Chiung-Yao Fang Hsiu-Lin Hsueh Sei-Wang Chen National Taiwan Normal University Department of Computer Science and Information Engineering Dangerous Driving Event Analysis System by a Cascaded Fuzzy Reasoning Petri Net

Outline Introduction System flowchart Cascaded fuzzy reasoning Petri net Dangerous driving event analysis system Experimental results Conclusions and future work

Introduction Driver assistance system  Passive methods  Active methods Active driver assistance system  Detection component  Analysis component

Block Diagram of an Active DAS Analysis component Detection component Sensor 1 Sensor 2Sensor n Detection system 1 Detection system 2 Detection system n Dangerous driving event analysis system Warning output … …

Flowchart of the Analysis System Start Data acquisition Driving event integration Degree of danger computation Degree of danger output Behavior analysis of our vehicleInteraction analysis between nearby vehicles and our vehicle CFRPN

Cascaded Fuzzy Reasoning Petri Net (CFRPN)

The Production Rules of FRPN Rule 1: where : confidence vector of rule associated with the only corresponding transition Rule 2: where : confidence vector of the rule related to the corresponding m transitions

Fuzzy Reasoning Algorithm

Some Terminology Lateral distance Forward distance Our vehicle Right- front vehicle Forward distance Lateral distance

Using FRPNs for Reasoning An example  Get the membership values of Lateral distance Position Speed  Input to the fuzzy reasoning Petri net Speed change reasoning Lane change reasoning Integration Our vehicle Preceding vehicle Following vehicle Left- rear vehicle Right vehicle Left- front vehicle Right- front vehicle Left vehicle Right- rear vehicle

Membership Functions Lateral distance Position Speed Lateral distance (m) Position (m) Speed (km/hr)

Example of Lane Change R easoning V o : our vehicle V lf : left-front vehicle (1) : V o moves without lane change. (2) : V o changes to the left lane. (3) : V o changes to the right lane. (4) : V lf moves without changing lane. (5) : V lf changes to the left lane. (6) : V lf changes to the right lane. (7) : V lf and V o are moving in the same lane. (8) : V lf and V o are moving in different lanes.

Example of Lane Change Reasoning Two production rules:  : occurrence possibility that “V lf and V o are moving in the same lane.”  : occurrence possibility that “V lf and V o are moving in different lanes.”

Corresponding FRPN : left-front vehicle and our vehicle are moving in the same lane : left-front vehicle and our vehicle are moving in different lanes

Example of Speed Change Reasoning V o : our vehicle V lf : left-front vehicle (1) : forward distance between V lf and V o is close (2) : speed of V o is slower than that of V lf (3) : speeds of V lf and V o are equal (4) : speed of V o is faster than that of V lf (5) : forward distance between V lf and V o increases (6) : forward distance between V lf and V o remains the same (7) : forward distance between V lf and V o decreases

Example of Speed Change Reasoning Three production rules :  To decide the occurrence possibilities of the following driving events: Forward distance between V lf and V o increases Forward distance between V lf and V o decreases Forward distance between V lf and V o remains unchanged

Corresponding FRPN : forward distance between V lf and V o increases : forward distance between V lf and V o remains the same : forward distance between V lf and V o decreases

Integration Integration rule: : degree of danger of the interaction between V lf and V o

Part of CFRPN Road change reasoning Speed change reasoning Integration

Freeway Driving Event Simulation Objective – provide experimental data Two major stages:  Simulation of freeway environments  Simulation of vehicle behaviors

Simulation of Freeway Environments Given:  Total length of the freeway  Number of toll stations, tunnels, freeway entries and exits Produce:  Total lengths of tunnels  Locations of toll stations, tunnel entries and exits, freeway entries and exits  Locations of road signs

Simulation of Vehicle Behaviors Given :  Vehicle positions and moving directions ( of our vehicle and nearby vehicles) Produce :  Vehicle speed  Lateral distance  Directional signal  Braking signal Our vehicle Preceding vehicle Following vehicle Left- rear vehicle Right vehicle Left- front vehicle Right- front vehicle Left vehicle Right- rear vehicle

Experimental Results Conditions:  Our vehicle moves without lane change.  The left-front vehicle changes its lane to the right.  The speed of our vehicle is faster than that of the left-front one.

Experimental Results Left-front vehicle and our vehicle are moving in the same lane Distance between left-front vehicle and our vehicle decreases Our vehicle moves without changing lane Our vehicle is faster than the left- front one Left-front vehicle changes lane to the right Dangerous

Degrees of Danger of Interactions Between Left- front Vehicle V lf and Our Vehicle V o No. Speed of V o – speed of V lf (Km/hr) Forward distance between Vo and V lf (meter)/(second) Horizontal shift of V o (meters) Horizontal shift of V lf (meters) Degree of danger / / / / / / / / /

Degrees of Danger of Interactions Between Preceding Vehicle V a and Our Vehicle V o No Speed of V o – speed of V a (Km/hr) Distance between V o and V a (meter)/(second) Horizontal shift of V o (meters) Horizontal shift of V a (meters) Degree of danger / / / / / / / / /

Conclusions and Future Work Dangerous driving event analysis system  Reasoning by a cascaded FRPN module  Detection subsystem integration  Warning drivers  Future work: integrate into the driver assistance system Freeway driving event simulation system  Provide experimental data  Support other driver assistance subsystems  Future work: include more road conditions