Micro-simulation of Traffic - Examples & Applications

A leader's front is at 95 m along the lane, a follower's front is at 60 m, and leader length is 5 m. Determine the clear gap.

A follower maintains $s=30\text{ m}$ clear gap at $v_F=15\text{ m/s}$. Calculate the simple clear-gap time diagnostic $h=s/v_F$.

An illustrative model uses $\Delta t=0.50\text{ s}$ with a vehicle moving at a constant $12\text{ m/s}$ during that step. Estimate the travel distance.

A modeled vehicle must merge before a lane end. An illustrative gap-acceptance rule for this single test requires 24 m of usable target-lane gap, while the observed gap is 20 m. Decide whether the modeled change is permitted by this assumed rule.

A field count records 300 vehicles in 20 minutes at a network boundary during a stable demand period. Find the equivalent mean hourly arrival rate.

A simulation runs for 90 minutes in total. The first 15 minutes are reserved for warm-up. Determine the reportable observation duration and its fraction of elapsed run time.

A base model simulates mean corridor travel time of 8.1 minutes while designated calibration observations show 9.0 minutes. Determine relative error.

At one count station, observed hourly volume is $M=800\text{ veh/h}$ and simulated mean is $C=840\text{ veh/h}$. Compute $GEH=\sqrt{2(C-M)^2/(C+M)}$ and explain its role.

Observed travel times are 10 and 12 min; simulated values are 11 and 10 min for the same two periods. Calculate mean absolute percentage error (MAPE).

Calibration counts match well, but independent validation observations show a peak queue of 12 vehicles when the simulation predicts 9. Calculate the relative difference and decide how to proceed.

Across 10 independent seed runs, delay has mean $46.2\text{ s/veh}$ and sample standard deviation $3.6\text{ s/veh}$. Estimate standard error of the sample mean.

Four paired runs show baseline minus alternative mean delay improvements of 4, 6, 2, and 4 s/veh. Estimate mean paired improvement and its standard error.