A Representative Driving Cycle for the Southern Expressway Compared to Existing Driving Cycles

Abstract

This paper critically evaluates traffic related performance of the Southern Expressway (SEW) in Sri Lanka using basic traffic engineering parameters such as average speeds, acceleration-deceleration changes, root mean square acceleration, and positive kinetic energy. An on-road speed/time data sample was collected, and a driving cycle was developed to compare to well-established driving cycles worldwide. Ten traffic-related parameters were identified in order to evaluate the SEW using the collected data. Data was collected in proportion to the number of actual trips made by users on an average day using the on-board method; the segment-based method was adopted for cycle construction. Previously identified traffic-related parameters were used to evaluate and select representative cycle for the SEW from candidate cycles. The selected driving cycle was 1213 s in length. Average speed, average acceleration, and average deceleration were 80.6 km/h, 0.45, and 0.25 m/s 2 , respectively. Results showed that both average and running speeds of the SEW were significantly below compared to its posted speed limit, thereby increasing the travel time. Comparatively smooth driving behavior will improve the SEW's fuel and emission performances. This study created a platform with which future studies can evaluate performances of all operational and future expressways.

Use of the Bezier Curves for a Vehicles Driving Cycles' Modeling

“…There are four main methods of the driving cycles' creation, namely: microtrip-based, segmentbased, pattern classification and modal cycle construction. Each of them has its own advantages and disadvantages and discerns by different complexity [17][18][19].…”

“…It is a common knowledge that a driving cycle in a graphic interpretation is a set of segments that include an acceleration of a vehicle, a movement with constant speed and braking (deceleration). The researches of real driving cycles, previously published [17,[20][21][22][23][24], are based on determination of extreme indices of the elementary sections of a cycle and of their deviation from standardized driving cycles.…”

Statistically supported real driving emission calibration: Using cycle generation to provide vehicle-specific and statistically representative test scenarios for Euro 7

“…is particularly suitable for development and validation. 9,11–20 Therefore, the objective is to develop a uniform test and validation methodology for reliable compliance with RDE requirements and robust emission calibration. The first step toward this goal must consequently be the development of a methodology that allows existing tests and driving profiles to be compared quantitatively.…”

“…10 Current approaches either deal with the creation of geographically and regionally realistic driving scenarios or with synthetic profiles with significantly high driving dynamics aiming to cause maximized emissions. 10–17,19 The individual combination of vehicle and powertrain, the influence of calibration and performance of exhaust after-treatment systems over lifetime are not considered in these methods. 10,38 The “WLTP random cycle-generator” approach considered by the European Union (EU) takes vehicle-related input parameters such as vehicle mass, driving resistance coefficients and effective engine power into account when creating the cycle.…”

“…10,38 The “WLTP random cycle-generator” approach considered by the European Union (EU) takes vehicle-related input parameters such as vehicle mass, driving resistance coefficients and effective engine power into account when creating the cycle. Two Markov chains (commonly used for cycle generation) whose statistical background is based on the worldwide harmonized light duty vehicles test cycle (WLTC) database are used to 13–16,39–42…”