly because of the travel and socio-economic characteristics of the traveller it possible for different responses to the specified Reference Point (RP) as well as the loss aversion. This difference can be seen from the value of Cumulative Prospect Theory parameters. Therefore, this paper will discuss about the determination of parameters CPT which affect public transportation mode choice model in the course of work trip activity. The reference point as an essential part of this study is determined based on the average travel time of commuter worker from South Tangerang City to Jakarta. Data obtained from stated preference survey, Feeder Busway/Busway and Commuter Line Jabodetabek as mode alternative and travel time attribute as a risk factor. The Binomial Logit model which has transformed utility distribution and probability with CPT and the Least Square Method to be obtained the parameters. Finally, some conclusions can be drawn that the CPT parameters produced by this study, have closed the range of value requirements in the CPT theory. So that the parameter value can be used to model the probability of mode choice with the risk of travel time in the study area.

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Route choice model based on cellular automata and cumulative prospect theory: Case analysis of transportation network in Sichuan-Tibet region

Journal of Intelligent & Fuzzy Systems ◽

10.3233/jifs-201578 ◽

2020 ◽

pp. 1-15

Author(s):

Junxiang Xu ◽

Jingni Guo ◽

Jin Zhang ◽

Weihua Liu ◽

Hui Ma

Keyword(s):

Cellular Automata ◽

Prospect Theory ◽

Choice Model ◽

Transportation Network ◽

Route Choice ◽

Research Abstract ◽

Cumulative Prospect Theory ◽

Reference Points ◽

Transportation Organization ◽

The Impact

In order to study the influence of travelers’ self-adaptive adjustment behavior on transportation network under the assumption of bounded rationality, using cellular automaton to discretize the selection model under the analytic paradigm in the existing research, abstract each cell into a traveler, and describe the traveler characteristics with finite rationality characteristics through the travel risk attitude and travel generalized cost budget. Cellular automata and cumulative prospect theory is used to establish the travel route choice model, giving the dynamic evolution process of different reference points for travelers and taking the actual regional transportation network of Sichuan Tibet region in China as the study object, analyzes the impact of bounded rational travel behavior on route choice. The model and algorithm proposed in our study can not only guide the transportation organization of Sichuan Tibet region, but also provide theoretical support for the implementation of regional transportation planning and traffic control scheme in the future.

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Dynamic Model Research of Departure Time and Route Choice Based on Prospect Theory

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.243-249.4418 ◽

2011 ◽

Vol 243-249 ◽

pp. 4418-4421

Author(s):

Zhi Yong Yang ◽

Gui Yun Yan

Keyword(s):

Prospect Theory ◽

Choice Model ◽

Weighting Function ◽

Route Choice ◽

Traffic Information ◽

Traveler Information ◽

Travel Choice ◽

Traveler Information Systems ◽

Model Research ◽

Departure Time

This paper takes commuters’ daily travel as research object to build model of travel choice which contains departure time and travel route based on Prospect Theory. Choosing the time of arriving destination as reference point, commuter will choose the time at which he/she can obtain the maximum value as departure time, then establishes choice model of departure time. Using Bayesian Theory to update and adjust route’s forecasting travel time in light of traffic information provided by Advanced Traveler Information Systems (ATIS) and travelers’ previous experience information. Gets decision weighting function after having analyzed traveler’s individual subjective probability which is about the possible result for route choice, then obtains the expression of travel route’s prospect value and gets route choice model. Finally, by designing a network to analyze the dynamic choice model, and achieves expected effect.

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