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Driving with knowledge from the physical world

Jing Yuan, Yu Zheng, Xing Xie, Guangzhong Sun
2011 Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining - KDD '11  
As a result, our service accurately estimates the travel time of a route for a user; hence finding the fastest route customized for the user.  ...  Using this model, our system predicts the traffic conditions of a future time (when the computed route is actually driven) and performs a self-adaptive driving direction service for a particular user.  ...  Therefore, different from existing methods [14] [22] regarding the travel time of an edge as a single-valued function based on time of day, we regard a landmark edge's travel time as a set of distributions  ... 
doi:10.1145/2020408.2020462 dblp:conf/kdd/YuanZXS11 fatcat:gsm75aexobdxzhcm3xosb6lbjy

Bus arrival time prediction algorithm based on Markov chain
Алгоритм прогнозирования моментов времени прибытия городских пассажирских автобусов на основе Марковских цепей

Yuan Tian, Harbin Institute of Technology, Aleksandr Rakhmangulov, Dmitri Muravev, Siqing Wang, Nosov Magnitogorsk State Technical University, Shanghai Jiao Tong University, Harbin Institute of Technology
2018 Modern Problems of Russian Transport Complex  
Conclusion Based on the operation characteristics of bus vehicles, a Markov chain based algorithm is proposed to predict internal travel time between bus stops and bus arrive time.  ...  , that is, the basic travel time prediction algorithm based on Markov chain, and the concrete prediction algorithm steps are as follows. 1.  ... 
doi:10.18503/2222-9396-2018-8-2-29-37 fatcat:mawgt2kqsfbvhd4bvjjjochw4u

On the estimation of arterial route travel time distribution with Markov chains

Mohsen Ramezani, Nikolas Geroliminis
2012 Transportation Research Part B: Methodological  
We then compute the transition probabilities and link partial travel time distributions to obtain the arterial route travel time distribution.  ...  Specifically, we focus on the estimation of probability distribution of arterial route travel time, which contains more information regarding arterial performance measurements and travel time reliability  ...  The developed model is based on Markov chain to address both the traffic progression and correlation between links.  ... 
doi:10.1016/j.trb.2012.08.004 fatcat:5e6qgrbswrbrzabqes6ey2yux4

Driving cycle prediction model based on bus route features

Denggao Huang, Hui Xie, Hongjie Ma, Qiang Sun
2017 Transportation Research Part D: Transport and Environment  
To conveniently predict 9 representative driving cycles of special bus routes, this paper proposed a prediction model based on bus route 10 features, which supports bus optimization.  ...  driving conditions, and, 8 therefore, it is critical to predict the driving cycles based on the route conditions.  ...  The iterative Markov chain is a method for driving cycle profile generation based on the 117 inter-station driving characteristics and the transmission matrices.  ... 
doi:10.1016/j.trd.2017.04.038 fatcat:o6jhp5arpvhmzknmvxb6ygxu7m

Adaptive Driving Cycles of EVs for Reducing Energy Consumption

Iwona Komorska, Andrzej Puchalski, Andrzej Niewczas, Marcin Ślęzak, Tomasz Szczepański
2021 Energies  
A novel distance-based adaptive driving cycle method was developed. The proposed algorithm uses the segmentation and iterative synthesis procedures of Markov chains.  ...  A driving cycle is a time series of a vehicle's speed, reflecting its movement in real road conditions.  ...  Markov Chain Method A Markov chain is the process wherein computation of the random variable future value is based on the current value, irrespective of the previous value.  ... 
doi:10.3390/en14092592 doaj:5495e265575846d1a57f7dd68a072320 fatcat:y6viz7miwrfk5avcdbsi6jwp5a

A Stochastic Approach Towards Travel Route Optimization and Recommendation based on Users Constraints using Markov Chain

Shabir Ahmad, Israr Ullah, Faisal Mehmood, Muhammad Fayaz, Dohyeun Kim
2019 IEEE Access  
We apply a Markov chain model to predict the popularity of different places on the short-and long-term bases. The popularity index alongside user constraints is provided to find optimal routes.  ...  This paper aims to design and implement a novel application to recommend an optimal travel route based on user constraints.  ...  In [32] - [34] , Markov Chain is used for arterial route travel time distribution and road congestion prediction.  ... 
doi:10.1109/access.2019.2926675 fatcat:5g3muhnxjnc5fkrzt2lzhdkv2y

Knowledge Graph-Based Enhanced Transformer for Metro Individual Travel Destination Prediction

Hainan Chi, Boyue Wang, Qibin Ge, Guangyu Huo, Yanming Shen
2022 Journal of Advanced Transportation  
To solve these problems, this paper proposes a knowledge graph-based enhanced Transformer method (KG-Trans) for the metro individual travel destination prediction task (MITD-Pre), which contains three  ...  The experimental results show that the proposed method obtains a higher destination prediction accuracy than the previous individual travel destination prediction methods.  ...  as follows: (i) An individual travel KG is constructed, and we propose a novel individual travel destination prediction method based on such KG, which aims to accurately analyze the individual travel  ... 
doi:10.1155/2022/8030690 fatcat:vi5ub4tmpzh2nf7ecqkz72csrm

An Efficient Traffic Analysis and Optimization on the Dynamic Network Using Two Stage Routing Algorithm

A. Keerthika, K. Poonkavithai
2015 International Journal of Future Generation Communication and Networking  
This paper address these limitation, proposes two stage routing algorithm and weight propagation model to predict the cost of an arbitrary path on road network and accurately detects the traffic environment  ...  Now-a-days the transportation network traffic plays a vital role in the society. People are focusing on arriving at our destination as quickly as possible.  ...  T-Drive [11] models time-dependent travel time distributions on road segments using sets of histograms and enables the inference of future travel times using Markov chains [14] .  ... 
doi:10.14257/ijfgcn.2015.8.1.27 fatcat:s6ug5ahqpbh7fpu4cqlk42osqu

MATSim as a Monte-Carlo Engine [chapter]

Gunnar Flötteröd
2016 The Multi-Agent Transport Simulation MATSim  
A simulation of this model then draws one or more realizations (route choices) from this distribution. One always needs a model before one can simulate.  ...  The network supply model predicts these network conditions using a certain travel behavior chosen by all travelers in the system.  ...  To obtain a Markov chain representation of Algorithm 48.1, one needs to specify (i) what variables in MATSim represent the states of that chain and (ii) what transition distribution underlies the MATSim  ... 
doi:10.5334/baw.48 fatcat:vpsqevtgkvbp7cin7dzxr52gsy

Synthesis and Feature Selection-Supported Validation of Multidimensional Driving Cycles

Jakov Topić, Branimir Škugor, Joško Deur
2021 Sustainability  
First, a Markov chain model is established based on velocity, acceleration, road slope and road slope time derivative states.  ...  Next, a large set of synthetic driving cycles is generated by using a corresponding 8D transition probability matrix, which is implemented in a sparse form based on a dictionary of keys to improve computational  ...  Markov Chain-Based Synthesis Method A Markov chain consists of a set of transitions determined by a probability distribution that satisfies the Markov property, where the transition probability distributions  ... 
doi:10.3390/su13094704 doaj:1be296911422444eb8f358b116d2e009 fatcat:spa4drfdz5b4xkxtogupj3k3n4

A Novel Markov Model for Near-Term Railway Delay Prediction [article]

Jin Xu, Weiqi Wang, Zheming Gao, Haochen Luo, Qian Wu
2022 arXiv   pre-print
We first develop a chi-square test to show that the delay evolution over stations follows a first-order Markov chain. We then propose a delay prediction model based on non-homogeneous Markov chains.  ...  The Markov chain model we propose also shows to be better than other widely-used time series models with respect to both interpretability and prediction accuracy.  ...  The results show that the delays over stations of the same train follow a first-order Markov chain. • We develop a Gaussian-kernel-based method to recover the transition matrices for the Markov chain model  ... 
arXiv:2205.10682v1 fatcat:p2sdduwjazh55jk6kzemzl7vry

Spatial and temporal modelling of tourist movements using Semi-Markov processes

Jianhong (Cecilia) Xia, Panlop Zeephongsekul, David Packer
2011 Tourism Management  
Semi-Markov processes have a Markov chain and a renewal process embedded within their structure, and as such, can be used to provide a wide variety of practical models.  ...  One of the outcomes of this approach is the introduction of a measure to assess the attractiveness of particular tourist attractions based on spatial and temporal interactions between the attractions.  ...  Therefore, by integrating time into the model, the Semi-Markov chain can be used to estimate time spent at attractions and travel time between attractions, as well as the probability of routes to travel  ... 
doi:10.1016/j.tourman.2010.07.009 fatcat:ds7wtyp7fngwdm6evt6gw55aqi

Estimating Urban Traffic Patterns through Probabilistic Interconnectivity of Road Network Junctions

Ed Manley, Tobias Preis
2015 PLoS ONE  
The paper presents an implementation of the modified MCMC approach for London, United Kingdom, building an MCMC model based on a dataset of nearly 700000 minicab routes.  ...  Using this dataset, the interconnectivity between road network junctions is extracted in the form of a Markov chain.  ...  The model demonstrates how future route choices can be predicted with a reasonably high accuracy based on the major junctions on the road network previously visited.  ... 
doi:10.1371/journal.pone.0127095 pmid:26009884 pmcid:PMC4444350 fatcat:gs2ofwamy5hrnbyujiqlvtkqdu

Travel time estimation for ambulances using Bayesian data augmentation

Bradford S. Westgate, Dawn B. Woodard, David S. Matteson, Shane G. Henderson
2013 Annals of Applied Statistics  
We introduce new methods for estimating the distribution of travel times on each road segment in a city, using Global Positioning System (GPS) data recorded during ambulance trips.  ...  Estimates of ambulance travel times on road networks are critical for effective ambulance base placement and real-time ambulance dispatching.  ...  only the travel times, to improve mixing of the Markov chain.  ... 
doi:10.1214/13-aoas626 fatcat:rlxlqe35afhsvpn7w26lpzj3i4

The prediction of freeway traffic conditions for logistics systems

Wenke Wang, Jeng-Chung Chen, Yenchun Jim
2019 IEEE Access  
Therefore, this study used a discrete-time Markov chain and online traffic monitoring data to predict the probability of traffic congestion and identify the freeway bottlenecks.  ...  INDEX TERMS Discrete-time Markov chain, freeway traffic congestion, logistics management, short-term traffic prediction.  ...  METHOD A.  ... 
doi:10.1109/access.2019.2943187 fatcat:igo6a4q3izet3c4ytwxifudbry
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