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Data-Driven Multi-Agent Vehicle Routing in a Congested City

Alex Solter, Fuhua Lin, Dunwei Wen, Xiaokang Zhou
2021 Information  
These data are made available to all users, such that they may be able to learn and predict the effects of congestion for building a route adaptively.  ...  This method is further enhanced by combining the traffic information system data with previous routing experiences to determine the fastest route with less exploration.  ...  Acknowledgments: We acknowledge the support of the Natural Sciences and Engineering Research Council of Canada (NSERC). Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/info12110447 fatcat:ndvugsw3qbdb5h26qhcfls75xa

T-Drive: Enhancing Driving Directions with Taxi Drivers' Intelligence

Jing Yuan, Yu Zheng, Xing Xie, Guangzhong Sun
2013 IEEE Transactions on Knowledge and Data Engineering  
Then, a Variance-Entropy-Based Clustering approach is devised to estimate the distribution of travel time between two landmarks in different time slots.  ...  Based on this graph, we design a two-stage routing algorithm to compute the practically fastest and customized route for end users.  ...  the fastest route according to the estimated speeds.  ... 
doi:10.1109/tkde.2011.200 fatcat:xvfrse46sbhvtngysh4hjihec4

An Eco-Friendly Multimodal Route Guidance System for Urban Areas Using Multi-Agent Technology

Abdallah Namoun, Ali Tufail, Nikolay Mehandjiev, Ahmed Alrehaili, Javad Akhlaghinia, Evtim Peytchev
2021 Applied Sciences  
Our validation results demonstrate the effectiveness of personalized multimodal route guidance in inducing a positive travel behavior change and the ability of the agent-based route planning system to  ...  Commuters are supplied with multimodal routes that endeavor to reduce travel times and transport carbon footprint.  ...  Acknowledgments: We would like to acknowledge and thank the participants of the field trials in Nottingham (UK) and Sofia (Bulgaria) for taking part in this research.  ... 
doi:10.3390/app11052057 fatcat:n5haqzck6re57gegs66bse76oa

T-drive

Jing Yuan, Yu Zheng, Chengyang Zhang, Wenlei Xie, Xing Xie, Guangzhong Sun, Yan Huang
2010 Proceedings of the 18th SIGSPATIAL International Conference on Advances in Geographic Information Systems - GIS '10  
Then, a Variance-Entropy-Based Clustering approach is devised to estimate the distribution of travel time between two landmarks in different time slots.  ...  Based on this graph, we design a two-stage routing algorithm to compute the practically fastest route.  ...  For example, in Figure 11 (A), if we start at time = 0, the fastest route from to is → 3 → 4 → .  ... 
doi:10.1145/1869790.1869807 dblp:conf/gis/YuanZZXXSH10 fatcat:c6r5v6qwfbeo5aiowxs3ytmfju

Learning to Route via Theory-Guided Residual Network [article]

Chang Liu, Guanjie Zheng, Zhenhui Li
2021 arXiv   pre-print
To address these problems, we propose a theory-guided residual network model, where the theoretical part can emphasize the general principles for human routing decisions (e.g., fastest route), and the  ...  First, human routing decisions are determined by multiple factors, besides the common time and distance factor.  ...  Related Work Route Recommendation Route recommendation is the most relevant topic to our paper, which aims to recommend routes for a given origin and destination that can save time for travelers or mitigate  ... 
arXiv:2105.08279v2 fatcat:4chugk3uw5er3o7aczsgmezoju

Towards Green Driving: A Review of Efficient Driving Techniques

Maram Bani Younes
2022 World Electric Vehicle Journal  
These recommendations are selected according to the real-time traffic distribution and the context of the road network.  ...  In addition, several advisory systems have been proposed to recommend to drivers the most efficient speed, route, or other decisions to follow towards their targeted destinations.  ...  Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/wevj13060103 fatcat:3lqg6tz7nvcmfjvjgqj3ttkiri

Exploring Factors that Influence Connected Drivers to (Not) Use or Follow Recommended Optimal Routes

Briane Paul V. Samson, Yasuyuki Sumi
2019 Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems - CHI '19  
With the intention to circumnavigate congested roads, their route guidance always follows the basic assumption that drivers always want the fastest route.  ...  We found that while drivers choose a recommended route in urgent situations, many still preferred to follow familiar routes.  ...  Deviations Comparing the estimated travel time of the recommended routes and the actual travel times, deviating at least once made the trips longer by an average of 3.11 minutes (N=53, SD=12.35).  ... 
doi:10.1145/3290605.3300601 dblp:conf/chi/SamsonS19 fatcat:wlxsbojwbfgidczmwvqhqmnpkq

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.  ...  This service gradually learns a user's driving behavior from the user's GPS logs and customizes the fastest route for the user with the help of the Cloud.  ...  To address the above challenges, instead of directly finding the fastest driving route for a particular user, we first record the routes the user has driven with GPS logs and then estimate the travel time  ... 
doi:10.1145/2020408.2020462 dblp:conf/kdd/YuanZXS11 fatcat:gsm75aexobdxzhcm3xosb6lbjy

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  
and also provides the optimal alternate route for destination.  ...  , fuel usage are needed for eco-routing.  ...  2) How these methods learn a user's diver behavior accurately and estimate the travel time of a route for the user precisely? If the answers are effective then the system is valuable.  ... 
doi:10.14257/ijfgcn.2015.8.1.27 fatcat:s6ug5ahqpbh7fpu4cqlk42osqu

Information impact on transportation systems

Sorina Litescu, Vaisagh Viswanathan, Michael Lees, Alois Knoll, Heiko Aydt
2015 Journal of Computational Science  
We developed an agent based model to simulate the effect of drivers using real time information to avoid traffic congestion.  ...  Experiments reveal that the system's performance is influenced by the number of participants that have access to real time information.  ...  Agents travel from origin to destination on the fastest recommended option. Agents select either Route A or Route B at the decision point.  ... 
doi:10.1016/j.jocs.2015.04.019 fatcat:i7h54w5bmnatxo3b4jbj2jpjry

Forecast-augmented Route Guidance in Urban Traffic Networks based on Infrastructure Observations

Matthias Sommer, Sven Tomforde, Jörg Hähner
2016 Proceedings of the International Conference on Vehicle Technology and Intelligent Transport Systems  
The results indicate their benefit in terms of lower travel times and emissions, even under low compliance rates.  ...  These protocols were adapted to utilise forecasts of traffic flows to offer anticipatory and time-dependant DRG for road users.  ...  Each table entry now contains entries for each incoming section, the destination, the recommended next turning and the estimated travel time to this destination.  ... 
doi:10.5220/0005741901770186 dblp:conf/vehits/SommerTH16 fatcat:haw4xkc4mzcydmxjwksei7bqw4

An Approach to Assess the Effect of Currentness of Spatial Data on Routing Quality

Martin Schmidl, Gerhard Navratil, Ioannis Giannopoulos
2021 AGILE: GIScience Series  
Road networks, the main data source for routing, are prone to changes which can have a big impact on the computed route and therefore on travel time.  ...  During navigation these decisions are crucial for being routed to the desired destination (usually going by the shortest or fastest route).  ...  We would like to thank the members of the OSRM-talk mailing list for providing helpful advice in using the OSRM routing engine.  ... 
doi:10.5194/agile-giss-2-13-2021 fatcat:omrhczknivdxznmvwf4uo2vj4i

Time-Dependent Trajectory Regression on Road Networks via Multi-Task Learning

Jiangchuan Zheng, Lionel M. Ni
2013 PROCEEDINGS OF THE THIRTIETH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE AND THE TWENTY-EIGHTH INNOVATIVE APPLICATIONS OF ARTIFICIAL INTELLIGENCE CONFERENCE  
Experiments conducted on both synthetic and real data sets demonstrate the effectiveness of our method and its improved accuracy on travel time prediction.  ...  Other works on route planning and recommendation that have considered temporal factors simply assumed that the temporal dynamics be known in advance as a parametric function over time, which is not faithful  ...  Related Work Traffic mining-based fastest route computation Many approaches have been proposed to recommend fastest route by mining knowledge from historical vehicle trajectories.  ... 
doi:10.1609/aaai.v27i1.8577 fatcat:5tc42sdfinf4flzeyy664bzn5u

Optimal estimates for short horizon travel time prediction in urban areas

Indrė Žliobaitė, Mikhail Khokhlov
2016 Intelligent Data Analysis  
One approach is to predict travel times for route segments, and sum those estimates to obtain a prediction for the whole route. We study how to obtain optimal predictions in this scenario.  ...  One of the main challenges for travel time estimation and prediction in such a setting is how to aggregate data from vehicles that have followed different routes, and predict travel time for other routes  ...  Therefore, travel time is chosen as the target variable given the task to plan the fastest route. 3. Estimating travel time from historical data.  ... 
doi:10.3233/ida-150292 fatcat:76hoeizynbf3xopmuoklxzvzta

DoppelDriver: Counterfactual actual travel times for alternative routes

Daehan Kwak, Daeyoung Kim, Ruilin Liu, Badri Nath, Liviu Iftode
2015 2015 IEEE International Conference on Pervasive Computing and Communications (PerCom)  
Also, we describe the potential usage and benefits of ex-post feedback (i.e. travel time on non-chosen routes) and how snapshots of travel time comparisons can be used to support strategic decision making  ...  Using real taxi GPS data, we investigate whether aggregating ATAs for road segments from other users mimics the ATA for the intended origin-to-destination route.  ...  ACKNOWLEDGMENT We thank Daniele Puccinelli and the anonymous reviewers for their insightful comments. This work was supported in part by NSF grant CNS-1111811 and Google Research Award.  ... 
doi:10.1109/percom.2015.7146525 dblp:conf/percom/KwakKLNI15 fatcat:c4dawmhgfffvheaqvc2sm46nse
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