2016/04/30 by Albert Solé‐Ribalta, Albert Solé-Ribalta, Sergio Gómez +2
Computer Science · Engineering · Physics and Astronomy · Social Sciences · #Air quality index #Business #Computer science #Congestion pricing #Economics #Engineering #Environmental economics #Geography #Hotspot (geology) #Human Mobility and Location-Based Analysis #Meteorology #Microeconomics #Population #Price elasticity of demand #Road pricing #Singapore Area Licensing Scheme #Traffic Prediction and Management Techniques #Traffic congestion #Transport engineering #Transportation Planning and Optimization #Traverse #cs.CY #physics.soc-ph
paper · pdf · doi:10.1007/s11067-017-9349-y
published as Networks and Spatial Economics 18 (2018) 33-50 · 12 pages, 10 figures
openalex publication_date 2017/08/12 · arxiv created 2018/04/26 · arxiv updated 2018/04/27 · openalex created_date 2020/11/23 · openalex updated_date 2026/08/05
The rapid growth of population in urban areas is jeopardizing the mobility and air quality worldwide. One of the most notable problems arising is that of traffic congestion which in turn affects air pollution. With the advent of technologies able to sense real-time data about cities, and its public distribution for analysis, we are in place to forecast scenarios valuable to ameliorate and control congestion. Here, we analyze a local congestion pricing scheme, hotspot pricing, that surcharges vehicles traversing congested junctions. The proposed tax is computed from the estimation of the evolution of congestion at local level, and the expected response of users to the tax (elasticity). Results on cities' road networks, considering real-traffic data, show that the proposed hotspot pricing scheme would be more effective than current mechanisms to decongest urban areas, and paves the way towards sustainable congestion in urban areas.