scholarly journals Dynamic Evolution of Traveler’s Bounded-Rational Route Choice Behavior

2018 ◽  
Vol 2018 ◽  
pp. 1-12
Author(s):  
Xueqin Long ◽  
Liancai Zhang ◽  
Yuejiao Wang ◽  
Hongzhi Guan

Travelers’ route choice shows bounded-rationality because of different perceptions of route attributes. Based on the bounded-rationality, the paper proposes the dynamic evolution rules and route choice model, and simulation method is applied to study the evolution process and results. The model includes three parameters reflecting the bounded-rationality of travelers. First, simulation results show that the bounded-rationality affects the evolution process. The switching threshold or the perception deviance is larger, convergence rate is faster, and shorter time is needed to reach equilibrium state. Also, fewer perfect rational travelers will lead to similar results. Second, the system can reach equilibrium and the final equilibrium volume of every route is almost unaffected by bounded-rationality. The equilibrium volume of every route is an approximately fixed value under all simulation scenes. At last, it is found that equilibrium volume of every route obeys normal distribution. That is, bounded-rationality affects the equilibrium convergence rate, but volume equilibrium results will not be influenced.

Author(s):  
Tetsuro Hyodo ◽  
Norikazu Suzuki ◽  
Katsumi Takahashi

A new modeling method that describes bicycle route or destination choice behavior is presented. Although there are numerous bicycle users in Japan, the urban transportation planning process often treats bicycles and pedestrians as a single mode. Therefore, a methodology by which to evaluate and analyze bicycle demand needs to be developed. A bicycle route choice model that describes the relationship between route choice behavior and facility characteristics (e.g., road width or sidewalk) has been proposed. This model can be applied to the planning of bicycle road networks. The data from a bicycle trip survey conducted in Japan are used to study the characteristics of the model. The model is applied to study access railway station choice (destination choice). The model can produce a better fit than can a conventional model.


Author(s):  
Anthony Chen ◽  
Maya Tatineni ◽  
Der-Horng Lee ◽  
Hai Yang

The issue of planning for adequate capacity in transportation systems to accommodate growing traffic demand is becoming a serious problem. Recent research has introduced "capacity reliability" as a new network performance index. Capacity reliability is defined as the probability that a network can accommodate a certain volume of traffic demand at a required service level given variable arc capacities, while accounting for drivers' route choice behavior. Previous papers on this topic provide a comprehensive methodology for assessing capacity reliability along with extensive simulation results. However, an important issue that remains is what type of route choice model should be used to model driver behavior in estimating network capacity reliability. Three different route choice models (one deterministic and two stochastic models) are compared, and the effect of using each of these models on estimating network capacity reliability is examined.


2011 ◽  
Vol 97-98 ◽  
pp. 925-930
Author(s):  
Shi Xu Liu ◽  
Hong Zhi Guan

The influence of different traffic information on drivers’ day-to-day route choice behavior based on microscopic simulation is investigated. Firstly, it is assumed that drivers select routes in terms of drivers’ perceived travel time on routes. Consequently, the route choice model is developed. Then, updating the drivers’ perceived travel time on routes is modeled in three kinds of traffic information conditions respectively, which no information, releasing historical information and releasing predictive information. Finally, by setting a simple road network with two parallel paths, the drivers’ day-to-day route choice is simulated. The statistical characteristics of drivers’ behavior are computed. Considering user equilibrium as a yardstick, the effects of three kinds of traffic information are compared. The results show that the impacts of traffic information on drivers are related to the random level of driver’s route choice and reliance on the information. In addition, the road network cannot reach user equilibrium in three kinds of information. This research results can provide a useful reference for the application of traffic information system.


Author(s):  
Martin Stubenschrott ◽  
Thomas Matyus ◽  
Helmut Schrom-Feiertag ◽  
Christian Kogler ◽  
Stefan Seer

In recent years, pedestrian simulation has been a valuable tool for the quantitative assessment of egress performance in various environments during emergency evacuation. For a high level of realism, an evacuation simulation requires a behavioral model that takes into account behavioral aspects of real pedestrians. In many studies, however, it is assumed that simulated pedestrians have a global knowledge of the infrastructure and choose either a predefined or the shortest route. It is questionable whether this simplification provides realistic results. This study addresses the problem of human-like route-choice behavior for microscopic pedestrian simulations. A route-choice model is presented that considers two concepts: first, the modeling of infrastructure knowledge to represent the variations in the decision-making processes of pedestrians with different degrees of familiarity with the infrastructure (e.g., regular commuters versus first-time visitors). Second, for each pedestrian the internal preference for selecting a certain path can be calibrated to allow the choice for the fastest routes or the ones that are most convenient for the agent (e.g., by avoiding stairs). The approach here uses a hybrid route-choice behavior model composed of a graph-based macrolevel representation of the environment, which is augmented with local information to avoid obstacles and dense crowds in the vicinity. This method was applied with different parameter sets in an evacuation study of a multilevel subway station. The results show the impact of these parameters on evacuation times, use of infrastructure elements, and crowd density at specific locations.


2013 ◽  
Vol 361-363 ◽  
pp. 2036-2039 ◽  
Author(s):  
En Jian Yao ◽  
Long Pan ◽  
Yang Yang ◽  
Yong Sheng Zhang

Taxi drivers are viewed having more driving experience, being more familiar with road traffic condition, and in turn having more rational route choice behaviors than ordinary drivers. Using floating car data (FCD) of Beijing taxi in 2010, this study discusses the influence of road network conditions and traffic status to taxi drivers route choice behaviors. First, trip information is extracted from FCD using trip-identification method; Second, map matching and K-shortest paths are used to construct the trajectories and the sets of alternate routes, and route similarity evaluation is conducted to build the sample data of route choice behavior analysis; Finally, route choice model for taxi drivers based on Multinomial Logit (MNL) Model is estimated. The result shows that taxi drivers tend to choose the route which has faster driving speed, less frequency of left turns, more proportion of express way and less proportion of minor road, and increasing a left-turn or decreasing travel speed by 2.12km/h has the same effect on route choice utility. This study is expected to be helpful to establish map-matching algorithm of FCD, route guidance scheme and traffic assignment model.


Author(s):  
Winnie Daamen ◽  
Piet H. L. Bovy ◽  
Serge P. Hoogendoorn

In assessing the design of a public transfer station, it is important to be able to predict the routes taken by passengers. Most simulation tools use simple route choice models that take into account only the shortest walking distance or walking time between a passenger's origin and destination. To improve this type of route choice model, other factors affecting passenger route choice need to be identified. Also, the way these factors influence route choice behavior needs to be determined to indicate how each factor is valued. In this research, route choice data have been collected in two Dutch train stations by following passengers through the facility from their origins to their destinations. These data have been used to estimate extended route choice models. The focus is on the influences of level changes in walking routes on passenger route choice behavior. It appears that ways of bridging level changes (ramps, stairs, escalators) each have a significant and different impact on the attractiveness of a route to a traveler.


2020 ◽  
Vol 12 (3) ◽  
pp. 1149 ◽  
Author(s):  
Anders F. Jensen ◽  
Thomas K. Rasmussen ◽  
Carlo G. Prato

Battery Electric Vehicles (BEVs) play an important role in the needed transition away from fossil fuels and Internal Combustion Engine Vehicles (ICEVs). Although transport planning models and routing problem solutions exist for BEVs, the assumption that BEV drivers search for the shortest path while constraining energy consumption does not have any empirical basis. This study presents a study of actual route choice behavior of drivers from 107 Danish households participating in a large-scale experiment with BEVs and at the same time driving their ICEVs. GPS traces from 8968 BEV and 6678 ICEV routes were map matched to a detailed road network to construct observed routes, and a route choice model was specified and estimated to capture behavioral differences related to the vehicle type. The results reveal that drivers had a higher sensitivity to travel time and trip length when driving BEVs, and to route directness after receiving the BEV, regardless of vehicle type. The results suggest the need to revise the assumptions of transport planning models and routing problems for BEVs in order not to fail to predict what drivers will do by ignoring differences and similarities related to vehicle type.


2014 ◽  
Vol 2014 ◽  
pp. 1-6 ◽  
Author(s):  
Qian Li ◽  
Changxu Ji ◽  
Limin Jia ◽  
Yong Qin

In order to overcome the subjectivity of existing pedestrian route choice models, an alternative choice model is presented based on the utility equation. It is composed of several indirectly objective characteristic variables, including the height, length, and width of interlayer facilities; speed of automated facilities; and carry-on luggage. Considering the scene that pedestrians choose between the stairs or escalators, an extended binary logit model is developed. Calibration and validation of the model are accomplished by using the data collected in four typical passenger transfer stations in Beijing, China. The results show that the proposed model has an average accuracy of 86.56% in bidirection for predicting pedestrians’ behavior. An interesting phenomenon can be found that the length of facility has poorer impact than height on pedestrians’ route choice behavior. Some quantitative and irradiative conclusions have been illustrated on the relationship between the selection probability and the variables, which is expected to be valuable for extracting the implicit theoretical mechanism of passenger choice behavior.


Sign in / Sign up

Export Citation Format

Share Document