How Far Have We Delved Deep into The Travel Time Prediction Methods? A Review of the Studies from ۲۰۱۰ to ۲۰۲۰

According to statistics, congestion is becoming a great challenge for metropolitan areas, andin congested traffic regimes, prediction of travel time is necessary both for travelers andtransportation planners. Needless to say, travel time can impact various aspects of trips, soprecise and reliable prediction of travel time can lead to an enhancement in congestion reliefand routing problems. Recent advances in modeling techniques and data collection procedurehas faced planners with some real challenges: What are the most valid methods for predictingtravel time? How data sources can help planners lessen the required efforts for achieving areliable prediction? This study is an attempt to depict a broad framework in which numerousstudies, starting from ۲۰۱۰ to ۲۰۲۰ were assessed carefully. The results have revealed thatrecent efforts in the field of data collection can provide insight into the information requiredfor modeling travel time. Also, many authors relied on hybrid artificial intelligence (AI)methods, which represent better performance than single AI methods in terms of reducingprediction error.

کلیدواژه ها:

Travel time prediction ، Machine learning ، Modeling