Warning: pg_query(): Query failed: ERROR: missing chunk number 0 for toast value 29512337 in pg_toast_2619 in /dati/webiit-old/includes/database.pgsql.inc on line 138 Warning: ERROR: missing chunk number 0 for toast value 29512337 in pg_toast_2619 query: SELECT data, created, headers, expire, serialized FROM cache_page WHERE cid = 'https://www-old.iit.cnr.it/node/59294' in /dati/webiit-old/includes/database.pgsql.inc on line 159 Warning: pg_query(): Query failed: ERROR: missing chunk number 0 for toast value 29512337 in pg_toast_2619 in /dati/webiit-old/includes/database.pgsql.inc on line 138 Warning: ERROR: missing chunk number 0 for toast value 29512337 in pg_toast_2619 query: SELECT data, created, headers, expire, serialized FROM cache_page WHERE cid = 'https://www-old.iit.cnr.it/node/59294' in /dati/webiit-old/includes/database.pgsql.inc on line 159 Heterogeneous Links Between Real-World Driving Volatility and Driving Stress Using Integrated CAN-Bus and Biometric Health Data | IIT - CNR - Istituto di Informatica e Telematica
IIT Home Page CNR Home Page

Heterogeneous Links Between Real-World Driving Volatility and Driving Stress Using Integrated CAN-Bus and Biometric Health Data

Links between real-world driving stress and driving volatility are not well understood. The seemingly unstructured big data generated by computational and physical components of cyber-physical systems allows examination of the links between volatility in microscopic driving behaviors and real-world driving stress. A natural experiment is conducted to collect over 0.2 million geo-referenced temporal samples of real-world driving behavior and health biomarkers for 150 driving sessions/trips. The integrated kinematic and biometric data are linked with detailed roadway geometric data from OpenStreetMap. A rigorous data analytic methodology is proposed to measure driving volatility and stress (captured by health biomarkers) at the trip-level. Owing to the important methodological issues related to systematic and random heterogeneity, fixed parameter, random parameter, and random parameter models with extension to heterogeneity-in-means are estimated to examine the links between driving stress and driving volatility at the trip level. A sizable portion of drivers’ instantaneous heart rates does not fall in the normal range (60 to 100 heart beats per minute). Statistically significant and positive correlations are observed between driving volatility measures (based on speed, vehicular jerk) and driving stress. Motorways are associated with lower stress. Contrarily, larger standard deviation of number of lanes positively correlates with driving stress. Several of the heterogeneous associations captured by random parameters vary itself as a function of observed factors. The substantial heterogeneity in associations across the trips underscores the importance of accounting for observed and unobserved heterogeneity to avoid misleading inferences. Relevance of the results for proactive driver assistance systems is discussed.

Transportation Research Board Annual Meeting, Washington, USA, 2021

Autori esterni: Behram Wali (MIT), Sebastiano Milardo (MIT), Umberto Fugiglando (MIT), Carlo Ratti (MIT)
Autori IIT:

Tipo: Contributo in atti di convegno
Area di disciplina: Computer Science & Engineering

File: TRBAM-S-20-02067.pdf

Attività: Algoritmica per reti wireless