Feasibility of on-Street Parking Based on Degree of Saturation

Abstract

On-street parking leads to reduced road capacity and decreased traffic performance of the certain road. Therefore, this study was conducted to evaluate the feasibility of on-street parking based on road performance. The study was conducted at Central Business District namely Peunayong, Banda Aceh. Based on the Indonesian Highway Capacity Manual (IHCM) one of the performance parameter values is Degree of Saturation (DS). The data needed for calculation of DS are the geometric conditions, traffic volume and the side frictions. The results indicate that on-street parking facilities on segment 2 of Khairil Anwar Street should be evaluated, as the DS value is greater than 0.75 (unstable road condition), by changing parking patterns into a parallel configuration or eliminating parking facilities. Furthermore, the parking configuration of R.A. Kartini Street also needs to be rearranged. Despite the stable road performance, this road is uncomfortable to pass because there is only one lane remained due to unfeasible parking patterns and existence of street market along the segment. The road performance of Khairil Anwar Street (segment 1), Ahmad Yani Street, W.R Supratman Street, T.P. Polem Street, Twk. Daudsyah Street and Ratu Safiatuddin Street is in stable condition, with DS < 0.75. This indicating that on-street parking facilities can be maintained. While as for the W.R. Supratman and Ahmad Yani Street should be evaluated in year of 2019 to avoid traffic jam along this corridors.

Intelligent Management of On-street Parking Provision for the Autonomous Vehicles Era

“…Thus, our results indicate a complex correlation for this on-street parking problem. These findings extend previous studies [19], [21], which attempted to prove a negatively correlated, linear relationship between on-street parking and transport efficiency. 7 indicates a maximum difference of 55.60s per AV at the max flow rate of 70 veh/h.…”

“…Previous research concerning the on-street parking problem predominantly concentrates on three areas: the demand, supply and pricing for parking [15], [16]; safety and delay impacts of curb parking behaviours [17], [18]; the impact of on-street parking on traffic operations [19], [20]. A subset of studies from the third group has investigated how onstreet parking patterns can have an impact on such traffic operations [21]- [23]. To address this issue, these studies used cellular automata models [8], queuing models including the M/M/∞ model [24], M/M/C model [25] and agent-based models [26] to estimate the additional travel cost and traffic congestion caused by on-street parking manoeuvres.…”

“…A similar approach was used by Wang et al [28], who minimised cruising distances, walking distance and coverage of amenities to balance on-street and off-street parking supply. Besides these variables, road capacity [19], [21], cruising time [29] and parking service rate [26] are all objective variables options according to previous studies. However, few studies have minimised traffic delay to obtain the optimal distribution of curb parking.…”

“…Due to the complexity of interactions between on-street parking behaviours and transport operations, previous mathematical models often simplified the representation of traffic congestion, vehicular delays and microscopic driving manoeuvres [20], [21], [23], [28]. Such a simplification would lead to an approximation of the system or even inaccurate outcomes.…”