scholarly journals A hybrid gravity and route choice model to assess vector traffic in large-scale road networks

2020 ◽  
Vol 7 (5) ◽  
pp. 191858
Author(s):  
S. M. Fischer ◽  
M. Beck ◽  
L.-M. Herborg ◽  
M. A. Lewis
Keyword(s):  
Large Scale ◽  
Road Traffic ◽  
Choice Model ◽  
Route Choice ◽  
Gravity Models ◽  
Sampling Effort ◽  
Long Distance ◽  
General Terms ◽  
Rigorous Model ◽  
Stochastic Gravity

Human traffic along roads can be a major vector for infectious diseases and invasive species. Though most road traffic is local, a small number of long-distance trips can suffice to move an invasion or disease front forward. Therefore, understanding how many agents travel over long distances and which routes they choose is key to successful management of diseases and invasions. Stochastic gravity models have been used to estimate the distribution of trips between origins and destinations of agents. However, in large-scale systems, it is hard to collect the data required to fit these models, as the number of long-distance travellers is small, and origins and destinations can have multiple access points. Therefore, gravity models often provide only relative measures of the agent flow. Furthermore, gravity models yield no insights into which roads agents use. We resolve these issues by combining a stochastic gravity model with a stochastic route choice model. Our hybrid model can be fitted to survey data collected at roads that are used by many long-distance travellers. This decreases the sampling effort, allows us to obtain absolute predictions of both vector pressure and pathways, and permits rigorous model validation. After introducing our approach in general terms, we demonstrate its benefits by applying it to the potential invasion of zebra and quagga mussels ( Dreissena spp.) to the Canadian province British Columbia. The model yields an R 2 -value of 0.73 for variance-corrected agent counts at survey locations.

Dynamic Route Choice Model of Large-Scale Traffic Network

1997 ◽  
Vol 123 (4) ◽  
pp. 276-282 ◽  
Author(s):  
David E. Boyce ◽  
Der-Horng Lee ◽  
Bruce N. Janson ◽  
Stanislaw Berka
Keyword(s):  
Large Scale ◽  
Choice Model ◽  
Route Choice ◽  
Traffic Network ◽  
Dynamic Route

scholarly journals A bounded path size route choice model excluding unrealistic routes: Formulation and estimation from a large-scale GPS study

2021 ◽  
pp. 1-59
Author(s):  
Lawrence Christopher Duncan ◽  
David Paul Watling ◽  
Richard Dominic Connors ◽  
Thomas Kjær Rasmussen ◽  
Otto Anker Nielsen
Keyword(s):  
Large Scale ◽  
Choice Model ◽  
Route Choice

Taxi Driver's Route Choice Behavior Analysis Based on Floating Car Data

2013 ◽  
Vol 361-363 ◽  
pp. 2036-2039 ◽  
Author(s):  
En Jian Yao ◽  
Long Pan ◽  
Yang Yang ◽  
Yong Sheng Zhang
Keyword(s):  
Behavior Analysis ◽  
Choice Behavior ◽  
Road Traffic ◽  
Choice Model ◽  
Route Choice ◽  
Map Matching ◽  
Taxi Drivers ◽  
Floating Car Data ◽  
Route Choice Behavior ◽  
Minor Road

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.

Long-Distance, Multimodal Freight in a Continental Transportation Model

2018 ◽  
Vol 2672 (44) ◽  
pp. 103-113
Author(s):  
Klaus Noekel ◽  
Ian Williams ◽  
Davide Fiorello
Keyword(s):  
Large Scale ◽  
Channel Model ◽  
Choice Model ◽  
Distribution Channel ◽  
Destination Choice ◽  
Logistic Distribution ◽  
Band Model ◽  
Distribution Centers ◽  
Long Distance ◽  
Production And Consumption

This paper proposes a model of long-distance freight traffic that is suitable for transportation models covering very large areas. Three challenges are discussed in turn. First, the geographic distribution of trips not only depends on locations of production and consumption, but also on the choice between alternative logistic distribution chains and the locations of intermediate distribution centers. Second, any stage of the distribution chain may combine several modes into a multi-leg transport. Third, the large scale of the model leads to large zones, implying a significant share of intrazonal traffic. The proposed approach adapts the four-stage model by generalizing destination choice into a distribution channel model and by introducing a mode sequence choice model for multimodal transport. A simplified distance band model is applied to intrazonal traffic.

scholarly journals A Route Choice Model for Capturing Driver Preferences When Driving Electric and Conventional Vehicles

2020 ◽  
Vol 12 (3) ◽  
pp. 1149 ◽  
Author(s):  
Anders F. Jensen ◽  
Thomas K. Rasmussen ◽  
Carlo G. Prato
Keyword(s):  
Large Scale ◽  
Fossil Fuels ◽  
Choice Model ◽  
Combustion Engine ◽  
Route Choice ◽  
Transport Planning ◽  
Routing Problem ◽  
Vehicle Type ◽  
Route Choice Behavior ◽  
Planning Models

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.

scholarly journals META-ANALYSIS OF CHOICE SET GENERATION EFFECTS ON ROUTE CHOICE MODEL ESTIMATES AND PREDICTIONS

Transport ◽  
2012 ◽  
Vol 27 (3) ◽  
pp. 286-298 ◽  
Author(s):  
Carlo Giacomo Prato
Keyword(s):  
Large Scale ◽  
Choice Model ◽  
Meta Analysis ◽  
Route Choice ◽  
Behavior Modeling ◽  
Path Generation ◽  
Choice Sets ◽  
True Model ◽  
Choice Set Generation ◽  
Choice Set

Large scale applications of behaviorally realistic transport models pose several challenges to transport modelers on both the demand and the supply sides. On the supply side, path-based solutions to the user assignment equilibrium problem help modelers in enhancing the route choice behavior modeling, but require them to generate choice sets by selecting a path generation technique and its parameters according to personal judgments. This paper proposes a methodology and an experimental setting to provide general indications about objective judgments for an effective route choice set generation. Initially, path generation techniques are implemented within a synthetic network to generate possible subjective choice sets considered by travelers. Next, ‘true model estimates’ and ‘postulated predicted routes’ are assumed from the simulation of a route choice model. Then, objective choice sets are applied for model estimation and results are compared to the ‘true model estimates’. Last, predictions from the simulation of models estimated with objective choice sets are compared to the ‘postulated predicted routes’. A meta-analytical approach allows synthesizing the effect of judgments for the implementation of path generation techniques, since a large number of models generate a large amount of results that are otherwise difficult to summarize and to process. Meta-analysis estimates suggest that transport modelers should implement stochastic path generation techniques with average variance of its distribution parameters and correction for unequal sampling probabilities of the alternative routes in order to obtain satisfactory results in terms of coverage of ‘postulated chosen routes’, reproduction of ‘true model estimates’ and prediction of ‘postulated predicted routes’.

scholarly journals Modeling Stochastic Route Choice Behaviors with Equivalent Impedance

2015 ◽  
Vol 2015 ◽  
pp. 1-10
Author(s):  
Jun Li ◽  
Yulin Huang ◽  
Xinjun Lai
Keyword(s):  
Large Scale ◽  
Choice Model ◽  
Route Choice ◽  
Multinomial Logit Model ◽  
Closed Form Expression ◽  
Travel Costs ◽  
Scale Parameters ◽  
Equivalent Impedance ◽  
Proposed Model ◽  
Large Scale Networks

A Logit-based route choice model is proposed to address the overlapping and scaling problems in the traditional multinomial Logit model. The nonoverlapping links are defined as a subnetwork, and its equivalent impedance is explicitly calculated in order to simply network analyzing. The overlapping links are repeatedly merged into subnetworks with Logit-based equivalent travel costs. The choice set at each intersection comprises only the virtual equivalent route without overlapping. In order to capture heterogeneity in perception errors of different sizes of networks, different scale parameters are assigned to subnetworks and they are linked to the topological relationships to avoid estimation burden. The proposed model provides an alternative method to model the stochastic route choice behaviors without the overlapping and scaling problems, and it still maintains the simple and closed-form expression from the MNL model. A link-based loading algorithm based on Dial’s algorithm is proposed to obviate route enumeration and it is suitable to be applied on large-scale networks. Finally a comparison between the proposed model and other route choice models is given by numerical examples.

scholarly journals Target Tracking and 3D Trajectory Reconstruction Based on Multicamera Calibration

2022 ◽  
Vol 2022 ◽  
pp. 1-8
Author(s):  
Junfang Song ◽  
Yao Fan ◽  
Huansheng Song ◽  
Haili Zhao
Keyword(s):  
Large Scale ◽  
Road Traffic ◽  
Traffic Information ◽  
Long Distance ◽  
Trajectory Reconstruction ◽  
Automatic Target Detection ◽  
Operation Conditions ◽  
Vehicle Trajectories ◽  
The Cross ◽  
Vehicle Trajectory

In traffic scenarios, vehicle trajectories can provide almost all the dynamic information of moving vehicles. Analyzing the vehicle trajectory in the monitoring scene can grasp the dynamic road traffic information. Cross-camera association of vehicle trajectories in multiple cameras can break the isolation of target information between single cameras and obtain the overall road operation conditions in a large-scale video surveillance area, which helps road traffic managers to conduct traffic analysis, prediction, and control. Based on the framework of DBT automatic target detection, this paper proposes a cross-camera vehicle trajectory correlation matching method based on the Euclidean distance metric correlation of trajectory points. For the multitarget vehicle trajectory acquired in a single camera, we first perform 3D trajectory reconstruction based on the combined camera calibration in the overlapping area and then complete the similarity association between the cross-camera trajectories and the cross-camera trajectory update, and complete the trajectory transfer of the vehicle between adjacent cameras. Experiments show that the method in this paper can well solve the problem that the current tracking technology is difficult to match the vehicle trajectory under different cameras in complex traffic scenes and essentially achieves long-term and long-distance continuous tracking and trajectory acquisition of multiple targets across cameras.

Sign in / Sign up

Export Citation Format

Share Document