Anticipating Spatial–Temporal Distribution of Regional Highway Traffic with Online Navigation Route Recommendation

Yuli Fan, Qingming Zhan (), Huizi Zhang, Zihao Mi and Kun Xiao
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Yuli Fan: School of Urban Design, Wuhan University, Wuhan 430072, China
Qingming Zhan: School of Urban Design, Wuhan University, Wuhan 430072, China
Huizi Zhang: Power China Zhongnan Engineering Co., Ltd., Changsha 410014, China
Zihao Mi: Hubei General Institute of Planning and Design, Wuhan 430071, China
Kun Xiao: Wuhan Geomatics Institute, Wuhan 430010, China

Sustainability, 2022, vol. 15, issue 1, 1-19

Abstract: Detailed anticipation of potential highway congestion is becoming more necessary, as increasing regional road traffic puts pressure on both highways and towns its passes through; tidal traffic during vacations and unsatisfactory town planning make the situation even worse. Remote sensing and on-site sensors can dynamically detect upcoming congestion, but they lack global and long-term perspectives. This paper proposes a demand-network approach that is based on online route recommendations to exploit its accuracy, coverage and timeliness. Specifically, a presumed optimal route is acquired for each prefecture pair by accessing an online navigation platform with its Application Programming Interface; time attributes are given to down-sampled route points to allocate traffic volume on that route to different hours; then different routes are weighted with the origin–destination traveler amount data from location-based services providers, resulting in fine-level prediction of the spatial–temporal distribution of traffic volume on highway network. Experiments with data in January 2020 show good consistency with empirical predictions of highway administrations, and they further reveal the importance of dealing with congestion hotspots outside big cities, for which we conclude that dynamic bypassing is a potential solution to be explored in further studies.

Keywords: regional transportation; traffic congestion; online navigation; travel route; origin–destination (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
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