Data-Driven Traffic Engineering : Understanding of Traffic and Applications Based on Three-Phase Traffic Theory

Front Cover -- Data-driven traffic engineering: Understanding of Traffic and Applications based on Three-Phase Traffic Theory -- Copyright -- Contents -- Aim of the book -- Expected readers -- Scope and outline of the book -- Chapter 1: Introduction -- References -- Chapter 2: How traffic data are measured -- 2.1. Loop detector data -- 2.2. Probe vehicle data -- 2.2.1. Propagating congestion -- 2.2.2. Localized congestion -- 2.2.3. Localized and propagating congestion: A general traffic pattern -- 2.2.4. Localized congestion: Complete freeway blockage (``Megajam´´) -- 2.2.5. Induced congestion: Propagating structures -- 2.2.6. Similar and heterogeneous congested traffic patterns -- 2.2.7. Complex empirical traffic patterns -- 2.2.8. Traffic patterns in urban areas -- 2.3. Camera-based microscopic measurements -- References -- Chapter 3: Analysis of congested traffic pattern features on freeways: A historical overview -- 3.1. About empirical studies of traffic congestion -- 3.2. A brief history of Kerner's three-phase traffic theory -- 3.2.1. The beginning -- 3.2.2. Kerner's synchronized flow as a new traffic phase -- 3.2.3. Paradigm shift in traffic science caused by the discovery of the empirical nucleation nature of a traffic breakdown -- 3.2.4. Kerner's indifferent zone in car following -- 3.2.5. Some milestones of related projects in the past -- 3.2.6. The situation today -- 3.3. Summary of some main hypotheses of Kerner's three-phase traffic theory -- 3.4. Main types of spatiotemporal congested traffic patterns -- 3.5. Detection of congested traffic patterns based on probe vehicles -- 3.5.1. Phase transition points -- 3.5.2. Examples of applications of probe vehicle data for reconstruction of traffic in space and time -- 3.5.3. Prediction of upstream fronts of traffic phases (in particular jam front warning) based on probe vehicle data.